基于GI/G/m的逆向物流优化

Ding Si-Bo, Huang Wei-lai
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引用次数: 3

摘要

在过去的几年里,公众对环境问题的认识大大提高了。由于报废产品的处理引起了人们的极大关注,未来随着回收率的提高和服务范围的扩大,逆向物流系统规划将变得至关重要。本研究结合GI/G/m排队模型和自适应遗传算法对恢复设施容量、基础设施设计和逆向网络流进行优化。所提出的模型试图使总成本最小化,总成本包括收集成本、运输成本、设施固定成本、变动成本、处置成本,以及回收材料的销售收入和销售双手产品的收入。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reverse Logistics Optimization Based on GI/G/m
Over the past few years, public awareness of environmental aspects has dramatically increased. Since the disposition of end-of-life products has caused tremendous attention, Reverse logistics system planning shall become vital as the take-back rate increases and the service area expands in the future. This study combines GI/G/m queuing model and adaptive genetic algorithm to optimize the capacity of the recovery facilities, the infrastructure design and the reverse network flow. The proposed model attempts to minimize the total cost, which consists of collection cost, transportation cost, fixed cost for facilities, variable cost, disposal cost, as well as the sale revenue of reclaimed materials and revenue of selling two-hands products.
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