An alternative approach for unbalanced assignment problem via genetic algorithm. (English) Zbl 1241.90073

Summary: This paper presents an alternative approach using genetic algorithm to a new variant of the unbalanced assignment problem that dealing with an additional constraint on the maximum number of jobs that can be assigned to some agent(s). In this approach, genetic algorithm is also improved by introducing newly proposed initialization, crossover and mutation in such a way that the developed algorithm is capable to assign optimally all the jobs to agents. Computational results with comparative performance of the algorithm are reported for four test problems.


90B80 Discrete location and assignment
90C59 Approximation methods and heuristics in mathematical programming
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