Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1- 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ identify a long-horizon optimized plan; determine plant configuration result data indicating whether a number of blenders associated with the processing plant is greater than or equal to a number of concurrent products ”- are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example the language in the context of this claim encompasses that the user mentally could make a decision, observation, and calculation. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements- : “ An apparatus for generating at least one optimized operational parameter associated with a processing plant utilizing a dual-horizon optimization process, the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to … and generate the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Accordingly these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “ An apparatus for generating at least one optimized operational parameter associated with a processing plant utilizing a dual-horizon optimization process, the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to … and generate the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). generating an optimized operational parameter using a short horizon based on a long horizon optimized plan is considered to be well-understood, routine, conventional activity – US 20210072742 [0006] the operations include performing a first optimization of the first objective function to generate a short-term maintenance and replacement schedule for the building equipment over a duration of the short-term horizon. In some embodiments, the operations include using a result of the first optimization to perform a second optimization of a second objective function to generate a long-term maintenance and replacement schedule for the building equipment over a duration of a long-term horizon . Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ indicates that the number of blenders is greater than or equal to the number of concurrent products ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “ where the plant configuration result data… wherein to generate the at least one optimized operational parameter the apparatus is caused to: apply at least one value of the long-horizon optimized plan as the at least one optimized operational parameter to control at least one physical component of the processing plant ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 3 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ an average product run rate determined from the long-horizon optimized plan ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “ the apparatus further caused to: set at least one blender outlet target flowrate to an average product run rate ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ indicates that the number of blenders is determined not greater than the number of concurrent products and wherein the plant configuration result data indicates that the number of blenders is equivalent to a number of primary products ”, and “ and identify a short-horizon optimized plan that represents a change from the closest primary product to the secondary product as a specification disturbance ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “wherein the plant configuration result data… wherein to generate the optimal operational parameters the apparatus is caused to: for each secondary product of at least one secondary product, assign a closest primary product associated with the secondary product ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 5 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ indicates that the number of blenders is determined not greater than or equal to the number of concurrent products … indicates that the number of blenders is less than a number of primary products, and wherein the plant configuration results indicates that the processing plant is not agile ”, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “ wherein the palnt configuration result data… and wherein the plant configuration result… and wherein to generate the at least one optimal operational parameter the apparatus is caused to: set at least one first ideal resting value for at least one product run rate of at least one blender based at least in part on at least one demand rate of the long-horizon optimized plan; set at least one second ideal resting value for at least one process unit based at least in part on at least one unit target represented in the long-horizon optimized plan; and set at least one third ideal resting value for at least one blender recipe based at least in part on at least one aggregate blend recipe represented in the long-horizon optimized plan. ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 6 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ indicates that the number of blenders is determined not greater than the number of concurrent products ”, and “ indicates that the processing plant is agile and … , and wherein to generate the at least one optimized operational parameter the apparatus is caused to: identify a short-horizon optimized plan using the short-horizon optimization process that does not utilize the long-horizon optimized plan; and determine the at least one optimized operational parameter from the short-horizon optimized plan … that the processing plant is configured where changing product or changing run-rate does not impact optimization of a target parameter ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “ wherein the plant configuration result data… wherein the plant configuration results indicates that the number of blenders is less than a number of primary products, wherein the plant configuration results ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 7 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ indicates that the number of blenders is determined not greater than the number of concurrent products … indicates that the number of blenders is less than a number of primary products, wherein the plant configuration result data indicates that the processing plant is agile … wherein to generate the at least one optimized