基于ACNS-MADS的上下料口布局与配置联合优化

    Joint Optimization for Layout and Allocation of Pick-up/Drop-off Points Using ACNS-MADS

    • 摘要: 针对单元流水式车间内单元上料与下料口 (P/D口) 的位置布局和容量配置的联合优化问题,以最小化总运输成本 (包括拥堵成本) 和最小化配置成本为目标,建立含有产出率和生产周期约束的优化模型。针对相邻工序P/D口之间的容量平衡以及P/D口位置与容量协同优化的问题特征,提出一种嵌入自适应协同邻域搜索算法的网格自适应直接搜索算法 (ACNS-MADS),其中,ACNS算法用于再优化新解的P/D口位置布局与容量配置方案。实验结果表明,与其他对比算法相比,ACNS-MADS算法获得的总运输成本和P/D口配置成本分别减少2.99%和5.64%,算法时间减少17.95%以上。这验证了所提算法求解P/D口布局与配置联合优化问题是有效且高效的,具有实用价值。

       

      Abstract: Aiming at the joint optimization problem of location layout and capacity allocation of pick-up/drop-off points (P/D point) in cellar flow shops, an optimization model with throughput rates and cycle time constraints is established with the objective of minimizing the total transportation cost (including congestion cost) and allocation cost. According to the capacity balance between P/D points of adjacent processes and the problem characteristics of joint optimization of P/D point locations and capacities, a mesh adaptive direct search algorithm embedded with adaptive cooperative neighborhood search algorithm (ACNS-MADS) is proposed, in which the ACNS is used to reoptimize the P/D point location layout and capacity allocation scheme of a new solution. Experimental results show that compared with other algorithms, the total transportation cost and the P/D point allocation cost obtained by ACNS-MADS are reduced by 2.99% and 5.64% respectively, with a computation time reduction of over 17.95%. It can conclude that the proposed algorithm is effective and efficient to solve the joint optimization problem of P/D point layout and allocation, having practical value.

       

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