Location-Routing Optimization of Cold Chain Distribution Center Based on Hybrid Genetic Algorithm - Tabu search

摘要

Since location and route problems are of equal importance to the cold chain logistics, it is necessary to consider the location and route optimization comprehensively for the benefit of the overall system. In this paper, an optimal location-routing model considered temperature variation among sensitive products for cold chain distribution centers is designed, with the objective function to minimize the overall expenses. As a solution method, a hybrid genetic algorithm-tabu search is proposed, which is applied to location-routing optimization utilizing an efficient integer index encoding and its appropriate parameters. The algorithm verified by an illustrative example with certain scale data reveals to be feasible and effective, which finally identifies and prioritizes potential alternatives for continuous improvement.