Perbandingan Kombinasi Genetic Algorithm – Simulated Annealing dengan Particle Swarm Optimization pada Permasalahan Tata Letak Fasilitas

Abstract

This article aims to compare the performance of combination of Genetic Algorithm-Simulated Annealing (GA-SA) with Particle Swarm Optimization (PSO) to solve facility layout problem. GA-SA in this article consist of two algorithms, GA-SA I and GA-SA II, with a different mutation rule. PSO uses fuzzy particle swarm concept to represent solution from each particle. Two criteria to analyze all algorithms performance are moment of movement and computational time. Experiments show that GA-SA II has the best performance in minimization both criteria

Keywords

• Genetic Algorithm
• Simulated Annealing
• Particle Swarm Optimization
• fuzzy particle swarm
• facility layout problem