### 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 language | English |
---|---|

Pages (from-to) | 400-410 |

Number of pages | 11 |

Journal | Journal of Theoretical and Applied Information Technology |

Volume | 59 |

Issue number | 2 |

Publication status | Published - 2014 |

### Fingerprint

### Keywords

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

### ASJC Scopus subject areas

- Computer Science(all)
- Theoretical Computer Science

### Cite this

*Journal of Theoretical and Applied Information Technology*,

*59*(2), 400-410.

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

Research output: Contribution to journal › Article

*Journal of Theoretical and Applied Information Technology*, vol. 59, no. 2, pp. 400-410.

}

TY - JOUR

T1 - Solving Maximal Covering Problem using Partitioned Intelligent Fish Algorithm

AU - Jula, Amin

AU - A Sundararajan, Elankovan

AU - Naseri, Narjes Khatoon

AU - Abiat, Reza

PY - 2014

Y1 - 2014

N2 - 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.

AB - 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.

KW - Artificial Fish Algorithm

KW - Maximal Covering Problem

KW - NP-hard problem

UR - http://www.scopus.com/inward/record.url?scp=84892739317&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84892739317&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:84892739317

VL - 59

SP - 400

EP - 410

JO - Journal of Theoretical and Applied Information Technology

JF - Journal of Theoretical and Applied Information Technology

SN - 1992-8645

IS - 2

ER -