基于混合蚁群算法的生产系统设施规划问题研究

设施规划问题主要研究生产设备的布局规划，从而减小厂区内的物料搬运成本。一个有效的设施规划有利于生产过程中整体运作效率的提高。随着市场竞争的日趋激烈，市场环境处于不断的变化之中，制造企业需不断对设施布局进行重新规划来适应不断变化的市场环境对产品需求量的影响，并达到降低成本的目的。这一问题便需要用多阶段设施规划（MFLP）的方法来解决。本文提出了一种改进的混和蚁群算法（HACO）来解决带有财务预算约束的多阶段设施规划问题，并将此方法与其他一些典型的启发式算法进行了对比分析。结果表明，本文提出的HACO算法是求解带有财务预算约束的MFLP问题的一种有效的方法。

A Research for Multi-stage Facility Layout Problem of Production System Based on Hybrid Ant Colony Optimization Algorithm

Facility layout problem mainly studies the layouts of manufacturing facilities, which aims at reducing the material handling costs in the plant. An effective facility layout method can contribute to improve the overall operation efficiencies during the process of manufacturing. With the increasingly fierce competition in the market, the market environment is constantly changing. Manufacturing enterprises must continuously redesign the facility layout so as to adapt the changing production demands and reduce the cost. This problem requires the solution of Dynamic facility layout problem (DFLP). In this paper, an improved hybrid ant colony optimization (HACO) is proposed to solve the DFLP with budget constraints. The HACO algorithm proposed by this paper can show good performance both for small and for large scale facility layout problems. There exists great gap between HACO and the other algorithms on solving large scale facility layout problems. Therefore, HACO is an effective method to solve dynamic facility layout problem with budget constraints.