A Multi-state Gravitational Search Algorithm for Combinatorial Optimization Problems

The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA)...

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Vydáno v:2015 7th International Conference on Computational Intelligence, Communication Systems and Networks s. 9 - 14
Hlavní autoři: Ibrahim, Ismail, Ibrahim, Zuwairie, Ahmad, Hamzah, Yusof, Zulkifli Md
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: IEEE 01.06.2015
Témata:
Algorithm design and analysis
Approximation algorithms
Benchmark testing
Cities and towns
discrete combinatorial optimization problem
Force
gravitational search algorithm
Heuristic algorithms
multi-state
Optimization
rule-based
travelling salesman problem
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Abstract The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism of transition between two states. The performance of the MSGSA is empirically compared to the original BGSA based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The experimental results show the effectiveness of the newly introduced approach, regarding its ability to consistently outperform the binary-based algorithm in solving the discrete optimization problems.
AbstractList The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements of the binary-based algorithms have been reported. In this paper, a variant of GSA called multi-state gravitational search algorithm (MSGSA) for discrete optimization problems is proposed. The MSGSA concept is based on a simplified mechanism of transition between two states. The performance of the MSGSA is empirically compared to the original BGSA based on six sets of selected benchmarks instances of traveling salesman problem (TSP). The experimental results show the effectiveness of the newly introduced approach, regarding its ability to consistently outperform the binary-based algorithm in solving the discrete optimization problems.
Author Ibrahim, Ismail
Ahmad, Hamzah
Ibrahim, Zuwairie
Yusof, Zulkifli Md
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  givenname: Zuwairie
  surname: Ibrahim
  fullname: Ibrahim, Zuwairie
  email: zuwairie@ump.edu.my
  organization: Univ. Malaysia Pahang, Pekan, Malaysia
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  givenname: Hamzah
  surname: Ahmad
  fullname: Ahmad, Hamzah
  email: hamzah@ump.edu.my
  organization: Univ. Malaysia Pahang, Pekan, Malaysia
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  givenname: Zulkifli Md
  surname: Yusof
  fullname: Yusof, Zulkifli Md
  email: zmdyusof@ump.edu.my
  organization: Univ. Malaysia Pahang, Pekan, Malaysia
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Snippet The binary-based algorithms including the binary gravitational search algorithm (BGSA) were designed to solve discrete optimization problems. Many improvements...
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SubjectTerms Algorithm design and analysis
Approximation algorithms
Benchmark testing
Cities and towns
discrete combinatorial optimization problem
Force
gravitational search algorithm
Heuristic algorithms
multi-state
Optimization
rule-based
travelling salesman problem
Title A Multi-state Gravitational Search Algorithm for Combinatorial Optimization Problems
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