AN APPROACH FOR VEHICLE ROUTING PROBLEM USING GRASSHOPPER OPTIMIZATION ALGORITHM AND SIMULATED ANNEALING

This paper is focused on the study of basic problem vehicle for reducing cost factor and increasing efficiency solution. Features constraint uses some capabilities algorithm used to modify it dynamically between nodes depot. demonstrated with a feasible schedule every node minimizes total as much possible. The analysis based address given model solution procedure.The purpose this research provide examples models applications which include profits, extensions partitioned features. objective minimize traveled distance that visits subset one after another while maximizing or satisfying minimum collected profit from each visited node. concepts VRP are discussed in Section I issues VI. VI also contains modeling aspects constraints can be solving paper. Simulated annealing grasshopper optimization combined routing VII. investigates both variants clustering different methods generation routes overcome optimal In conventional algorithm, shortest path certain starts center depot calculated by means local search algorithms. Few such ant colony genetic considered route optimization. We compare performance these solve VRP. Therefore, proposed method able produce better solutions than other reveal large number benchmark experimental results very promising.