Reverse Logistics Network Problem using Priority-based Genetic Algorithm
نویسندگان
چکیده
Today, interest about the recovery of used products and materials is on increasing. Therefore, reverse logistics will become power and great potential for winning consumers in more competitive contexts in the future. This paper considers the multistage reverse Logistics Network Problem (mrLNP) with minimizing the total of costs to reverse logistics shipping cost. We will demonstrate the mrLNP model will be formulated as a three-stage logistics network model. For solving this problem, we propose a Genetic Algorithm (priGA) with priority-based encoding method consisting of two stages, and combine a new crossover operator called Weight Mapping Crossover (WMX). Also a heuristic approach is applied in the 3rd stage to transportation of materials from processing center to manufacturer. Computer simulations show the several numerical examples by using priGA and pnGA (Prüfer number based GA), and effectiveness of the proposed method.
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