Fuzzy Demand Vehicle Routing Problem with Soft Time Windows

Tao Yang, Weixin Wang and Qiqi Wu
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Tao Yang: College of Extended Education, Chongqing University of Education, Chongqing 400067, China
Weixin Wang: School of International Business and Management, Sichuan International Studies University, Chongqing 400031, China
Qiqi Wu: College of Finance and Economics, Sichuan International Studies University, Chongqing 400031, China

Sustainability, 2022, vol. 14, issue 9, 1-14

Abstract: Considering the vehicle routing problem with fuzzy demand and fuzzy time windows, a vehicle routing optimization method is proposed considering both soft time windows and uncertain customer demand. First, a fuzzy chance-constrained programming model is established based on credibility theory, minimizing the total logistics cost. At the same time, a random simulation algorithm is designed to calculate the penalty cost of delivery failures caused by demand that cannot be satisfied. In order to overcome the shortcomings of GA, which easily falls into the local optimum in the process of searching, and the slow convergence speed of SA when the population is too large, a hybrid simulated annealing–genetic algorithm is adopted to improve the solution quality and efficiency. Finally, the Solomon standard example is used to verify the effectiveness of the algorithm, and the influence of decision-makers’ subjective cost preference is analyzed.

Keywords: vehicle routing problem; fuzzy demand; simulated annealing algorithm; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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