Skill-based Framework for Optimal Software Project Selection and Resource Allocation

Fadi A. Zaraket, Majd Olleik, Ali Yassine — American University of Beirut

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 Selectand 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 runs until completion and 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.

Resources

The following file contains answers to the first survey from 11 Lebanese companies on staffing, cost, skills, and the details of one selected project from each company.

Survey on 11 Lebanese companies

The following file contains data that we passed to PMAX using CPLEX and TSGA.

Simulation data

The following files contain the validation survey for the PMAX results and the skill-based framework.

Validation survey Validation survey results

Proof of theorem 1

Equivalence of clause C7

Detailed results for Table 4

Online appendix

 
pmax.txt · Last modified: 2020/07/13 12:31 (external edit)
 
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