Research On Vehicle Routing Problem Optimization In Models And Algorithms In Simultaneous Pickup And Delivery And Collaborations

In recent years,the supply chains that form the core of various enterprises have linked suppliers,plants,distributors,retailers,and users into a cohesive unit by means of controlling information flow,logistics,and capital flow.Many enterprises have paid increasing attention to the vehicle routing problem for logistic distribution,which is considered to be a fundamental part of a supply chain.Through the analysis of the actual transportation problem,the enterprise establishes the mathematical model of vehicle routing problem on the basis of certain hypothesis strips.Through the analysis and solution of the model,a scientific and reasonable transportation plan can be obtained,which will help the enterprise to reduce the transportation cost,improve the transportation efficiency,and thus achieve greater economic benefits.However,the complexity,diversity of logistics distribution and the variability of customer demand have brought many difficulties to vehicle routing optimization.Firstly,as an important extension of the vehicle routing problem,the vehicle routing problem with simultaneous pickup and delivery rarely considers the routing failure problem which often occurs in the transportation process and does not propose a reasonable strategy to solve this problem.Secondly,the existing collaborative vehicle routing optimization research mainly focuses on supply-side or demand-side unilateral logistics collaborations,but ignore the collaborations between supply-sides and between demand-sides,as may make the potentially more cost-reduced transportation solutions be neglected.Thirdly,as a typical NP-hard problem,how to explore an efficient algorithm is also a difficult problem.The existing algorithms for solving vehicle routing problem are not mature,and their performance needs to be further improved.According to the above analysis,two different vehicle routing optimization models(i.e.,simultaneous pickup and delivery and collaboration)are constructed for two different customer demands(i.e.,simultaneous pickup and delivery and only delivery and no pickup)in this study,and two different heuristic algorithms are proposed to solve the two models respectively in order to reduce the total transportation cost of the optimal transportation scheme.The main contributions of this study are concluded as follows:1.We propose a new vehicle routing model based on dynamic multi-stage failurespecific cooperative(DMS-FSC)recourse strategy.The proposed DMS-FSC strategy allows a pair of cooperative vehicles to revisit each other's customers with unmet demands by dividing the whole transportation route into multiple stages,so as to solve the route failure which occurs in the vehicle routing problem with simultaneous pickup and delivery.On this basis,an improved Genetic Algorithm(GA)with a new multi-stage paired vectors representation scheme is offered to more effectively deal with the proposed DMS-FSC strategy.It explores a more ideal a priori transportation plan by incorporating an acceptance criterion based on simulated annealing.Finally,the experimental results confirm that the proposed algorithm's effectiveness in solving the presented problem and evaluate the cost savings generated from the proposed DMS-FSC strategy.2.We propose a new vehicle routing model based on the collaborations between supply-sides and between demand-sides.The proposed model extends supply-side unilateral logistics collaborations to simultaneously consider collaborations between supply-and demand-sides Further,the proposed model uses a composite objective that is a weighted sum of four objectives — including quality,reliability,cost,and time — to accurately evaluate and analyze the efficiency improvement.On this basis,an extended Variable Neighborhood Search(VNS)algorithm is presented based on three matrices,including the supplier collaboration matrix,customer collaboration matrix,and transportation sequence matrix.This algorithm aims to address the trade-offs among multiple objectives by incorporating new operators based on specific features involved in the problem.Finally,the experimental results confirm that the proposed algorithm's effectiveness in solving the presented problem and evaluate the cost savings generated from the proposed model.In summary,the research on vehicle routing problem with simultaneous pickup and delivery and collaborative vehicle routing problem is of great theoretical and practical significance to the optimization of transportation cost in logistics industry.