operational parameter the apparatus is caused to: generate a short-horizon optimized plan including at least one anchoring point based at least in part on the long-horizon optimized plan; and include at least one ideal resting value in the short-horizon optimized plan based at least in part on the long-horizon optimized plan ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “wherein the plant the plant configuration result data.. wherein the plant configuration result data… and that the processing plant is configured where changing product or changing run-rate does impact optimization of a target parameter ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 8 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ an estimated long-horizon optimized plan representing operation of the processing plant with addition of at least one new blender ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The additional element of “the apparatus further caused to: generate improvement data associated with ” , which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 9 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ the apparatus further caused to: determine that the improvement data satisfies an improvement threshold; and generate an indication that the improvement data satisfies the improvement threshold ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 10 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “ wherein the processing plant includes at least one rundown blender and at least one batch blender …” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook (" Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). The claim recites “ wherein the apparatus generates the at least one optimized operational parameter utilized to control the at least one rundown blender, and wherein the apparatus is caused to: generate, using a different optimization process, at least one second optimized operational parameter utilized to control the at least one batch blender ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 11 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ identify a data identifier that represents a particular value for the plant configuration result data, wherein the particular value indicates whether the processing plant: ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The claim recites “the apparatus further caused to: wherein the apparatus generates the at least one optimized operational parameter based at least in part on the short-horizon optimization process corresponding to the data identifier ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 12 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ identify a data identifier from a set of candidate data identifiers, wherein the data identifier represents at least one plant characteristic associated with the processing plant, wherein the plant characteristic at least indicates whether the processing plant includes the number of blenders that is greater than or equal to the number of concurrent products ” under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas . The claim recites “the apparatus further caused to:… wherein the apparatus generates the at least one optimized operational parameter utilizing the short-horizon optimization process corresponding to the data identifier ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well-understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 13 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “ wherein the number of blenders represents a number of physical blenders in the processing plant ” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook (" Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 14 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1 . Additionally the claim recites- “ wherein the number of blenders represents a number of virtual blenders associated with the processing plant ” which falls under field of use and technological environment- see MPEP 2106.05(h) Parker v. Flook (" Flook established that limiting an abstract idea to one field of use or adding token postsolution components did not make the concept patentable"). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 15 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim inherits the mental abstract idea from claim 1. The claim recites “ the apparatus further caused to: cause configuration of a lift schedule based at least in part on the at least one optimized operational parameter ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f) - considered to be well- understood, routine, conventional activity Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 16 is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites “ identifying a long-horizon optimized plan; determining plant configuration result data indicating whether a number of blenders associated with the processing plant is greater than or equal to a number of concurrent products ”- are processes that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, nothing in the claim element precludes the step from practically being performed in the mind. For example the language in the context of this claim encompasses that the user mentally could make a decision, observation, and calculation. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. This judicial exception is not integrated into a practical application. In particular, the claim recites additional elements- : “ A computer-implemented method for generating at least one optimized operational parameter associated with a processing plant utilizing a dual-horizon optimization process comprising … and generating the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data ” which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Accordingly these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of “ A computer-implemented method for generating at least one optimized operational parameter associated with a processing plant utilizing a dual-horizon optimization process comprising … and generating the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data ”, which is simply using a computer as a tool to perform abstract ideas -Mere instructions to apply an exception – see