WGW: A Hybrid Approach Based on Whale and Grey Wolf Optimization Algorithms for Requirements Prioritization

Authors

  • Raja Masadeh The World Islamic Sciences and Education University
  • Amjad Hudaib
  • Abdullah Alzaqebah

DOI:

https://doi.org/10.25728/assa.2018.18.2.576

Keywords:

Requirement prioritizations (RP), Whale Optimization Algorithm (WOA), Grey wolf optimization (GWO), Replacement Access, Library and ID Card project (RALIC), RP-WOA.

Abstract

Requirement engineering is the base phase of any software project, since this phase is concerned about requirements identification, processing and manipulation. The main source of these requirements is the project stakeholders with considering the project constraints and limitation.  Number of requirement is varying for each project, so the requirements prioritization term comes for prioritizing the order of execution for software requirements according to the stakeholder's opinions and decisions. Various proposed optimization algorithms are employed to solve optimization problems; recently whale optimization (WO) algorithm is proposed in 2016 by Mirjalili which mimics the main characteristic of humpback whales which is the foraging method that is called bubble-net technique.  On the other hand Grey wolf optimization (GWO) algorithm was proposed in 2014 in order to solve optimization problems by imitating the grey wolves hunting behavior. In this paper, a Hybrid approach based on Whale and Grey wolf optimization algorithms (WGW) is proposed by combining the advantages of each algorithm in order to prioritize the software requirements. Moreover, the data set that used in this paper is RALIC which a real software project’s requirements is in order to evaluate the proposed method. Thus, the proposed method shows 91% accuracy of requirements prioritization comparing with RALIC data sat.  

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Published

2018-08-23

How to Cite

Masadeh, R., Hudaib, A., & Alzaqebah, A. (2018). WGW: A Hybrid Approach Based on Whale and Grey Wolf Optimization Algorithms for Requirements Prioritization. Advances in Systems Science and Applications, 18(2), 63–83. https://doi.org/10.25728/assa.2018.18.2.576

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Section

Articles