- All Journals
- Al-Qadisiyah University
- Basrah University
- Kirkuk University
- Mosul University
- The Iraqi Borad for Medical Specialization
- University of Anbar
- University of Technology
- Al Mustafa University
- Al-Zahraa University for Women
- Alnoor University
- Kunooz University
- Misan University
- Ninevah University
- Tikrit University
- University of Al-Hamdaniya
- University of Kerbala
Nature-inspired optimization algorithms in knapsack problem: A review | ||
| IRAQI JOURNAL OF STATISTICAL SCIENCES | ||
| Article 4, Volume 16, Issue 3, 2019, Pages 55-72 PDF (846.17 K) | ||
| DOI: 10.33899/iqjoss.2019.0164174 | ||
| Authors | ||
| Ghalya Tawfeeq Basheer* 1; Zakariya Yahya Algamal* 2 | ||
| 1Department of operations research and intelligent techniques, University of Mosul, Mosul, Iraq. | ||
| 2Dept. of Statistics and Informatics/ college of computer sciences and mathematics/ University of Mosul, Mosul, iraq | ||
| Abstract | ||
| Meta-heuristic algorithms have become an arising field of research in recent years. Some of these algorithms have proved to be efficient in solving combinatorial optimization problems, particularly knapsack problem. In this paper, four meta-heuristic algorithms are presented particle swarm optimization, firefly algorithm, flower pollination algorithm and monarch butterfly optimization in solving knapsack problem as example of NP-hard combinational optimization problems. Based on twenty 0-1 knapsack problem instances, the computational results demonstrated that the binary flower pollination algorithm has the ability to find the best solutions in reasonable time. | ||
| Keywords | ||
| Combinatorial optimization problem; NP-hard problem; 0-1 knapsack problem; Meta-heuristic algorithms | ||
|
Statistics Article View: 641 PDF Download: 534 |
||