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:
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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
collection ePrints
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.
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institution Universiti Teknologi Malaysia - ePrints
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publishDate 2012
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spelling utm.eprints-343762017-09-10T07:43:45Z http://eprints.utm.my/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.
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.
title 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_short 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
topic TK Electrical engineering. Electronics Nuclear engineering
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