基于IPSO的动态多行设施布局优化

Dynamic Multi-row Facility Layout Optimization Based on IPSO

摘要

针对制造车间设施布局研究中存在的动态性处理不足、优化效果不稳定的问题，提出一种面向动态多行布局问题的优化模型与算法框架。通过正态分布扰动构建模糊随机物流量，真实反映生产系统中物料需求的不确定性。在此基础上，建立考虑物料搬运成本、设施重排成本及占地面积成本的多周期混合整数规划模型。算法部分提出一种改进的粒子群优化方法，在传统粒子群算法 (PSO) 基础上引入混沌搜索初始化粒子群，增强搜索多样性；动态调整惯性权重与学习因子，实现全局搜索与局部搜索的平衡；同时结合基于布局结构特性的改进邻域更新机制，提高收敛精度。仿真实验结果表明，改进粒子群算法在多组算例中均表现更优的稳定性和收敛性能，平均迭代次数减少约 30%。实例验证所提模型和算法在实际动态布局场景中的可行性与有效性，与静态方案相比，总成本降低了约 10.8%。研究结果表明，该方法在动态多行设施布局优化中，与现有元启发式算法相比有更高的全局搜索能力和求解效率，为制造车间的动态布局提供了有效的优化途径。

Abstract

To address the inadequate consideration of dynamic factors and unstable optimization results in manufacturing facility layout, this study develops an optimization model and algorithmic framework for dynamic multi-row facility layout problems. Fuzzy-stochastic material flows are generated by introducing normally distributed perturbations to capture the uncertainty of material demand. Based on this, a multi-period mixed-integer programming model is formulated considering material handling cost, facility relocation cost, and space utilization cost. An improved particle swarm optimization (PSO) algorithm is proposed, where chaos-based initialization is introduced to enhance search diversity. In addition, inertia weight and learning factors are dynamically adjusted to balance global exploration and local exploitation, while an improved neighborhood update mechanism based on layout structure is developed to improve convergence accuracy. Simulation results show that the improved PSO achieves higher stability and faster convergence, reducing the average number of iterations by about 30%. A case study confirms the feasibility and effectiveness of the proposed model and algorithm, reducing total cost by approximately 10.8% compared with static layouts. The proposed method demonstrates better global search capability and computational efficiency than existing metaheuristic algorithms, providing an effective approach for dynamic facility layout optimization in manufacturing systems.

关键词

动态多行布局 / 模糊随机物流 / 混合整数规划 / 改进粒子群算法

Key words

dynamic multi-row layout / fuzzy-stochastic material flows / mixed-integer programming / improved particle swarm optimization

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基金资助

安徽省高校自然科学研究重点项目(2022AH050324)

安徽省普通高校重点实验室开放基金项目(CS2023-04)

安徽省工业互联网智能应用与安全工程研究中心开放基金项目(IASII24-07)