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A multi-objective mathematical model and genetic algorithm for reliability analysis in flexible job-shop scheduling problem

机译:柔性作业车间调度问题可靠性分析的多目标数学模型和遗传算法

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摘要

Problems involving a single objective function are not as realistic as the ones, which involve multi-objective functions. This paper presents a new two objectives mathematical model for flexible job-shop scheduling problem in which the reliability index of machines as an important fact has been taken into consideration. The objectives are defined as: minimising total completion time of jobs and maximising the reliability of system (minimising failure rate of machines). Since these objectives are conflict and complexity of the model is high, a non-dominated sorting genetic algorithm (NSGAII) is designed to find Pareto optimal solution for this problem. The Pareto optimal solutions resulted from this paper is used by decision maker for selecting the solution that satisfies her/his needs in different industrial environments.
机译:涉及单个目标函数的问题并不像涉及多个目标函数的问题那样现实。本文提出了一种针对柔性作业车间调度问题的新的两目标数学模型,该模型考虑了机器的可靠性指标这一重要事实。这些目标的定义是:最大限度地减少工作的总完成时间,并使系统的可靠性最大化(使机器的故障率最小化)。由于这些目标是冲突的,并且模型的复杂性很高,因此设计了一种非支配排序遗传算法(NSGAII)来找到针对该问题的Pareto最优解。决策者使用本文得出的帕累托最优解决方案来选择可满足其在不同工业环境中需求的解决方案。

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