Simultaneous Pickup And Delivery Location-Routing Network Optimization With Grey Demand

Location routing problem has extensive practical basis and application value,and has been one of the focus of academic research in decades.In reality,the customer often has two-way demand for picking and delivery.Considering that the simultaneous pickup and delivery strategy is beneficial to reduce the logistics cost and improve the customer service level,the location routing problem with simultaneous pickup and delivery(LRPSPD)has been paid attention.At present,the research of LRPSPD is mainly based on deterministic environment but less for uncertain environment.But in the actual situation,the customer's both pickup and delivery demand have uncertainty,performed as ambiguity,randomness or grey.Therefore,it's of great value to study LRPSPD with grey demand in both theoretical and practical.The main work of this paper is as follows:(1)Processing optimization problem feature.Considering the customer's two-way grey demand.The grey number is used to describe grey uncertainty,and simultaneous pickup and delivery strategy is used to meet customer's two-way demand.(2)Establishing grey optimization model.Considering the LRPSPD with grey demand,①in order to reduce the logistics cost,meeting the customer's pickup and delivery demand at the same time,and taking minimizing cost as the goal,then establishing the single-objective optimization model;② In order to balance the customer service level,on the basis of the Model I,taking the customer satisfaction function based on the time window into account,and taking both minimizing the cost and maximizing customer satisfaction as the goal,then establishing the multi-objective optimization model.(3)Solving grey optimization model.For the fact that the model which contains grey parameters can not be solved directly,firstly,transforming the model into a grey chance constrained model which can be solved directly.Secondly,for solving the single objective optimization model after transforming,a single-objective tabu search algorithm based on grey simulation is designed,in this algorithm,the grey simulation is used to deal with the grey chance constraints.And for solving the multi objective optimization model after transforming,a multi-objective tabu search algorithm embedded grey relational analysis algorithm is designed,in this algorithm,the grey correlation analysis is used to guide the search direction of the algorithm.(4)Simulating on grey optimization model.The experimental results show that:for the model,① it is necessary and reasonable to consider the grey uncertainty of customer demand,which can help the enterprise to avoid the change cost caused by ignoring the uncertainty of customer demand.② Confidence level has impact on the location routing decision,the higher confidence level,the higher cost.Therefore,the enterprise can set the confidence level depending on its own risk tolerance ability,and obtaining optimal solution under the corresponding confidence level;③There is a contradiction between the logistics cost and customer satisfaction.Enterprise can make finally decisions combine with its own strategic objectives and the reference solution given by grey correlation evaluation method.For the algorithm,① the algorithm proposed in this paper can effectively solve the LRPSPD with grey demand.② Compared with the common multi-objective algorithm,the multi-objective algorithm embedded with grey correlation analysis can get a better Pareto frontier.