Bilinear branch and check for unspecified parallel machine scheduling with shift consideration

IF 6 2区 管理学 Q1 OPERATIONS RESEARCH & MANAGEMENT SCIENCE European Journal of Operational Research Pub Date : 2024-08-13 DOI:10.1016/j.ejor.2024.08.011
Ponpot Jartnillaphand, Elham Mardaneh, Hoa T. Bui
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Abstract

This paper tackles the complex challenge of team formations, assignments, and job schedules within the static Unspecified Parallel Machine Flexible Resource Scheduling problem, specifically incorporating shift considerations. In existing literature, teams are often simplified as machines that operate continuously throughout the day without any interruptions. However, in reality, teams require breaks between shifts and cannot work continuously within a day. Therefore, we introduce shift considerations to ensure that teams do not work in consecutive shifts. We consider flexible workers, capable of performing any job, who are distributed among different teams in different shifts to undertake various jobs. The number of teams in each shift is a decision variable. The duration of each job is determined by the number of workers in a team assigned to it. The objective function is to minimize the makespan, representing the overall schedule completion time, while adhering to precedence constraints. We formulate an integer linear programming model for the proposed problem and develop a novel bilinear branch and check algorithm that introduces valid bilinear inequalities to accelerate convergence. The numerical results confirm that our algorithm’s performance optimally solves problems up to 35 jobs within a reasonable timeframe, surpassing the efficiency of the branch and cut method of IBM CPLEX and the classical branch and check algorithm.

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考虑移位因素的非指定并行机调度的双线性分支和校验
本文探讨了静态非指定并行机器灵活资源调度问题中团队组建、任务分配和作业计划的复杂挑战,特别是纳入了轮班考虑因素。在现有文献中,团队通常被简化为全天不间断运行的机器。但在现实中,团队需要轮班休息,不可能在一天内连续工作。因此,我们引入了轮班考虑因素,以确保团队不会连续轮班工作。我们考虑的是能够从事任何工作的灵活工人,他们被分配到不同班次的不同团队中,承担各种工作。每个班次的团队数量是一个决策变量。每项工作的持续时间由分配到该工作的团队人数决定。目标函数是在遵守优先级约束的前提下,最大限度地减少代表整体计划完成时间的工期。我们为提出的问题制定了一个整数线性规划模型,并开发了一种新颖的双线性分支和校验算法,该算法引入了有效的双线性不等式以加速收敛。数值结果证实,我们的算法能在合理的时间范围内优化解决多达 35 个作业的问题,其效率超过了 IBM CPLEX 的分支和切割法以及经典的分支和检查算法。
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来源期刊
European Journal of Operational Research
European Journal of Operational Research 管理科学-运筹学与管理科学
CiteScore
11.90
自引率
9.40%
发文量
786
审稿时长
8.2 months
期刊介绍: The European Journal of Operational Research (EJOR) publishes high quality, original papers that contribute to the methodology of operational research (OR) and to the practice of decision making.
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