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A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.

Particle swarm optimization (PSO) has been widely used to solve real-valued optimization problems. A variant of PSO, namely, binary particle swarm optimization (BinPSO) has been previously developed to solve discrete optimization problems. Later, many studies have been done to improve BinPSO in term...

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Main Authors: Zulkifli, Md. Yusof, I., Ibrahim, S. W., Nawawi, M. A. A., Rahim, K., Khalil, H., Ahmad, Z., Ibrahim
Format: Conference or Workshop Item
Published: 2012
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utm.my/id/eprint/34376/
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spelling my.utm.343762017-09-10T07:43:45Z http://eprints.utm.my/id/eprint/34376/ A novel multi-state particle swarm optimization for discrete combinatorial optimization problems. Zulkifli, Md. Yusof I., Ibrahim S. W., Nawawi M. A. A., Rahim K., Khalil H., Ahmad Z., Ibrahim TK Electrical engineering. Electronics Nuclear engineering Particle swarm optimization (PSO) has been widely used to solve real-valued optimization problems. A variant of PSO, namely, binary particle swarm optimization (BinPSO) has been previously developed to solve discrete optimization problems. Later, many studies have been done to improve BinPSO in term of convergence speed, stagnation in local optimum, and complexity. In this paper, a novel multi-state particle swarm optimization (MSPSO) is proposed to solve discrete optimization problems. Instead of evolving a high dimensional bit vector as in BinPSO, the proposed MSPSO mechanism evolves states of variables involved. The MSPSO algorithm has been applied to two benchmark instances of traveling salesman problem (TSP). The experimental results show that the the proposed MSPSO algorithm consistently outperforms the BinPSO in solving the discrete combinatorial optimization problem. 2012 Conference or Workshop Item PeerReviewed Zulkifli, Md. Yusof and I., Ibrahim and S. W., Nawawi and M. A. A., Rahim and K., Khalil and H., Ahmad and Z., Ibrahim (2012) A novel multi-state particle swarm optimization for discrete combinatorial optimization problems. In: 2012 Fourth International Conference on Computational Intelligence, Modelling and Simulation.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zulkifli, Md. Yusof
I., Ibrahim
S. W., Nawawi
M. A. A., Rahim
K., Khalil
H., Ahmad
Z., Ibrahim
A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
description Particle swarm optimization (PSO) has been widely used to solve real-valued optimization problems. A variant of PSO, namely, binary particle swarm optimization (BinPSO) has been previously developed to solve discrete optimization problems. Later, many studies have been done to improve BinPSO in term of convergence speed, stagnation in local optimum, and complexity. In this paper, a novel multi-state particle swarm optimization (MSPSO) is proposed to solve discrete optimization problems. Instead of evolving a high dimensional bit vector as in BinPSO, the proposed MSPSO mechanism evolves states of variables involved. The MSPSO algorithm has been applied to two benchmark instances of traveling salesman problem (TSP). The experimental results show that the the proposed MSPSO algorithm consistently outperforms the BinPSO in solving the discrete combinatorial optimization problem.
format Conference or Workshop Item
author Zulkifli, Md. Yusof
I., Ibrahim
S. W., Nawawi
M. A. A., Rahim
K., Khalil
H., Ahmad
Z., Ibrahim
author_facet Zulkifli, Md. Yusof
I., Ibrahim
S. W., Nawawi
M. A. A., Rahim
K., Khalil
H., Ahmad
Z., Ibrahim
author_sort Zulkifli, Md. Yusof
title A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
title_short A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
title_full A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
title_fullStr A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
title_full_unstemmed A novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
title_sort novel multi-state particle swarm optimization for discrete combinatorial optimization problems.
publishDate 2012
url http://eprints.utm.my/id/eprint/34376/
_version_ 1643649569962065920
score 13.2014675

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