TY - JOUR
T1 - Skill-based framework for optimal software project selection and resource allocation
AU - Zaraket, Fadi A.
AU - Olleik, Majd
AU - Yassine, Ali A.
PY - 2014/4/1
Y1 - 2014/4/1
N2 - 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.
AB - 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.
KW - Meta-heuristic
KW - Project selection
KW - Resource allocation
KW - Software development
KW - Software skills
UR - http://www.scopus.com/inward/record.url?scp=84890437647&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84890437647&partnerID=8YFLogxK
U2 - 10.1016/j.ejor.2013.09.035
DO - 10.1016/j.ejor.2013.09.035
M3 - Article
AN - SCOPUS:84890437647
SN - 0377-2217
VL - 234
SP - 308
EP - 318
JO - European Journal of Operational Research
JF - European Journal of Operational Research
IS - 1
ER -