一维装箱问题的混合遗传方法

Q3 Business, Management and Accounting
R. Potarusov, H. Allaoui, G. Goncalves, V. Kureychik
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引用次数: 2

摘要

本文研究一维装箱问题(1-D BPP)。精确解方法只能用于非常小的实例,因此对于现实世界的问题,我们必须关注启发式方法。近年来,研究人员开始应用进化方法来解决这个问题,包括遗传算法和进化规划。本文提出一种求解一维BPP问题的混合遗传算法(HGA)。我们将我们的方法与Scholl等人、Alvim等人和Kok-Hua等人给出的算法进行了比较。然后讨论了该方法的性能。我们表明,在质量解决方案方面,我们的HGA方法在计算时间方面优于这些算法,至少具有相同的性能。这种性能是由于遗传算法和局部搜索混合的新机制。
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 approach for 1-D bin packing problem
This paper deals with the one-dimensional Bin Packing Problem (1-D BPP). Exact solution methods can only be used for very small instances, hence for real-world problems we have to focus on heuristic methods. In recent years, researchers have started to apply evolutionary approaches to this problem, including Genetic Algorithms and Evolutionary Programming. In this paper, we propose a Hybrid Genetic Algorithm (HGA) to solve 1-D BPP. We compare our approach with algorithms given by Scholl et al., Alvim et al. and Kok-Hua et al. Then we discuss the performance of the approach. We show that giving at least the same performance on term of quality solution, our HGA approach outperforms these algorithms on term of computational time. This performance is due to new mechanisms of hybridisation of genetic algorithms and local search.
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来源期刊
International Journal of Services Operations and Informatics
International Journal of Services Operations and Informatics Business, Management and Accounting-Management Information Systems
CiteScore
1.60
自引率
0.00%
发文量
9
期刊介绍: The advances in distributed computing and networks make it possible to link people, heterogeneous service providers and physically isolated services efficiently and cost-effectively. As the economic dynamics and the complexity of service operations continue to increase, it becomes a critical challenge to leverage information technology in achieving world-class quality and productivity in the production and delivery of physical goods and services. The IJSOI, a fully refereed journal, provides the primary forum for both academic and industry researchers and practitioners to propose and foster discussion on state-of-the-art research and development in the areas of service operations and the role of informatics towards improving their efficiency and competitiveness.
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