A modified Particle Swarm Optimization Algorithm to solve Time Minimization Transportation Problem

When the supply of items need urgent/earliest delivery to the destinations, the Time Minimization Transportation Problems (TMTPs) are indispensable. Traditionally these problems have been solved using the exact techniques, however, the (meta) heuristic techniques have provided a great breakthrough in search space exploration. Particle Swarm Optimization is one such meta-heuristic technique that has been applied on a wide variety of continuous optimization problems. For discrete problems, either the mathematical model of problem or the solution procedure has been changed. In this paper, the PSO has been modified to incorporate the discrete nature of variables and the non-linearity of the objective function. The proposed PSO is tested on the problems available in the literature and the optimal solutions are obtained efficiently. The exhaustive search capability of proposed PSO is established by obtaining alternate optimal solutions and the combinations of the allocated cells that are beyond ( ) m n 1 in number. This proposed solution technique, therefore, provides an effective alternate to the analytical techniques for decision making in the logistic systems.