Abstract
This study addresses a biobjective vehicle routing problem with stochastic demand and split deliveries. Apart from minimizing the total travel cost that is widely considered in classical vehicle routing problems, we aim to balance the workload of all routes. A recourse policy for paired vehicles that allows the distribution service to fail once and meet part of the demand of customers first is provided. To solve the proposed biobjective vehicle routing problem, an adaptive large neighborhood search embedded with an improved optimization method is developed. The objective value is calculated based on the normalized values of two goals using the improved weighted sum approach. To evaluate the proposed optimization model and corresponding algorithm, some experiments modified from Solomon’s instances are conducted. Computational results show that the performance of the proposed heuristic approach is effective.
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