具有不相等和作业相关的早迟到成本最小化的混合遗传算法

IF 1.3 Q3 ENGINEERING, MULTIDISCIPLINARY
Prasad Bari, Prasad Karande, Vaidehi Bag
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引用次数: 0

摘要

针对单机调度问题,提出了两种组合遗传算法:不等早发延迟遗传算法(UET-GA)和作业依赖早发延迟遗传算法(JDET-GA),以最小化早发延迟成本。将基本UET和JDET中产生的工作序列作为染色体添加到遗传算法的随机种群中。每个epoch的最佳序列也作为种群成员注入到下一个epoch。提出的改进寻求在更短的时间内实现收敛,以寻找最优解。尽管遗传算法已经在许多不同类型的优化问题上得到了非常成功的实现,但据了解,该算法具有搜索能力困难,使得计算np困难的优化问题类型,如基于排列的优化问题。使用普通的随机总体初始化会导致这个缺陷。为了加强随机种群初始化,利用所提出的增强来获得收敛性并找到一个有希望的解。使用JDET-GA将到期日作为决策变量,可以进一步显著降低成本。在知名的单机基准示例上运行了多个测试,以证明所提出方法的有效性,并将结果与基本的UET和JDET方法进行了比较,在降低成本方面取得了显着的进步。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hybrid genetic algorithm to minimize scheduling cost with unequal and job dependent earliness tardiness cost
This article presents two combinatorial genetic algorithms (GA), unequal earliness tardiness-GA (UET-GA) and job-dependent earliness tardiness-GA (JDET-GA) for the single-machine scheduling problem to minimize earliness tardiness (ET) cost. The sequence of jobs produced in basic UET and JDET as a chromosome is added to the random population of GA. The best sequence from each epoch is also injected as a population member in the subsequent epoch. The proposed improvement seeks to achieve convergence in less time to search for an optimal solution. Although the GA has been implemented very successfully on many different types of optimization problems, it has been learnt that the algorithm has a search ability difficulty that makes computations NP-hard for types of optimization problems, such as permutation-based optimization problems. The use of a plain random population initialization results in this flaw. To reinforce the random population initialization, the proposed enhancement is utilized to obtain convergence and find a promising solution. The cost is further significantly lowered offering the due date as a decision variable with JDET-GA. Multiple tests were run on well-known single-machine benchmark examples to demonstrate the efficacy of the proposed methodology, and the results are displayed by comparing them with the fundamental UET and JDET approaches with a notable improvement in cost reduction.
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来源期刊
CiteScore
2.10
自引率
13.30%
发文量
18
审稿时长
20 weeks
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