Cohesion and balance in a human resource allocation problem

Abstract

Collaborative work appears between intelligent agents of different types. The problem discussed occurred when many construction workers were taken to Germany from Romania to work in construction projects. Managers have to make independent groups of workers from some categories, like carpenters, brick layers, etc. To discover their collaborative attitudes they use the scoring method, where every worker scores the others from different trades. The objectives are to form groups of workers with high compatibility value and to have a high compatibility value for the worst group, too. The problem becomes more interesting if software collaborative groups or specialized intelligent agents are involved. One has to prospect also the level of knowledge overlap between the trade groups of agents. This paper resumes to the problem of construction workers so as there is no overlap between the trades and the level of knowledge is not in the universe of discourse. We propose a Greedy and a genetic algorithm approach and we compare these methods.