将人工蜂群元启发式与Dhouib-Matrix-TSP1启发式相结合求解钻孔问题

IF 4 Q2 ENGINEERING, INDUSTRIAL Journal of Industrial and Production Engineering Pub Date : 2022-12-22 DOI:10.1080/21681015.2022.2158499
S. Dhouib, A. Zouari, Saima Dhouib, H. Chabchoub
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引用次数: 5

摘要

摘要本文提出了一种创新的混合优化方法,该方法基于人工蜂群元启发式和Dhouib-Matrix-TSP1启发式的集成,以克服刀具路径最小化问题。所提出的方法首先包括通过使用几个描述性统计度量实现Dhouib-Matrix-TSP1来提供不同的可行解决方案。然后,这些解决方案将成为人工蜂群初始种群的一部分,人工蜂群将执行该种群以生成最优解决方案。为了验证和比较所提出的方法,模拟了几个多孔制造的实验实例。所使用的数据集由四个矩形布局和两个圆形布局组成,布局从25个孔到2600个孔。结果表明,该方法优于标准元启发式算法,改进率在0.24%-9.35%之间。所获得的改进同时涉及最小路径长度、平均路径长度和路径长度的SD。图形摘要
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Integrating the artificial bee colony metaheuristic with Dhouib-Matrix-TSP1 heuristic for holes drilling problems
ABSTRACT In this article, an innovative hybrid optimization method is proposed based on the integration of the Artificial Bee Colony metaheuristic and the Dhouib-Matrix-TSP1 heuristic to overcome the tool path minimization problem. The proposed methodology consists firstly of providing different feasible solutions by implementing Dhouib-Matrix-TSP1 with several descriptive statistical metrics. Then, these solutions will become a part of the initial population of the Artificial Bee Colony that will perform this population in order to generate the optimal solution. To validate and compare the proposed method, several experimental instances of multi-hole making are simulated. The used dataset consists of four rectangular layouts and two circular layouts with an arrangement from 25 to 2600 holes. Results show that the proposed method outperforms the standard metaheuristics with an improvement rate between 0.24% and 9.35%. The obtained improvements concern simultaneously the minimal path length, the mean path length, and the SD of path lengths. Graphical Abstract
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
21
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