The problem of dynamic relocation and phase-out of combined manufacturingplant and warehousing facilities in the supply chain are concerned. A multiple time/multipleobjective model is proposed to maximize total profit...The problem of dynamic relocation and phase-out of combined manufacturingplant and warehousing facilities in the supply chain are concerned. A multiple time/multipleobjective model is proposed to maximize total profit during the time horizon, minimize total accesstime from the plant/warehouse facilities to its suppliers and customers and maximize aggregatedlocal incentives during the time horizon. The relocation problem keeps the feature of NP-hard andwith the traditional method the optimal result cannot be got easily. So a compact genetic algorithm(CGA) is introduced to solve the problem. In order to accelerate the convergence speed of the CGA,the least square approach is introduced and a fast compact genetic algorithm (fCGA) is proposed.Finally, simulation results with the fCGA are compared with the CGA and classical integerprogramming (IP). The results show that the fCGA proposed is of high efficiency for Paretooptimality problem.展开更多
基金This project is supported by National Natural Science Foundation of China (No.59889505, 70071017).
文摘The problem of dynamic relocation and phase-out of combined manufacturingplant and warehousing facilities in the supply chain are concerned. A multiple time/multipleobjective model is proposed to maximize total profit during the time horizon, minimize total accesstime from the plant/warehouse facilities to its suppliers and customers and maximize aggregatedlocal incentives during the time horizon. The relocation problem keeps the feature of NP-hard andwith the traditional method the optimal result cannot be got easily. So a compact genetic algorithm(CGA) is introduced to solve the problem. In order to accelerate the convergence speed of the CGA,the least square approach is introduced and a fast compact genetic algorithm (fCGA) is proposed.Finally, simulation results with the fCGA are compared with the CGA and classical integerprogramming (IP). The results show that the fCGA proposed is of high efficiency for Paretooptimality problem.
