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Multi-objective whale optimization algorithm and multi-objective grey wolf optimizer for solving next release problem with developing fairness and uncertainty quality indicators

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Abstract

Selecting a set of requirements to implement in the next software release is an NP-Hard problem known as NRP. We propose multi-objective versions of grey wolf optimizer and whale optimization algorithm for solving bi-objective NRP. We used these two algorithms and three other evolutionary algorithms to solve NRP problem instances from four datasets. The cost-to-score ratio and the roulette wheel are used to satisfy constraints of the NRP problem. We compare obtained Pareto fronts based on eight quality indicators. In addition to four general multi-objective optimization quality indicators, the three aspects of fairness among clients and also uncertainty are reconfigured as quality indicators. These quality indicators are computed for a Pareto front. Results show that MOWOA performs better than others and makes requirement selection fairer. MOGWO works better than the rest when budget constraints are reduced.

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Authors and Affiliations

  1. Department of Computer Engineering, Yasooj Branch, Islamic Azad University, Yasooj, Iran

    Mohsen Ghasemi & Karamollah Bagherifard

  2. Young Researchers and Elite Club, Yasooj Branch, Islamic Azad University, Yasooj, Iran

    Karamollah Bagherifard & Samad Nejatian

  3. Institute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam

    Hamid Parvin

  4. Faculty of Information Technology, Duy Tan University, Da Nang, 550000, Vietnam

    Hamid Parvin

  5. Department of Computer Engineering, Nourabad Mamasani Branch, Islamic Azad University, Nourabad, Mamasani, Iran

    Hamid Parvin

  6. Department of Electrical Engineering, Yasooj Branch, Islamic Azad University, Yasooj, Iran

    Samad Nejatian

  7. Fractional Calculus, Optimization and Algebra Research Group, Faculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, Vietnam

    Kim-Hung Pho

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  1. Mohsen Ghasemi
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  2. Karamollah Bagherifard
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Correspondence to Hamid Parvin.

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Ghasemi, M., Bagherifard, K., Parvin, H. et al. Multi-objective whale optimization algorithm and multi-objective grey wolf optimizer for solving next release problem with developing fairness and uncertainty quality indicators. Appl Intell 51, 5358–5387 (2021). https://doi.org/10.1007/s10489-020-02018-2

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