Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem

Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorith...

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Main Authors: Ismail, Ibrahim, Zuwairie, Ibrahim, Zulkifli, Md. Yusof
Format: Conference or Workshop Item
Language:English
English
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/11826/
http://umpir.ump.edu.my/id/eprint/11826/
http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf
http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf
id ump-11826
recordtype eprints
spelling ump-118262018-02-08T00:59:59Z http://umpir.ump.edu.my/id/eprint/11826/ Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem Ismail, Ibrahim Zuwairie, Ibrahim Zulkifli, Md. Yusof TK Electrical engineering. Electronics Nuclear engineering Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. The algorithm able to produce feasible solution in solving traveling salesman problem (TSP), one of the most intensively studied discrete combinatorial optimization problems. To evaluate the performances of the proposed algorithm and the BGSA, several experiments using six sets of selected benchmarks instances of traveling salesman problem (TSP) are conducted. The experimental results showed the newly introduced approach consistently outperformed the BGSA in all TSP benchmark instances used. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf Ismail, Ibrahim and Zuwairie, Ibrahim and Zulkifli, Md. Yusof (2015) Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem. In: 4th International Conference on Software Engineering and Computer Systems, 19-21 August 2015 , Kuantan, Pahang, Malaysia. pp. 142-147.. http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7333099
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Ismail, Ibrahim
Zuwairie, Ibrahim
Zulkifli, Md. Yusof
Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
description Gravitational search algorithm swarm (GSA) is a metaheuristic optimization algorithm, which is based on the Newton's law of gravity and the law of motion, has been successfully applied to solve various optimization problems in real-value search space. Later, binary gravitational search algorithm (BGSA) is designed to solve discrete optimization problems. In this study, rule-based multi-state gravitational search algorithm (RBMSGSA) algorithm is proposed to solve discrete combinatorial optimization problems. The algorithm operates based on a simplified mechanism of transition between two states. The algorithm able to produce feasible solution in solving traveling salesman problem (TSP), one of the most intensively studied discrete combinatorial optimization problems. To evaluate the performances of the proposed algorithm and the BGSA, several experiments using six sets of selected benchmarks instances of traveling salesman problem (TSP) are conducted. The experimental results showed the newly introduced approach consistently outperformed the BGSA in all TSP benchmark instances used.
format Conference or Workshop Item
author Ismail, Ibrahim
Zuwairie, Ibrahim
Zulkifli, Md. Yusof
author_facet Ismail, Ibrahim
Zuwairie, Ibrahim
Zulkifli, Md. Yusof
author_sort Ismail, Ibrahim
title Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
title_short Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
title_full Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
title_fullStr Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
title_full_unstemmed Rule-Based Multi-State Gravitational Search Algorithm for Discrete Optimization Problem
title_sort rule-based multi-state gravitational search algorithm for discrete optimization problem
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11826/
http://umpir.ump.edu.my/id/eprint/11826/
http://umpir.ump.edu.my/id/eprint/11826/1/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf
http://umpir.ump.edu.my/id/eprint/11826/7/Rule-Based%20Multi-State%20Gravitational%20Search%20Algorithm%20for%20Discrete%20Optimization%20Problem.pdf
first_indexed 2023-09-18T22:12:49Z
last_indexed 2023-09-18T22:12:49Z
_version_ 1777415140655759360

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