Cataclysm genetic algorithm for solving vechicle scheduling problem with time windows

This paper proposed a new cataclysm genetic algorithm for the VSP with time window constraints,and then adopted genetic algorithm( GA),an efficient heuristic algorithm,to solve this kind of combinatorial optimization problem. However,GA had the drawbacks of premature convergence and easy to fall into local optimum. To solve this problem,it adopted cataclysm operator in the searching process to guarantee the GA jump out of local optimum. To avoid the infeasible offspring in the cross process of the chromosome,it designed a crossover operator which could generate the feasible solution directly focused on this VSP. In the end,according to the computational simulation,it verified the effectiveness of the proposed algorithm in solving the VSP with time windows. Through the comparison of the results obtained with the benchmark GA,the modified GA and the particle swam optimization( PSO),verifying that the catastrophe genetic algorithm is robust and can obtain superior optimization performance.