A modified Particle Swarm Optimization Algorithm to solve Time Minimization Transportation Problem
Gurwinder Singh1, Amarinder Singh2
1Gurwinder Singh*, Research Scholar, IKG Punjab Technical University, Jalandhar, Punjab, India.
2Amarinder Singh, Assistant Professor, Department of Applied Sciences, BBSB Engineering College, Fatehgarh Sahib, Punjab, India.
Manuscript received on January 05, 2020. | Revised Manuscript received on January 25, 2020. | Manuscript published on January 30, 2020. | PP: 3696-3692 | Volume-8 Issue-5, January 2020. | Retrieval Number: E6606018520/2020©BEIESP | DOI: 10.35940/ijrte.E6606.018520
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: 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.
Keywords: Transportation Problem, Time Minimization Transportation Problem, Particle Swarm Optimization, Optimal Solution.
Scope of the Article: Waveform Optimization for Wireless Power Transfer.