Paper Info
Title
Binary Accelerated Particle Swarm Algorithm (BAPSA) for discrete optimization problems
Abstract
The majority of Combinatorial Optimization Problems (COPs) are defined in the discrete space. Hence, proposing an efficient algorithm to solve the problems has become an attractive subject in recent years. In this paper, a meta-heuristic algorithm based on Binary Particle Swarm Algorithm (BPSO) and the governing Newtonian motion laws, so-called Binary Accelerated Particle Swarm Algorithm (BAPSA) is offered for discrete search spaces. The method is presented in two global and local topologies and evaluated on the 0---1 Multidimensional Knapsack Problem (MKP) as a famous problem in the class of COPs and NP-hard problems. Besides, the results are compared with BPSO for both global and local topologies as well as Genetic Algorithm (GA). We applied three methods of Penalty Function (PF) technique, Check-and-Drop (CD) and Improved Check-and-Repair Operator (ICRO) algorithms to solve the problem of infeasible solutions in the 0---1 MKP. Experimental results show that the proposed methods have better performance than BPSO and GA especially when ICRO algorithm is applied to convert infeasible solutions to feasible ones.
Year
DOI
Venue
2013
10.1007/s10898-012-0006-1
J. Global Optimization
Keywords
Field
DocType
Combinatorial Optimization Problem,NP-hard problem,Meta-heuristic algorithm,Binary Particle Swarm Optimization,Binary Accelerated Particle Swarm Algorithm,Multidimensional Knapsack Problem
Mathematical optimization,Swarm behaviour,Algorithm,Multi-swarm optimization,Knapsack problem,Optimization problem,Mathematics,Genetic algorithm,Binary number,Penalty method,Discrete space
Journal
Volume
Issue
ISSN
57
2
0925-5001
Citations 
PageRank 
References 
13
0.53
42
Authors
3
Name
Order
Citations
PageRank
Zahra Beheshti11566.79
Siti Mariyam Shamsuddin239841.80
Siti Yuhaniz3505.19