MPEP 2106.05(f). generating an optimized operational parameter using a short horizon based on a long horizon optimized plan is considered to be well-understood, routine, conventional activity – US20210072742 [0006] the operations include performing a first optimization of the first objective function to generate a short-term maintenance and replacement schedule for the building equipment over a duration of the short-term horizon. In some embodiments, the operations include using a result of the first optimization to perform a second optimization of a second objective function to generate a long-term maintenance and replacement schedule for the building equipment over a duration of a long-term horizon . Therefore these do not integrate a judicial exception into a practical application or provide significantly more. The claim is not patent eligible. Claim 17 is rejected under 35 U.S.C. 101 for similar reasons as claim 12 Claim 18 is rejected under 35 U.S.C. 101 for similar reasons as claim 15 Claim 19 is rejected under 35 U.S.C. 101 for similar reasons as claim 9 Claim 20 is rejected under 35 U.S.C. 101 for similar reasons as claim 16 Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. Claim(s) 1- 13, and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over L aval et al. (US 20120296690A1 , herein Varvarezos ), in view of Castillo et al. ( “Inventory pinch gasoline blend scheduling algorithm combining discrete-and continuous-time models , herein Castillo ) . Regarding claim 1, Varvarezos teaches An apparatus for generating at least one optimized operational parameter associated with a processing plant utiliz ing a … horizon o ptimization process ( Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0095] t he time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single produc t, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days) , the apparatus comprising at least one processor and at least one non-transitory memory including computer-coded instructions thereon, the computer coded instructions, with the at least one processor, cause the apparatus to ([0012] Central processor unit 84 is also attached to system bus 79 and provides for the execution of computer instructions , [0112] Memory 90 provides volatile storage for computer software instructions 92 and data 94 used to implement an embodiment of the present invention (e.g., rundown blending modeler 400) : identify a long-horizon optimized plan (Fig. 5-8 [0095] the time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single product, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days) ; Varvarezos does not teach dual-horizon… determine plant configuration result data indicating whether a number of blenders associated with the processing plant is greater than or equal to a number of concurrent products; and generate the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data. Castillo teaches dual-horizon ( page 616 Fig . 5 , page 613 Col. Right , lines 13-15 Given a short-term scheduling horizon, a set of blend components and their properties , page 618 Col. Left, lines 35-38 scheduling horizon, i.e. the horizon is portioned is subintervals denoted as L-intervals; and these subintervals are solved sequentially starting from the first one ) … determine plant configuration result data indicating whether a number of blenders associated with the processing plant is greater than or equal to a number of concurrent products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) and generate the at least one optimized operational parameter using a short-horizon optimization process based at least in part on the long-horizon optimized plan and the plant configuration result data ( page 616 Fig. 5, page 613 Col. Right , lines 13-15 Given a short-term scheduling horizon, a set of blend components and their properties, page 618 Col. Left, lines 35-38 scheduling horizon, i.e. the horizon is portioned is subintervals denoted as L-intervals; and these subintervals are solved sequentially starting from the first one ) . It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Varvarezos ’s teaching rundown blending optimization apparatus with Castillo ’s teaching of blend scheduling algorithm that indicates the number of blenders and product . The combined teaching provides an expected result of rundown blending optimization apparatus including a blending scheduling algorithm that indicates the number of blenders and product . Therefore, one of ordinary skill in the art would be motivated to improve accuracy in the blending optimization process. Regarding claim 2, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, … , wherein to generate the at least one optimized operational parameter the apparatus is caused to: apply at least one value of the long-horizon optimized plan as the at least one optimized operational parameter to control at least one physical component of the processing plant ( Varvarezos , Fig. 5-8 [0095] the time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single product, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days , [0059] Parameters: RD( c,t ), rundown for component (c) at time (t), Prop( i,c,t ), value for property ( i ) of component (c) at time (t), NB(c), the number of simultaneous blends for component (c), typically 1… t he parameter NB(c) controls the number of simultaneous blends that can use a rundown component in a single time period , [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations ) ; or apply the at least one value of the long-horizon optimized plan as the at least one optimized operational parameter to set at least one ideal resting value. Castillo further teaches wherein the plant configuration result data indicates that the number of blenders is greater than or equal to the number of concurrent products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) Regarding claim 2, the combination of Varvarezos and Castillo teach The apparatus according to claim 2, the apparatus further caused to: set at least one blender outlet target flowrate to an average product run rate determined from the long-horizon optimized plan ( Varvarezos , [0055] separate the rundown components into multiple