Abstract: In the cellar flow shop with limited capacity material handling system,aiming at the joint optimization problem of Pick-up/Drop-off(P/D)points location layout of manufacturing cells and Automated Guided Vehicle(AGV)quantity allocation,a joint optimization model of P/D point layout and AGV allocation was established by taking the minimized average total transportation cost and AGV allocation cost as the multi-objective.Due to the different characteristics between P/D point layout and AGV allocation,to improve the efficiency of the algorithm and the quality of results,a Particle swarm optimization Mesh Adaptive Direct search algorithm(PMADS)with embedded Conjugate Optimization Method(COM)and Particle Swarm Optimization(PSO)was proposed.In the optimization process,the new P/D point layout and the corresponding AGV allocation were re-optimized respectively.A precision manufacturing plant planning case was studied and the results showed that PMADS algorithm was superior to other comparison algorithms in performance and quality,and effectively solved the joint optimization problem of P/D point layout and AGV allocation.The results verified the effectiveness,efficiency and practical value of the proposed algorithm in solving the proposed problem,and the COM strengthened the direction of the algorithm and improved the efficiency and the quality.

Key words: pick-up/drop-off points layout, automated guided vehicle allocation, finite capacity material handling system, particle swarm optimization mesh adaptive direct search, conjugate optimization method

摘要： 在具有有限能力物料储运系统的单元流水式车间中,针对单元上料与下料(P/D)口位置布局与物料搬运AGV数量配置的联合优化问题,建立了以最小化平均运输总成本和AGV配置成本为目标的单元P/D口布局与AGV配置联合优化模型。由于P/D口布局与AGV配置具有不同的优化特点,为了提高算法效率和结果的质量,提出一种嵌入共轭优化法和粒子群优化的网格自适应直接搜索算法(PMADS),在优化过程中分别对新解的P/D口布局及对应的AGV配置进行再优化。将所提算法与其他对比算法应用于某精密制造企业新工厂规划项目,结果显示PMADS算法在性能和求解质量上均优于其他算法,有效解决了单元流水式车间单元P/D口布局与AGV配置的联合优化问题。结果验证了所提算法在求解车间单元P/D口布局与AGV配置问题上的有效性、高效性及实用价值,所提共轭优化法加强了算法搜索的方向性,提高了算法效率和解的质量。

关键词: 上下料口布局, AGV配置, 有限能力物料储运系统, 粒子群网格自适应直接搜索, 共轭优化法