同步生产计划和作业调度:MILP模型和精确算法

IF 1.1 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Aurélien Mombelli, Alain Quilliot
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引用次数: 0

摘要

我们解决了资源生产过程与作业消耗相关资源的同步问题。两个进程通过传输事务进行交互,传输事务成为调度问题的关键组成部分。这种同步资源生产/作业处理问题(SRPJP)通常出现在资源是储存在储罐或电池中的一种可再生能源(例如氢、光伏)时。我们首先将SRPJP转换为混合整数线性规划(MILP)格式,并通过涉及从可行转移事务结构中导出的特定No_Antichain约束的分支切断过程来处理它。随后,我们探索了另一种方法,该方法涉及消除非二进制决策变量并应用Benders分解方案。最后,我们将SRPJP问题重新表述为路径搜索问题,并通过设计定制的a *算法来有效地处理该问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
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.
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