Affiliations: [a] School of Computer and Software, Dalian Neusoft University of Information, Dalian, China
| [b] Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran
| [c] Young Researchers and Elite Club, Babol Branch, Islamic Azad University, Babol, Iran
| [d] Department of Computer Engineering, Sari Branch, Islamic Azad University, Sari, Iran
Correspondence:
[*]
Corresponding author. Ali Ebrahimnejad, Department of Mathematics, Qaemshahr Branch, Islamic Azad University, Qaemshahr, Iran. E-mail: [email protected]; [email protected].
Abstract: In software incremental development methodology, the product develops in several releases. In each release, one set of the requirements is suggested for development. The development team must select a subset of the proposed requirements for development in the next release such that by consideration the limitation of the problem provides the highest satisfaction to the customers and the lowest cost to the company. This problem is known as the next release problem. In complex projects where the number of requirements is high, development teams cannot choose an optimized subset of the requirements by traditional methods, so an intelligent algorithm is required to help in the decision-making process. The main contributions of this study are fivefold: (1) The customer satisfaction and the cost of every requirement are determined by use of fuzzy numbers because of the possible changing of the customers’ priorities during the product development period; (2) An improved approximate approach is suggested for summing fuzzy numbers of different kinds, (3) A new metaheuristic algorithm namely the Binary Artificial Algae Algorithm is used for choosing an optimized subset of requirements, (4) Experiments performed on two fuzzy datasets confirm that the resulted subsets from the suggested algorithm are free of human mistake and can be a great guidance to development teams in making decisions.
