Performance Evaluation of PSO, PSOCA and MPSOCA for Solving University Timetabling Problem
Journal Title: Annals. Computer Science Series - Year 2018, Vol 16, Issue 2
Abstract
In this paper, performance evaluation of Particle Swarm Optimization algorithm (PSO), Particle Swarm Optimization based Cultural Algorithm (PSOCA) and Modified Particle Swarm Optimization based Cultural Algorithm (MPSOCA) was carried out using simulation time, fitness value and number of unallocated courses as performance metrics. The evaluation results of PSO, PSOCA and MPSOCA yielded average simulation times of 35.29, 37.68 and 17.42 seconds, respectively. Also, fitness values of 85, 89 and 90% were recorded for PSO, PSOCA and MPSOCA, respectively. PSO have a total average number of 60 subjects unallocated compare to PSOCA and MPSOCA that successfully allocated all the subjects.
Authors and Affiliations
Oluwaseun M. ALADE, Christopher A. OYELEYE, Oluyinka T. ADEDEJI, Elijah Olusayo Omidiora, Stephen Olatunde Olabiyisi
Keywords
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Performance Evaluation of PSO, PSOCA and MPSOCA for Solving University Timetabling Problem
In this paper, performance evaluation of Particle Swarm Optimization algorithm (PSO), Particle Swarm Optimization based Cultural Algorithm (PSOCA) and Modified Particle Swarm Optimization based Cultural Algorithm (MPSOCA...