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Efficiency of Representation Schemes in Genetic Algorithms for Job-Shop Scheduling Problem

机译：作业商店调度问题遗传算法中的代表方案效率

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摘要

Genetic algorithms (Gas) have been applied to constrained optimization problems like job-shop scheduling with success. For these problems, the encoding of the solution (schedule) is a critical issue. Many representation schemes require the use a decoder to ensure the feasibility of the solution or use a repair scheme to make the solution feasible. With some of these current representations, the mapping from the solution space to encoding space is not unique (1:N), I.e., many chromosomes can be mapped to the same schedule. In this paper, we study the mechanics of chromosome-schedule mapping in the job-shop scheduling domain. When the initial population is generated, the set of unique schedules is identified and stored. As new chromosomes are created by genetic operators, the corresponding solutions are inspected for uniqueness. The number of unique solutions produced after each generation is maintained. A computational analysis is then performed to correlate the uniqueness of the population to the exploration of search space. The results of the study provide understanding how redundancy in representation scheme affects the exploration and convergence of the algorithm and provides a basis for choosing and designing effective representation schemes and genetic operators for the job shop scheduling domain.
机译：遗传算法（气体）已被应用于有限的优化问题，如成功的工作店调度。对于这些问题，解决方案（计划）的编码是一个关键问题。许多表示方案要求使用解码器确保解决方案的可行性或使用修理方案来使解决方案可行。利用这些当前的一些表示中的一些，从解决方案空间到编码空间的映射不是唯一的（1：n），即，许多染色体可以映射到相同的时间表。在本文中，我们研究了作业商店调度域中的染色体调度映射的力学。当生成初始群体时，识别并存储该组唯一计划。随着遗传算子创建的新染色体，对相应的解决方案进行了唯一性。维持各一代后产生的独特解决方案的数量。然后执行计算分析以将人口的唯一性与搜索空间的探索相关联。该研究的结果提供了了解表示方案中的冗余如何影响算法的探索和收敛性，并为作业商店调度域选择和设计有效表示方案和遗传运算符提供基础。

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