Brain Drain Optimization (BRADO) Algorithm to Solve Multi-Objective Expert Team Formation Problem in Social Networks

Abstract

Team performance and the composition of the members determine the success of a project. The multi-objective expert team formation problem seeks to identify a collaborative and affordable team of experts such that the hiring costs are minimized and mutual communication is maximized given a network of experts and an essential set of skills. A new swarm-based metaheuristic, called BRADO, has been utilized to address this NP-hard problem. The BRADO algorithm emulates the emigration phenomenon of intellectual elites of society. This problem has been solved by considering two different approaches, the Sigma, and the Multiplication methods, for integrating the affordability and collaboration objective functions. The problem has been solved for projects of varying scales by the proposed BRADO, Multi-objective PSO, NSGA-II, and Multi-objective ICA. Our experiments show that BRADO provides more efficient solutions to the multi-objective expert team formation problem than the other algorithms, especially for projects with more required skills.