SOLVE THE CAPACITANCE VEHICLE ROUTING PROBLEM (CVRP) USING THE TABU SEARCH ALGORITHM (TS) AND THE PARTICLE SWARM OPTIMIZATION WITH PRACTICAL APPLICATION

In this paper we examine the vehicle routing problem (VRP) which is classified as a problem (NP-HARD). This problem addresses the design of tracks for a group of vehicles that equip a number of customers deployed in different locations. The objective of this problem is to reduce the total cost of delivery, taking into account the limitations of the problem, and also to design the optimal distribution of the tracks within the specified vehicle capacity limits. The study includes the most important methods used to solve the problem, the use of the tabu search algorithm (TS) and particle swarm optimization(pso) and the hybridization of a new algorithm that adopts the characteristics of tabu search with particle swarm optimization ( TS-PSO) in solving problem Issues. The performance and efficiency of the algorithms are compared by solving known issues of the problem. The results show that the tabu search algorithm (TS) is efficient in finding solutions to the problem. The ability to reach the mean deviation about (1.764) from the standard solutions for the set of standard issues. However, the TS-PSO is able to produce results that overcame the results of the tabu search algorithm as well as the particle swarm algorithm, although the hybrid algorithm requires double and large computational times compared to the two individually designed algorithms. The method of the problem has been applied in the General Company for the manufacture of grain distribution process from one of the mills to a group of agents deployed geographically The method was able to reach to draw and design the best possible paths for vehicles available at the least distance cut and the lowest number of vehicles.