This research employs the meta-heuristic method of discrete particle swarm optimization (DPSO) to an application of traveling routing problems (TRP). The optimization procedure simulates the decision-making processes of swarm. And it is similar to other adaptive learning and artificial intelligence techniques such as ant colony optimization, simulated annealing and genetic algorithms. The objective is minimizing the total routing path and time of a trip. Experimentation results show that the algorithm is successful in finding solutions while applying discrete particle swarm. And the continues variable particle swarm optimization (CPSO) also be implement in this paper, the simulation results also show CPSO is a better method in solving combination problems.
The 2010 International Conference on Innovation and Management, Penang, Malaysia, July 7- 10, 2010.