학술논문

DCA-Based Algorithm for Cross-Functional Team Selection
Document Type
Conference
Source
Proceedings of the 2019 8th International Conference on Software and Computer Applications. :125-129
Subject
CPLEX
Cross-Functional Team
DCA
Genetic Algorithms
MDSB
Language
English
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.

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