Synchronizing production planning and job scheduling: MILP models and exact algorithms

We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through transfer transactions , which become the key components of the resulting scheduling problem. This Synchronized Resource Production/Job Processing problem...

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Published in:	Journal of combinatorial optimization Vol. 50; no. 1; p. 2
Main Authors:	Mombelli, Aurélien, Quilliot, Alain
Format:	Journal Article
Language:	English
Published:	New York Springer US 01.08.2025 Springer Nature B.V
Subjects:	Algorithms Benders decomposition Collaboration Combinatorics Convex and Discrete Geometry Decomposition Energy Hypotheses Integer programming Linear programming Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Mixed integer Operations Research/Decision Theory Optimization Production costs Production planning Production scheduling Robots Scheduling Storage tanks Synchronism Theory of Computation Vehicles Scheduling 90-10 Brand and cut A path search algorithm 90C11 Bender’s decomposition
ISSN:	1382-6905, 1573-2886
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Abstract	We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through transfer transactions , which become the key components of the resulting scheduling problem. This Synchronized Resource Production/Job Processing problem ( SRPJP ) problem typically arises when the resource is a form of renewable energy (e.g., hydrogen, photovoltaic) stored in tanks or batteries. We first cast SRPJP into the Mixed-Integer Linear Programming (MILP) format and handle it through a branch-and-cut process involving specific No _ Antichain constraints derived from the structure of the feasible transfer transactions . Subsequently, we explore another approach, which involves eliminating non-binary decision variables and applying a Benders decomposition scheme. Finally, we reformulate the SRPJP problem as a path search problem, which we efficiently handle by designing a tailored adaptation of the A* algorithm.
AbstractList	We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through transfer transactions , which become the key components of the resulting scheduling problem. This Synchronized Resource Production/Job Processing problem ( SRPJP ) problem typically arises when the resource is a form of renewable energy (e.g., hydrogen, photovoltaic) stored in tanks or batteries. We first cast SRPJP into the Mixed-Integer Linear Programming (MILP) format and handle it through a branch-and-cut process involving specific No _ Antichain constraints derived from the structure of the feasible transfer transactions . Subsequently, we explore another approach, which involves eliminating non-binary decision variables and applying a Benders decomposition scheme. Finally, we reformulate the SRPJP problem as a path search problem, which we efficiently handle by designing a tailored adaptation of the A* algorithm. We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through transfer transactions, which become the key components of the resulting scheduling problem. This Synchronized Resource Production/Job Processing problem (SRPJP) problem typically arises when the resource is a form of renewable energy (e.g., hydrogen, photovoltaic) stored in tanks or batteries. We first cast SRPJP into the Mixed-Integer Linear Programming (MILP) format and handle it through a branch-and-cut process involving specific No_Antichain constraints derived from the structure of the feasible transfer transactions. Subsequently, we explore another approach, which involves eliminating non-binary decision variables and applying a Benders decomposition scheme. Finally, we reformulate the SRPJP problem as a path search problem, which we efficiently handle by designing a tailored adaptation of the A* algorithm.
ArticleNumber	2
Author	Quilliot, Alain Mombelli, Aurélien
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Cites_doi	10.1111/mice.12246 10.1007/978-3-030-45308-4_1 10.1016/j.cie.2016.08.021 10.1080/00207543.2010.532908 10.1016/S0377-2217(97)00030-1 10.1145/1067309.1067324 10.1007/978-3-540-24777-7 10.1016/j.ejor.2017.02.024 10.1016/j.ejco.2021.100007 10.1109/MILCOM.2008.4753629 10.1109/TSSC.1968.300136 10.1016/j.cor.2014.01.011 10.1016/0095-8956(80)90079-9 10.1057/palgrave.jors.2601026 10.1007/s11081-019-09447-0 10.1155/2019/5075671 10.1080/00207543.2013.860251
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SubjectTerms	Algorithms Benders decomposition Collaboration Combinatorics Convex and Discrete Geometry Decomposition Energy Hypotheses Integer programming Linear programming Mathematical Modeling and Industrial Mathematics Mathematics Mathematics and Statistics Mixed integer Operations Research/Decision Theory Optimization Production costs Production planning Production scheduling Robots Scheduling Storage tanks Synchronism Theory of Computation Vehicles
Title	Synchronizing production planning and job scheduling: MILP models and exact algorithms
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