Uncertain Programming Model For Vehicle Scheduling With Integrated Loading And Unloading Of Multiple Distribution Centers

Vehicle scheduling plays an important role in modern logistics distribution systems Therefore,vehicle scheduling problems have been widely concerned and studied in both theoretical and practical fields,such as soft and hard time window vehicle scheduling problems,multi depot vehicle scheduling,and simultaneous unloading and picking up of goods while considering service points However,due to the limitations of information processing technology,many studies are mostly deterministic or stochastic models,which assume that all relevant information is known before arranging vehicle paths Combined with reality,the actual road conditions are relatively complex,and the demand or volume of recycled goods in various places are often variable.The scheduling process is often accompanied by many uncertain factors In recent years,many scholars have introduced uncertainty theory into vehicle scheduling problems,established uncertain planning models for vehicle scheduling problems,and proposed a planning model for gasoline vehicle scheduling in a single distribution center In fact,large enterprises often have more than one distribution center,and in order to reduce empty vehicles,they often arrange vehicles to deliver and pick up goods at the service point simultaneously And with the gradual maturity of electric truck technology,many logistics companies are also trying to use electric trucks for inter city distribution.Aiming at the above problems,this paper studies the vehicle scheduling problem in the uncertain environment.Firstly,this paper introduces the relevant background of the vehicle scheduling problem,and analyzes the relevant research status of the domestic and foreign scholars,the uncertain theory and uncertain planning researches.Secondly,on the basis of studying the relevant theoretical knowledge of uncertain planning and previous research by scholars,this paper considers the uncertainty of the delivery time between distribution points and the demand of each distribution point,minimizes the scheduling cost,and establishes a planning model of vehicle scheduling in multi-distribution centers in the uncertain environment.In addition,the chromosomal genetic algorithm and verification and corresponding numerical examples are given.Then,on the basis of the last model,combined with the situation of simultaneous loading and unloading at the distribution point,an uncertain planning model of vehicle scheduling in multiple distribution centers integrating loading and unloading is established.In order to verify the utility of the model,two example verification are presented in chapter 4.The test results show that the algorithm given in this paper can be applied to the established model,and can give a better path selection scheme.Finally,this paper combines the previous two models and introduces electric trucks for transportation and distribution.By assuming that it allows customers to be served while charging at the distribution point,it puts forward the uncertain planning model of electric vehicle scheduling in multi-distribution centers integrating loading and unloading.And take A company in the Pearl River Delta region as an example,give the scheduling scheme of vehicle distribution.Meanwhile,the experimental results were analyzed by considering the confidence level of the vehicle distribution and the confidence level of the loading capacity.The experimental results show that the model designed in this paper can be well applied to practical problems,give better vehicle path planning,and can provide reference for related enterprises in the actual logistics distribution,so as to select the optimal vehicle scheduling scheme.