Fusing Binary Particle Swarm Optimzation with Simulated Annealing for Knapsack Problems

作者: Mana Anantathanavit , Mud-Armeen Munlin

DOI: 10.1109/ICIEA.2014.6931496

关键词:

摘要: The Knapsack Problems (KPs) is a well-known combinatorial optimization problem. It has variety of practical applications. We propose the algorithm to solve both 0–1 problem (KP) and Multidimensional Problem (MKP) by fusing Binary Particle Swarm Optimization (BPSO) Simulated Annealing (SA) with maximum profit objective. main contribution develop novel approach hybridizing BPSO at local optimum simulated annealing help escape from reach global optimum. results indicate that fusion outperforms individual implementation binary particle swarm annealing.

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