Performance Analysis of Opposition Based Particle Swarm Optimization with Cauchy Distribution in Minimizing Makespan Time in Job Shop Scheduling
Anil Kumar K. R.1, Edwin Raja Dhas2
1Anil Kumar K. R.*, Research Scholar, Noorul Islam Centre for Higher Educarion, Kanyakumari, India.
2Dr. Edwin Raja Dhas, Department of Automobile Engineering, Noorul Islam Centre for Higher Educarion, Kanyakumari, India.
Manuscript received on February 12, 2020. | Revised Manuscript received on February 21, 2020. | Manuscript published on March 30, 2020. | PP: 360-366 | Volume-8 Issue-6, March 2020. | Retrieval Number: D8524118419/2020©BEIESP | DOI: 10.35940/ijrte.D8524.038620
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Abstract: In the contemporary circumstances, manual solving of job shop scheduling problem (JSSP) is quite time consuming and inaccurate. The main intention of this paper is to analyze the performance of various optimization techniques in JSSP in order to minimize makespan time. This paper aims to analyze four optimization techniques viz, particle swarm optimization (PSO), genetic algorithm (GA), opposition based genetic algorithm(OGA) and opposition based particle swarm optimization with Cauchy distribution (OPSO CD) in addition to the existing optimization techniques applied in various research papers on combinatorial optimization problems viz., JSSP. A comparative study of these optimization techniques were conducted and analyzed to find out the most effective optimization technique on solving JSSP. Results show that OPSO CD is found to possess minimum makespan time in comparison with other algorithms for JSSP.
Keywords: Job Shop Scheduling, Opposition Based Particle Swarm Optimization With Cauchy Distribution, Makespan Time, Combinatorial Optimization
Scope of the Article: Simulation Optimization and Risk Management