A New Representation and Operators for Genetic Algorithms Applied to Grouping Problems

Author:

Falkenauer Emanuel1

Affiliation:

1. CRIF - Research Centre for Belgian Metalworking Industry Industrial Automation Division CP 106 - P4 50, av. F. D. Roosevelt B-1050 Brussels Belgium

Abstract

An important class of computational problems are grouping problems, where the aim is to group together members of a set (i.e., find a good partition of the set). We show why both the standard and the ordering GAs fare poorly in this domain by pointing out their inherent difficulty to capture the regularities of the functional landscape of the grouping problems. We then propose a new encoding scheme and genetic operators adapted to these problems, yielding the Grouping Genetic Algorithm (GGA). We give an experimental comparison of the GGA with the other GAs applied to grouping problems, and we illustrate the approach with two more examples of important grouping problems successfully treated with the GGA: the problems of Bin Packing and Economies of Scale.

Publisher

MIT Press - Journals

Subject

Computational Mathematics

Reference18 articles.

1. Bhuyan, J. N., Raghavan, V. V. & Elayavalli, V. K. (1991). Genetic algorithm for clustering with an ordered representation. In R. K. Belew & L. B. Booker (Eds.), Proceedings of the Fourth International Conference on Genetic Algorithms (pp. 408-41 5). San Mateo, CA: Morgan Kaufmann.

2. Ding, H., El-Keib, A. A. & Smith, R. E. (1992). Optimal clustering of power nemorks using genetic algorithms (TCGA Report No. 92001). Tuscaloosa, AL: University of Alabama.

3. Falkenauer, E. (1991a). A genetic algorithm for grouping. In R. GutiCrrez & M. J. Valderrama (Eds.), Proceedings of the Fifth International Symposium on Applied Stochastic Models and Data Analysis (pp. 198-206). Granada, Spain: World Scientific.

4. Falkenauer, E. & Delchambre, A. (1992). A genetic algorithm for bin packing and line balancing. In Proceedings of the IEEE 1992 International Conference on Robotics and Automation (ipA92) (pp. 11 86-1192). Los Alamitos, CA: IEE Computer Society Press.

5. Falkenauer, E. (1994). Setting new limits in bin packing with a grouping G A using reduction (Technical Report R0108). Brussels, Belgium: CRIF Industrial Automation.

Cited by 140 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Metaheuristics for variable-size mixed optimization problems: A unified taxonomy and survey;Swarm and Evolutionary Computation;2024-08

2. Meta-Heuristics Algorithm for Computer Communications;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2024-06-30

3. Genetic Clustering Algorithm Based on the Division and Combination of Layer Series of Development;International Journal of Pattern Recognition and Artificial Intelligence;2024-06-29

4. A GA-Based Scheduling Algorithm for Semiconductor-Product Thermal Cycling Tests;Lecture Notes in Electrical Engineering;2024

5. Metaheuristics for (Variable-Size) Mixed Optimization Problems: A Unified Taxonomy and Survey;2024

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3