This thesis presents a skill-based methodology that considers the universities, software companies, software human resources and potential projects of a country using two integer linear programs, PMax and LCom. PMax determines the selection of projects and the allocation of human resources that maximize profit. We define a lean company as the company that performs a set of projects at the lowest cost. Accordingly, LCom takes an existing company and the output of PMax and generates its lean version. We show that both PMax and LCom are NP-complete. Therefore, we devise a meta-heuristic, called Tabu Select and Greedily Allocate (TSGA), to overcome the computational complexity of PMax. The skill-based methodology is applied to Lebanon by performing two surveys on the Lebanese industry and academia. We evaluate the effectiveness of the local software companies and we determine the most and least important software skills. When compared to CPLEX, TSGA performs 15 times faster with an accuracy of 98percent 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.
Description:
Thesis (M.E.M.)--American University of Beirut, Engineering Management Program, 2012.;"Advisor : Dr. Ali Yassine, Associate Professor, Engineering Management Program Co-Advisor : Dr. Fadi Zaraket, Assistant Professor, Electrical and Computer Engineering--Member of Committee : Dr. Bacel Maddah, Associate Professor, Engineering Management."
Includes bibliographical references (leaves 56-59)
