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针对作业车间调度问题JSP(Job-shop scheduling problem),提出一种入侵式杂草优化算法。该算法中,子代以正态分布方式在父代个体周围扩散,兼顾全局搜索和局部搜索,并根据迭代次数不同对二者强度进行调节。通过典型算例进行仿真试验,并在反复实验中对算法参数进行修正。测试结果表明杂草算法求解作业车间调度问题的可行性和有效性,优于萤火虫算法和基本粒子群算法,是解决生产调度问题的一种有效方法。
In order to solve Job-shop scheduling problem (JSP), an intrusion weed optimization algorithm is proposed. In this algorithm, the offspring spreads around the parent individuals in a normal distribution, taking into account the global search and local search, and adjusts the intensity of the two according to different iterations. Through a typical example simulation test, and in repeated experiments to amend the algorithm parameters. The test results show that the weed algorithm is more effective and feasible than the firefly algorithm and the basic particle swarm optimization algorithm to solve the job shop scheduling problem. It is an effective method to solve the production scheduling problem.