Research on Vehicle Routing Problem with Time Windows Based on Minimal Cost for Electronic Commerce
Currently, logistics Companies of Electronic Commerce face with modern market of multiple batches, small volume, high time requirement and individuation demand. The optimization model of vehicle scheduling based on traditional shortest vehicle route is difficult to satisfy the factual requirement of logistics distribution under electronic commerce. Since it excessively emphasizes the principle of shortest route, there has a risk of good delivery delay which may cause high distribution cost or losing competition ability. Considering the characteristics of logistics distribution under electronic commerce, the traditional vehicle scheduling model is modified in order to reduce the distribution cost, and the objective function is also modified based on minimum expense. Furthermore, in order to improve the distribution service quality and market competition, maximum work time, more vehicle types, vehicle load capacity restrictions, maximum running distance and others are added in restraint conditions which will also improve the applicability and universal characteristics of model. Because vehicle scheduling problem is NP puzzle, the optimization solution is obtained by improved genetic algorithm: using customer natural number when encoding the chromosomes to simplify the problem and improve the searching efficiency of genetic algorithm; using individual amount control selection game in order to guarantee colony diversity; using partially matched crossover to improve convergent speed of algorithm so as to better solve the inconsistency between diversity and convergent speed; using 2-exchange mutation strategy to strengthen the partial searching ability of chromosome and improve the convergent speed of algorithm. Finally, the good performance of the improved algorithm can be proved by experimental results and concrete examples.