Dynamic Adaptation of Genetic Algorithm for Solving Routing Problems on Large Scale Systems

Q3 Engineering

Advances in Systems Science and Applications Pub Date : 2020-06-30 DOI:10.25728/ASSA.2020.20.2.821

V. Zakharov, Alexander Mugaiskikh

引用次数: 1

Abstract

This paper is devoted to the implementation of the dynamic adaptation procedure for the genetic algorithm used for solving large-scale travelling salesman problem. This procedure serves to obtain more profitable solutions by a fixed operating time. In order to evaluate effectiveness of new approach computational experiments were performed on well-known problem instances from TSPLib library. As a result, generated solutions reduce the length of the routing plans in considered problem instances compare to classical genetic heuristics. By that, we show how to use the property of time inconsistency of heuristics to get better solutions. New criteria for estimating the efficiency of heuristics algorithms called experimental level of time consistency is introduced.

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遗传算法求解大规模系统路由问题的动态适应

本文致力于实现用于求解大规模旅行商问题的遗传算法的动态自适应过程。该程序用于在固定的操作时间内获得更有利可图的解决方案。为了评估新方法的有效性，对TSPLib库中的已知问题实例进行了计算实验。因此，与经典的遗传启发式算法相比，在所考虑的问题实例中，生成的解决方案减少了路由计划的长度。由此，我们展示了如何利用启发式算法的时间不一致性来获得更好的解。引入了一种新的启发式算法效率估计标准，称为时间一致性实验水平。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Advances in Systems Science and Applications Engineering-Engineering (all)

CiteScore

1.20

自引率

0.00%

发文量

期刊介绍： Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.