Abstract
The successful implementation of remanufacturing supply chain not only needs foundation engineering technology, but also needs the efficient supply chain model to support logistics network. But till now, the optimization problems of supply chain logistics network focus on the determination for the number and location of facilities and logistics distribution between the various facilities. Except for the decisive factors, the optimization problem of remanufacturing supply chain logistics network considers the environmental pollution factors the waste product returns and transportation. The market demand and waste product returns are actually uncertain in remanufacturing supply chain. There is few papers focus on dual uncertain factors although there are lots of studies on the problems. Therefore, based on dual stochastic programming, the optimization model of multi-phase multi-objective remanufacturing supply chain is established with maximum profit in the remanufacturing supply chain, maximum rapid response customer satisfaction and minimum environmental pollution. Dual-layer genetic algorithm mechanism was brought up. The first layer algorithm is responsible for supply chain logistics network structure. The second layer algorithm determines specific distributions for remanufacturing supply chain, based on optimized logistics network structure mechanism in the first layer algorithm. Finally, numerical examples demonstrate the validity of the model and algorithm for the optimization problem.
Published Version
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