streams of potentially different flow and qualities … the flow should be dispositioned into only one of the splitter output streams, then each stream should be designated as semi-continuous with a minimum value equal to the entire input flow , [0059] each rundown blend event is given an earliest start and latest stop to define the window of time in which it can take place. The set of times for the rundown component as well as the earliest start and latest stop for the associated blend event determine the number of periods in the set T for that blend and component combination , [0117] modeler 400 transmits the optimized schedule to other plant applications, such as blending control or plant process control systems. There, the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0100] It takes two days because blend event 70 a uses 4.0 KBbl of rundown component 1, at a rate of 2.0 KBb1/day. Blend event 70 a also uses 21.45 KBb1 of rundown component 2. The usage of this component in blend event 70 a starts on October 27 at 12:00 am and ends on October 29 at 11:50 pm. The rate for the first two days is 7.0 KBb1/day and for October 29 the rate is 7.5 KBb1/day, so blend event 70 a takes just under three days to consume 21.45 KBb1of rundown component 2 ) . Regarding claim 4, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, … wherein to generate the optimal operational parameters the apparatus is caused to: for each secondary product of at least one secondary product, assign a closest primary product associated with the secondary product; and identify a … horizon optimized plan that represents a change from the closest primary product to the secondary product as a specification disturbance ( Varvarezos , Fig. 5-8, [0005] no room for producing more high-priced products and there is no opportunity for high-value component sales, benefits can be realized by reducing the operating cost of the refinery by lowering the demand on units that produce high-value components , [0007] Sequencing refinery operations events can include moving refinery operations events, and switching and/or splitting rundown component operations between refinery products and/or associated tanks Splitting rundown component operations can include changing qualities of component streams. Examples of refinery products include gasoline (e.g., regular, premium), diesel (e.g., road, off-road, marine), heating oil (e.g., light, medium, heavy), kerosene, aviation gasoline, jet fuel, distillates, fuel oil, and bunker fuel , ([0117] modeler 400 transmits the optimized schedule to other plant applications, such as blending control or plant process control systems. There, the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations ) . C astillo further teaches … wherein the plant configuration result data indicates that the number of blenders is determined not greater than the number of concurrent products and wherein the plant configuration result data indicates that the number of blenders is equivalent to a number of primary products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) , … short-horizon ( page 616 Fig. 5, page 613 Col. Right , lines 13-15 Given a short-term scheduling horizon, a set of blend components and their properties, page 618 Col. Left, lines 35-38 scheduling horizon, i.e. the horizon is portioned is subintervals denoted as L-intervals; and these subintervals are solved sequentially starting from the first one ) Regarding claim 5, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, … and wherein the plant configuration results indicates that the processing plant is not agile, and wherein to generate the at least one optimal operational parameter the apparatus is caused to ( Varvarezos , [0058] If the optimization blending step fails, meaning that an acceptable solution cannot be found at step 460, the user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 , Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0095] t he time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single produc t, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days) ) : set at least one first ideal resting value for at least one product run rate of at least one blender based at least in part on at least one demand rate of the long-horizon optimized plan ( Fig. 5-8, [0005] The objective of product blending operations in a refinery is to meet all the shipment commitments on schedule, while meeting all the quality specifications , [0058] user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490 ) ; set at least one second ideal resting value for at least one process unit based at least in part on at least one unit target represented in the long-horizon optimized plan; and set at least one third ideal resting value for at least one blender recipe based at least in part on at least one aggregate blend recipe represented in the long-horizon optimized plan ( Fig.4, [0058] Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 , [0051] Adjust the operation (rate or properties) of a blend component production unit ) . Castillo further teaches wherein the plant configuration result data indicates that the number of blenders is determined not greater than or equal to the number of concurrent products, and wherein the plant configuration results indicates that the number of blenders is less than a number of primary products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) Regarding claim 6, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, … wherein the plant configuration results indicates that the processing plant is agile and that the processing plant is configured where changing product or changing run-rate does not impact optimization of a target parameter ( Varvarezos , [0058] If the optimization blending step fails, meaning that an acceptable solution cannot be found at step 460, the user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 , Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0095] t he time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single produc t, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days , [0051] Adjust the operation (rate or properties) of a blend component production unit ) ) , Castillo