Application of the Improved Ant Colony Algorithm to VRP
The Vehicle Routing Problem (VRP) is one of the chief problems in logistics transportation management. As a kind of new simulated evolutionary algorithm, ant colony algorithm (ACA) is fit for searching the best route of combinatorial optimization problems such as VRP. The algorithm has several shortages including long searching time, slow convergence rate and limiting to local optimal solution easily. In order to overcome these shortcomings and improve its performance, the improved ant colony algorithm was established, which integrates the ant algorithm with the genetic algorithm, in each iteration of the ant colony algorithm, the initial values of the components of the solution are selected by the pheromone trial at first, then the exact solution is determined by the operations of mutation. With the establishment of the performance index, the results derived from the genetic algorithm and the improved ACA were compared and analyzed in the experiment. Base on the comparison of the expenditure of the time and transportation, the effectiveness of the improved ant colony algorithm was proved. This algorithm has reference to the general resource scheduling and extended value to other fields.
The Vehicle Routing Problem Ant Colony Algorithm Genetic Algorithm
Zhi-xia ZHANG Xin HU Ying WANG
School of Mana.,Xian Univ.of Arch.& Tech.,China School of Civil Eng.,Xian Univ.of Arch.& Tech.,China
国际会议
北京
英文
2007-05-30（万方平台首次上网日期，不代表论文的发表时间）