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...

Full description

Bibliographic Details
Main Authors:	Ismail, Ibrahim, Zulkifli, Md. Yusof, Sophan Wahyudi, Nawawi, Muhammad Arif, Abdul Rahim, Kamal, Khalil, Hamzah, Ahmad, Zuwairie, Ibrahim
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2012
Subjects:	TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/26946/ http://umpir.ump.edu.my/id/eprint/26946/ http://umpir.ump.edu.my/id/eprint/26946/1/A%20novel%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20combinatorial%20optimization%20problems.pdf

id	ump-26946
recordtype	eprints
spelling	ump-269462020-03-20T02:27:13Z http://umpir.ump.edu.my/id/eprint/26946/ A novel multi-state particle swarm optimization for discrete combinatorial optimization problems Ismail, Ibrahim Zulkifli, Md. Yusof Sophan Wahyudi, Nawawi Muhammad Arif, Abdul Rahim Kamal, Khalil Hamzah, Ahmad Zuwairie, 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. IEEE 2012 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/26946/1/A%20novel%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20combinatorial%20optimization%20problems.pdf Ismail, Ibrahim and Zulkifli, Md. Yusof and Sophan Wahyudi, Nawawi and Muhammad Arif, Abdul Rahim and Kamal, Khalil and Hamzah, Ahmad and Zuwairie, Ibrahim (2012) A novel multi-state particle swarm optimization for discrete combinatorial optimization problems. In: IEEE 4th International Conference on Computational Intelligence, Modelling and Simulation (CIMSim 2012), 25-27 September 2012 , Kuantan, Pahang Darul Makmur. pp. 18-23.. ISBN 978-1-4673-3113-5 https://doi.org/10.1109/CIMSim.2012.46
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	TK Electrical engineering. Electronics Nuclear engineering Ismail, Ibrahim Zulkifli, Md. Yusof Sophan Wahyudi, Nawawi Muhammad Arif, Abdul Rahim Kamal, Khalil Hamzah, Ahmad Zuwairie, 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	Ismail, Ibrahim Zulkifli, Md. Yusof Sophan Wahyudi, Nawawi Muhammad Arif, Abdul Rahim Kamal, Khalil Hamzah, Ahmad Zuwairie, Ibrahim
author_facet	Ismail, Ibrahim Zulkifli, Md. Yusof Sophan Wahyudi, Nawawi Muhammad Arif, Abdul Rahim Kamal, Khalil Hamzah, Ahmad Zuwairie, Ibrahim
author_sort	Ismail, Ibrahim
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
publisher	IEEE
publishDate	2012
url	http://umpir.ump.edu.my/id/eprint/26946/ http://umpir.ump.edu.my/id/eprint/26946/ http://umpir.ump.edu.my/id/eprint/26946/1/A%20novel%20multi-state%20particle%20swarm%20optimization%20for%20discrete%20combinatorial%20optimization%20problems.pdf
first_indexed	2023-09-18T22:42:16Z
last_indexed	2023-09-18T22:42:16Z
_version_	1777416994048442368

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

Similar Items