Genetic Algorithm Optimization In The Logistics Vehicle Scheduling Research And Applications

With the development of market economy and logistics technology, logistics business developed rapidly. In logistics business, the vehicle scheduling problem affects mostly on raising service quality, reducing logistics cost and increasing economic benefits of logistics enterprises, which is the essential thing in the optimization of logistics system and essential content in electronic commerce. That is to say the system research of logistics distribution vehicle optimal scheduling is the development of logistics intensified, construction of the synthesis logistics system, the establishment of modern scheduling control system, the development of intelligence transportation system's foundation. In daily life and production, many problems such as mail delivery problems, bus scheduling problems, electricity dispatching problems, pipeline laying problems and computer network designing problems can all be seen as logistics distribution vehicle scheduling problems. Taking logistics distribution vehicle scheduling problem as its studying object, this paper has both theoretical and practical value.The logistics distribution vehicle scheduling problem is a restraint combination optimization question belongs to the NP problem (Nondeterministic Polynomial Problem). Along with the question input scale expansion, the solution time assumes the geometric series rise. In this article, I discuss with the genetic algorithm of the intelligence algorithm to solves the vehicles scheduling problem.Firstly, this article analyzes the outline of the logistics distribution vehicle scheduling optimization question, as well as the foundation of this question proposed, which has carried on the description, the mathematical model analysis as well as the corresponding solution algorithm analysis to the question commonly used two used two kinds of VSP, then in the foundation of detailed introduction of genetic algorithm, using MATLAB7.0 simulation software to have inherited the simulation of the genetic algorithm and the comparative analysis, confirmed the feasibility of the genetic algorithm to solve the question of the distribution way optimization, in the fourth chapter, I analyzed the travel sales problem of the genetic algorithm of the non-full load vehicles optimization scheduling, the common vehicles optimization scheduling problem as well as the time window of vehicles optimization on scheduling problem separately to carry on the heredity the genetic algorithm design, as well as test simulation analysis, in the fifth chapter, I had considered under the situation of the daily scheduling work of logistics distribution was very big and the carrier vehicle was very great, the situation that purely used the artificial method in the scheduled time continuously to determine the daily furthest scheme of distribution vehicle whole scheduling is impossible, proposed to establish the logistics distribution vehicle scheduling system optimization, it need to computer realization of the logistics distribution vehicle scheduling algorithm on optimization, and discussed its correlation data processing and the realization process of algorithm in this chapter...