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Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Sarah E. Almshhadany, Laheeb M. Ibrahim
10.5120/ijca2018917753

Sarah E Almshhadany and Laheeb M Ibrahim. Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem. International Journal of Computer Applications 181(16):6-13, September 2018. BibTeX

@article{10.5120/ijca2018917753,
	author = {Sarah E. Almshhadany and Laheeb M. Ibrahim},
	title = {Using Multi-objective Artificial Fish Swarm Algorithm to Solve the Software Project Scheduling Problem},
	journal = {International Journal of Computer Applications},
	issue_date = {September 2018},
	volume = {181},
	number = {16},
	month = {Sep},
	year = {2018},
	issn = {0975-8887},
	pages = {6-13},
	numpages = {8},
	url = {http://www.ijcaonline.org/archives/volume181/number16/29904-2018917753},
	doi = {10.5120/ijca2018917753},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this paper, a new multi-objective artificial fish swarm algorithm was proposed based on the principles of PAES algorithm and it is used to solve SPSP. The aim of this proposal is to solve the software project scheduling problem with artificial fish swarm algorithm and to overcome some disadvantages that AFSA suffer from. The performance of the proposed algorithm was compared with another multi-objective AFSA based on the use of global information (GAFSA), in terms of speed, quality of produced solutions and complexity of algorithm operations. The results show that the proposed algorithm is faster, easier to implement, require less computations, and had obtained better nondominated solutions than the other algorithm.

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Keywords

Software project scheduling problem, multi-objective optimization, artificial fish swarm algorithm.