A robust genetic algorithm for resource allocation in project scheduling. (English) Zbl 1024.90036

Summary: Genetic algorithms have been applied to many different optimization problems and they are one of the most promising metaheuristics. However, there are few published studies concerning the design of efficient genetic algorithms for resource allocation in project scheduling. In this work we present a robust genetic algorithm for the single-mode resource constrained project scheduling problem. We propose a new representation for the solutions, based on the standard activity list representation and develop new crossover techniques with good performance in a wide sample of projects. Through an extensive computational experiment, using standard sets of project instances, we evaluate our genetic algorithm and demonstrate that our approach outperforms the best algorithms appearing in the literature.


90B35 Deterministic scheduling theory in operations research
90B50 Management decision making, including multiple objectives
90C59 Approximation methods and heuristics in mathematical programming


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