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An improved genetic algorithm for solving flexible job shop scheduling problem

机译：一种改进的求解柔性作业商店调度问题的遗传算法

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The Flexible Job Shop Scheduling Problem (FJSP) is a very important problem in the modern manufacturing system. It is an extension of the classical job shop scheduling problem. It allows an operation to be processed by any machine from a given set. It is also a NP-hard problem. Since FJSP requires an additional decision of machine allocation during scheduling, therefore it is much more complex problem than JSP. This paper proposed an improved genetic algorithm (IGA) to solve FJSP. We tested the IGA against the GA method. Simulation results demonstrate that it can be superior to the regular GA. We also tested the IGA with the exhaustion method to show the algorithm's efficiency.
机译：灵活的作业商店调度问题（FJSP）是现代制造系统中的一个非常重要的问题。它是古典作业商店调度问题的延伸。它允许由来自给定集的任何机器处理的操作。它也是一个难题的问题。由于FJSP在调度期间需要额外的机器分配决定，因此它比JSP更复杂。本文提出了一种改进的遗传算法（IGA）来解决FJSP。我们对GA方法测试了IGA。仿真结果表明它可以优于常规GA。我们还通过耗尽方法测试了IGA以显示算法的效率。

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