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首页> 外文期刊>International Journal of Internet Manufacturing and Services >Multi-objective flexible job shop scheduling using hybrid differential evolution algorithm
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Multi-objective flexible job shop scheduling using hybrid differential evolution algorithm

机译:混合差分进化算法的多目标柔性作业车间调度

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The authors addressed multi objective flexible job shop scheduling problems using hybrid differential evolution algorithm for minimisation of makespan, total machine load and critical machine load. The differential evolution algorithm is a stochastic-based adaptive scheme used for global optimisation over continuous space and to apply it for flexible job shop scheduling problem a suitable encoding mechanism is required. In this work random keys encoding mechanism is used to generate schedules that deals with floating point vectors. A non-dominated sorting algorithm is used to find the set of non-dominated solutions for the given scheduling problem. The proposed approach is extensively tested on a set of standard flexible job shop scheduling instances reported in the literature and it is found that the proposed algorithm is performing well on all the test problems.
机译:作者使用混合差分进化算法解决了多目标柔性作业车间调度问题,以最小化制造期,总机器负载和关键机器负载。差分进化算法是一种基于随机的自适应方案,用于在连续空间上进行全局优化,并将其应用于灵活的作业车间调度问题,需要一种合适的编码机制。在这项工作中,随机密钥编码机制用于生成处理浮点向量的计划。使用非支配的排序算法来查找给定调度问题的非支配解集。该方法在文献报道的一组标准柔性作业车间调度实例上进行了广泛的测试,发现该算法在所有测试问题上均表现良好。

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