Solving Maximal Covering Problem using Partitioned Intelligent Fish Algorithm

Amin Jula, Elankovan A Sundararajan, Narjes Khatoon Naseri, Reza Abiat

Research output: Contribution to journalArticle

Abstract

NP-Complete optimization problems are a well-known and widely used set of problems which surveyed and researched in the field of soft computing. Nowadays, because of the acceptable rate of achieving optimal or near-optimal solutions of the mentioned issues, using of nature-inspired algorithms are increasingly considered. One of the familiar problems in the field of NP problems is Maximal Covering Problem which has various applications of pure mathematics to determine the location of mobile network antennas or police stations. In this paper, we introduced a heuristic algorithm called Partitioned Artificial Intelligent Fish Algorithm which using artificial fish-search algorithm, logical partitioning of the search space of this algorithm to several sub-space and change in motor functions in fishes, deals with the suitable, innovative and fast solution of maximal covering problem. The results of implementing this algorithm and comparing it with the performance of some the best known algorithms for solving NP problems will be represented by a very good performance of the proposed algorithm.

Original languageEnglish
Pages (from-to)400-410
Number of pages11
JournalJournal of Theoretical and Applied Information Technology
Volume59
Issue number2
Publication statusPublished - 2014

Fingerprint

Covering Problem
Fish
NP problem
Pure mathematics
Soft Computing
Mobile Networks
Soft computing
Heuristic algorithm
Law enforcement
Search Space
Search Algorithm
Heuristic algorithms
Antenna
Partitioning
NP-complete problem
Optimal Solution
Subspace
Wireless networks
Optimization Problem
Antennas

Keywords

  • Artificial Fish Algorithm
  • Maximal Covering Problem
  • NP-hard problem

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Solving Maximal Covering Problem using Partitioned Intelligent Fish Algorithm. / Jula, Amin; A Sundararajan, Elankovan; Naseri, Narjes Khatoon; Abiat, Reza.

In: Journal of Theoretical and Applied Information Technology, Vol. 59, No. 2, 2014, p. 400-410.

Research output: Contribution to journalArticle

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