DCA-Based Algorithm for Cross-Functional Team Selection

Abstract

This is a continuing work of Ngo et al, 2018 [1]. They have proposed a mixed binary integer quadratic programming (MIQP) model for cross-functional team selection. The model called Minimum distance to the boundary, MDSB. It is not only specific to team selection but also a generic model for other problems that in form of searching for the best-matched candidate to a predefined target. Ngo et al designed a generic algorithm (GA) for solving MDSB. The GA algorithm is efficient but it also comes with several disadvantages. In this paper, we propose a DCA-based algorithm to solve the MDSB. We compared the proposed algorithm with MIQP-CPLEX and Genetic Algorithm. The numerical results show that our algorithm not only provides the best objective value but also significantly faster than the other compared algorithms.