{"title":"同步生产计划和作业调度:MILP模型和精确算法","authors":"Aurélien Mombelli, Alain Quilliot","doi":"10.1007/s10878-025-01326-y","DOIUrl":null,"url":null,"abstract":"<p>We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through <i>transfer transactions</i>, which become the key components of the resulting scheduling problem. This <i>Synchronized Resource Production/Job Processing problem</i> (<b>SRPJP</b>) problem typically arises when the resource is a form of renewable energy (e.g., hydrogen, photovoltaic) stored in tanks or batteries. We first cast <b>SRPJP</b> into the Mixed-Integer Linear Programming (MILP) format and handle it through a branch-and-cut process involving specific <i>No</i>_<i>Antichain</i> constraints derived from the structure of the feasible <i>transfer transactions</i>. Subsequently, we explore another approach, which involves eliminating non-binary decision variables and applying a Benders decomposition scheme. Finally, we reformulate the <b>SRPJP</b> problem as a path search problem, which we efficiently handle by designing a tailored adaptation of the A* algorithm.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"111 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synchronizing production planning and job scheduling: MILP models and exact algorithms\",\"authors\":\"Aurélien Mombelli, Alain Quilliot\",\"doi\":\"10.1007/s10878-025-01326-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We address the synchronization of a resource production process with the consumption of related resources by jobs. Both processes interact through <i>transfer transactions</i>, which become the key components of the resulting scheduling problem. This <i>Synchronized Resource Production/Job Processing problem</i> (<b>SRPJP</b>) problem typically arises when the resource is a form of renewable energy (e.g., hydrogen, photovoltaic) stored in tanks or batteries. We first cast <b>SRPJP</b> into the Mixed-Integer Linear Programming (MILP) format and handle it through a branch-and-cut process involving specific <i>No</i>_<i>Antichain</i> constraints derived from the structure of the feasible <i>transfer transactions</i>. Subsequently, we explore another approach, which involves eliminating non-binary decision variables and applying a Benders decomposition scheme. Finally, we reformulate the <b>SRPJP</b> problem as a path search problem, which we efficiently handle by designing a tailored adaptation of the A* algorithm.</p>\",\"PeriodicalId\":50231,\"journal\":{\"name\":\"Journal of Combinatorial Optimization\",\"volume\":\"111 1\",\"pages\":\"\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2025-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Combinatorial Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10878-025-01326-y\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-025-01326-y","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
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 (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.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.