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In this paper, a cold chain vehicle routing problem with fuzzy time windows (CVRPFTW) is proposed and solved. This paper applies fuzzy membership functions to characterize the customer’s satisfaction level issues associated with time window violation in a vehicle routing problem and proposes CVRPFTW. CVRPFTW is formulated as a bi-objective model with two goals: (1) to minimize the total distribution cost and (2) to maximize the overall customer’s satisfaction level. To solve this bi-objective model, a two-stage algorithm is developed. Using the two-stage algorithm, CVRPFTW is decomposed into two subproblems, namely a traditional vehicle routing problem with time windows for cold chain and a service improvement problem, and each of the objectives is sequentially solved. Then, aiming at the characteristics of the model and the practical problems in this paper, a genetic algorithm which is more suitable for this model is designed, which is called the improved genetic algorithm. Finally, experiments based on a real fresh food company are conducted, and the results show that the CVRPFTW model can achieve considerable cost-savings, while at the same time maintaining an acceptable customer’s satisfaction level. Keywords—cold chain logistics; Vehicle routing problem (VRP); fuzzy time windows; genetic algorithm

Vehicle Routing Problem for perishable food in Cold Chain with Fuzzy Time Windows