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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Veröffentlicht in:Journal of combinatorial optimization Jg. 50; H. 1; S. 2
Hauptverfasser: Mombelli, Aurélien, Quilliot, Alain
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Springer US 01.08.2025
Springer Nature B.V
Schlagworte:
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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Zusammenfassung: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.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1382-6905
1573-2886
DOI:10.1007/s10878-025-01326-y