| Resumo: | We address the issue of optimal resource allocation, and more specifically, the analysis of complementarity of resources (primary resource or P-resource and supportive resource or S-resource) to activities in a project. The concept of complementarity can be incorporated into the engineering domain as an enhancement of the efficacy of a "primary" resource (P-resource) by adding to it other "supportive" resources (S-resources). We developed a Genetic Algorithm capable of determining the ideal mixture of resources allocated to the activities of a project, such that the project is completed with minimal cost. This problem has a circularity issue that greatly increases its complexity. In this paper we present a constructive algorithm to build solutions from a chromosome that will be integrated in a Genetic Algorithm, which we illustrate by application to a small instance of the problem. The Genetic Algorithm is based on a random keys chromosome that is very easy to implement and allows using conventional genetic operators for combinatorial optimization problems. A project is formed by a set of activities. Each activity uses a specific set of resources, and it is also necessary to guarantee that there is no overlap in the time it takes to process activities in the same resource.
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