基于混合灰狼算法的设施布局优化

doi:10.3778/j.issn.1002-8331.2403-0064

摘要/Abstract

摘要： 研究了一类复杂的设施布局优化问题，综合考虑各功能区出入口位置、布局方向和安全距离阈值等因素，构建了以最小化物流强度为目标的混合整数规划模型。提出了混合灰狼算法（hybrid grey wolf optimizer，HGWO）以获取优质的布局方案。结合问题特征构建了编码与解码方法，旨在适配当前问题和灰狼算法（grey wolf optimizer，GWO），并辅以个体评估函数以协助种群进化。通过Fuch混沌映射构建初始种群，力求生成高质量的初始种群。在种群进化方面，构建以优质解牵引和邻居学习为特征的混合进化机制，着力平衡算法自身的全局搜索和局部挖掘能力。开展了函数优化、压力容器设计问题和设施布局优化实例的仿真实验，结果分析验证了HGWO算法的良好性能。

关键词: 灰狼算法（GWO）, 设施布局, 混沌映射, 混合进化机制

Abstract: This paper investigates a complicated facility layout optimization problem with considerations of the factors such as entry/exit locations, the facility orientation and the safety distance. The problem domain is stated and the mathematical model is developed to minimize the total logistics intension. Then, a hybrid grey wolf optimizer (HGWO) is proposed for solution generation. By virtue of the problem nature, a novel encoding and decoding method is designed to adjust grey wolf optimizer (GWO) to the considered problem. Meanwhile, an evaluation function is proposed to assist the population evolution. To improve the solution performance at initialization stage, the Fuch chaotic mapping is used to create initial solutions. In addition, a hybrid solution update mechanism is defined by combining the optimal solution guidance and neighborhood learning strategies to balance the global search and local mining capabilities. Finally, experiments are carried out to address numerical optimization problems, such as the pressure vessel problem and the facility layout optimization instances. The simulation results validate the performance of the proposed HGWO.

Key words: grey wolf optimizer(GWO), facility layout, chaotic mapping, hybrid solution update mechanism

宋强. 基于混合灰狼算法的设施布局优化[J]. 计算机工程与应用, 2025, 61(11): 351-363.

SONG Qiang. Facility Layout Optimization Using Hybrid Grey Wolf Optimizer[J]. Computer Engineering and Applications, 2025, 61(11): 351-363.

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