further teaches wherein the plant configuration result data indicates that the number of blenders is determined not greater than the number of concurrent products, wherein the plant configuration results indicates that the number of blenders is less than a number of primary products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) , and wherein to generate the at least one optimized operational parameter the apparatus is caused to: identify a short-horizon optimized plan using the short-horizon optimization process that does not utilize the long-horizon optimized plan; and determine the at least one optimized operational parameter from the short-horizon optimized plan ( page 616 Fig. 5, page 613 Col. Right , lines 13-15 Given a short-term scheduling horizon, a set of blend components and their properties, page 618 Col. Left, lines 35-38 scheduling horizon, i.e. the horizon is portioned is subintervals denoted as L-intervals; and these subintervals are solved sequentially starting from the first one ) . Regarding claim 7, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, … wherein the plant configuration result data indicates that the processing plant is agile and that the processing plant is configured where changing product or changing run-rate does impact optimization of a target parameter, and wherein to generate the at least one optimized operational parameter the apparatus is caused to ( Varvarezos , Fig. 4, [0058] If the optimization blending step fails, meaning that an acceptable solution cannot be found at step 460, the user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 , Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0095] t he time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single produc t, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days) ) : … and include at least one ideal resting value in the short-horizon optimized plan based at least in part on the long-horizon optimized plan ( Fig. 5-8, [0005] The objective of product blending operations in a refinery is to meet all the shipment commitments on schedule, while meeting all the quality specifications , [0058] user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490 ) . Castillo further teaches wherein the plant configuration result data indicates that the number of blenders is determined not greater than the number of concurrent products, wherein the plant configuration result data indicates that the number of blenders is less than a number of primary products ( page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) , generate a short-horizon optimized plan including at least one anchoring point based at least in part on the long-horizon optimized plan ( page 616 Fig. 5, page 613 Col. Right , lines 13-15 Given a short-term scheduling horizon, a set of blend components and their properties, page 618 Col. Left, lines 35-38 scheduling horizon, i.e. the horizon is portioned is subintervals denoted as L-intervals; and these subintervals are solved sequentially starting from the first one ) . Regarding claim 8, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, the apparatus further caused to: generate improvement data associated with an estimated long-horizon optimized plan representing operation of the processing plant ( Varvarezos , [0058] If the optimization blending step fails, meaning that an acceptable solution cannot be found at step 460, the user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 , Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or reinitializes the control system's operations , [0095] t he time horizon of interest is 16 days. During the time horizon, there are six rundown blend events for a single produc t, [0096] The bottom of the chart shows the time horizon, from October 27 to November 12, or 16 days ) Castillo further teaches with addition of at least one new blender ( Fig, 5, page 620 Table 1, page 614 Fig. 1, page 617 Col. Left lines 22-40 all blenders work at some point during the scheduling horizon (this equation assumes that the number of blend runs required is greater than the number of blenders)… establishes that the delivered amount must be equal to the demand, page 613, Col. Right, lines 25-26 A blender can produce at most one product at any time. Once it begins blending, it must operate for some minimum time before it can switch to another product) . Regarding claim 9, the combination of Varvarezos and Castillo teach The apparatus according to claim 8, the apparatus further caused to: determine that the improvement data satisfies an improvement threshold; and generate an indication that the improvement data satisfies the improvement threshold ( Varvarezos , [0024] operational constraints such as minimum thresholds for components into blends are modeled via the use of discrete variables. All optimized event quantities, such as blend, shipment, receipt, and transfer, can also have threshold limits (e.g., a transfer event can be of either 0 volume or at least 1000 Bbls ). Those event quantities are also modeled through discrete variables , [0058] If the optimization blending step fails, meaning that an acceptable solution cannot be found at step 460, the user is prompted to modify settings at step 470 for the model and run step 440 again. Once the optimization step 450 is successful, the blending simulation is updated at step 480 along with the results and trends in the application. The user can then choose to publish the updated model to the database at step 490, if desired, and exit the application at step 495 ). Regarding claim 10, the combination of Varvarezos and Castillo teach The apparatus according to claim 1, wherein the processing plant includes at least one rundown blender ( Varvarezos , [0013] FIG. 2 is a schematic illustration of multi-period blending optimization with rundown blending according to this invention) … , wherein the apparatus generates the at least one optimized operational parameter utilized to control the at least one rundown blender, and wherein the apparatus is caused to ( Fig. 5-8, [0117] the optimized schedule (its output values) provide new value range (input value) to parameters and variables of the control system. This updates or