关键词: 车辆路径问题, 取送货问题, 模糊需求, 启发式算法

Abstract: To solve the problem of inventory imbalance in the chain enterprises, this paper studies the multi-commodity vehicle routing problem with split pickupand delivery and fuzzy demand (MCVRPSPDFD). The question considers factors such as mixed loading of multiple goods, multiple visits, unmatched supply and demand, non-unique demand, and uncertain demand. This paper constructs the MCVRPSPDFD mathematical model which aims at minimizing operating costs. The model uses credibility measurement theory to deal with uncertain factors in the decision-making environment and solves it through an improved genetic tabu algorithm. To adapt to model requirements and improve computing efficiency, the algorithm designs special initial population, encoding and decoding methods and selects appropriate parameters through parameter testing. The results of the calculation example show that the paper can effectively solve the problem of chain enterprises’ inventory imbalance. The change in the preference value of decision-makers will have an impact on operating costs.

Key words: vehicle routing problem, pickupanddelivery, fuzzydemand, heuristic algorithm