改善式BVEDA求解多目标调度问题

发布时间：2018-06-23 16:44

  本文选题：多目标优化 + 置换流水车间调度　； 参考：《山东大学学报(工学版)》2017年04期

【摘要】：针对以最小化最大完工时间、最小化最大拖期和最小化总流程时间为目标的置换流水车间调度问题(permutation flow shop scheduling problem,PFSP),基于双变量分布估计法(bi-variable estimation of distribution algorithm,BVEDA)提出改善式双变量分布估计算法(Improved BVEDA,IBVEDA)进行求解。利用BVEDA中双变量概率模型进行区块构建,根据组合概率公式进行区块竞争和区块挖掘,借用高质量的区块组合人造解,提高演化过程中解的质量;针对算法多样性较差的特点,设计在组合人造解的过程中加入派工规则最短处理时间、最长处理时间和最早交货期,将上述方法并行演化,通过top10的权重适度值总和动态调整上述方法处理的解的数量,最后利用帕累托支配筛选和保存非支配解。试验使用C++代码在Taillard标准算例上测试,IBVEDA与SPGAⅡ和BVEDA比较,并绘制解的分布图证实算法的有效性。
[Abstract]:To minimize the maximum completion time, In order to minimize the maximum tardiness and minimize the total flow time, the improved BVEDA-IBVEDA (improved BVEDA-IBVEDA) algorithm is proposed to solve the (permutation flow shop scheduling problem in the permutation flow shop scheduling problem, which is based on the bi-variable estimation of distribution algorithm (BVEDA). The improved BVEDA-IBVEDA (improved BVEDA-IBVEDA) algorithm is proposed to solve the problem. Using the bivariate probabilistic model of BVEDA to construct blocks, according to the combination probability formula, the block competition and block mining are carried out, and the high-quality artificial solution of block combination is used to improve the quality of the solution in the evolution process. The shortest processing time, the longest processing time and the earliest delivery time are added in the process of combining artificial solutions. The above methods are evolved in parallel, and the number of solutions processed by the above method is dynamically adjusted by the sum of the appropriate weight values of top10. Finally, Pareto domination is used to screen and preserve the non-dominant solutions. The C code is used to test the comparison of IBVEDA with SPGA 鈪，

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