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An evolutionary simulation-based optimization approach for dispatching scheduling

机译:基于进化仿真的调度调度优化方法

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An effective scheduling decision is one of the key factors towards improving the efficiency of a system's performance, particularly in the instance of multiple products thus dispatching rules have been widely used for real-time scheduling because they can provide a very quick and pretty good solution. However, deciding how to select appropriate rules is very difficult. In this paper, we develop evolutionary simulation-based heuristics to construct near-optimal solutions for dispatching rule allocation. Our heuristic is easy to use and gives a manager a useful tool for testing a configuration that can minimize certain performance measures. The optimization heuristics are used to determine priority strategies to maximize the performance of a complex manufacturing system with a large number of different products, along with an overtime that changes with a mix of different process types, including assembly and disassembly operations and with different types of internal and external disturbances. Modeling is carried out using discrete-event simulation. Case study analysis is of a commercial offset printing production system.
机译:有效的调度决策是提高系统性能效率的关键因素之一,特别是在多个产品的情况下,调度规则已被广泛用于实时调度,因为它们可以提供非常快速且非常好的解决方案。但是,决定如何选择适当的规则非常困难。在本文中,我们开发了基于进化仿真的启发式方法,以构造用于调度规则分配的近乎最优的解决方案。我们的启发式方法易于使用,并为经理提供了一个有用的工具,用于测试可最大程度地减少某些性能指标的配置。优化试探法用于确定优先级策略,以最大化具有大量不同产品的复杂制造系统的性能,以及随着不同过程类型(包括组装和拆卸操作)以及不同类型零件的混合而变化的加班时间。内部和外部干扰。使用离散事件模拟进行建模。案例分析是一种商业胶印生产系统。

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