Skill-based framework for optimal software project selection and resource allocation

Fadi A. Zaraket, Majd Olleik, Ali A. Yassine

    Research output: Contribution to journalArticlepeer-review

    22 Scopus citations

    Abstract

    This paper presents a conceptual framework and a mathematical formulation for software resource allocation and project selection at the level of software skills. First, we introduce a skill-based framework that considers universities, software companies, and potential projects of a country. Based on this framework, we formulate a linear integer program PMax which determines the selection of projects and the allocation of human resources that maximize profit for a certain company. We show that PMax is NP-complete. Therefore, we devise a meta-heuristic, called Tabu Select and Greedily Allocate (TSGA), to overcome the computational complexities. When compared to PMax running on CPLEX, TSGA performs 15 times faster with an accuracy of 98% on small to large size problems where CPLEX converges. On larger problems where CPLEX does not return an answer, TSGA computes a feasible solution in the order of minutes. For demonstration, the proposed skill-based framework and the corresponding mathematical model are applied to Lebanon by performing two surveys on the Lebanese software industry and academia. The case study shows that the proposed framework and mathematical model can be used in practice to improve project selection and resource allocation decisions in software companies.

    Original languageEnglish
    Pages (from-to)308-318
    Number of pages11
    JournalEuropean Journal of Operational Research
    Volume234
    Issue number1
    DOIs
    StatePublished - 1 Apr 2014

    Keywords

    • Meta-heuristic
    • Project selection
    • Resource allocation
    • Software development
    • Software skills

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