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

E Bohndiek Sarah | Zendy; M. Laheeb | Zendy

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

Author(s) -

E Bohndiek Sarah,

M. Laheeb

Publication year - 2018

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/ijca2018917753

Subject(s) - computer science , swarm behaviour , fish <actinopterygii> , software , scheduling (production processes) , operations research , artificial intelligence , mathematical optimization , algorithm , fishery , operating system , mathematics , engineering , biology

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 multiobjective 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. General Terms Swarm Intelligence.

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