Resource levelling using genetic algorithms for a power plant boiler construction project
by Christos Kyriklidis; Georgios Dounias
International Journal of Decision Support Systems (IJDSS), Vol. 2, No. 1/2/3, 2016

Abstract: This paper deals with the use of intelligent techniques for resource levelling optimisation. An intelligent approach previously introduced but enriched and improved, is applied in a real world project corresponding to the construction of a power plant boiler. Resource levelling optimisation is related to the optimal handling of available resources of a project. Conventional optimisation approaches like exhaustive or greedy search are unable to provide high quality solutions in a short amount of time. Thus, intelligent approaches properly modified, are used, which are capable of quickly reaching highly accurate near-optimal solutions. In this work, a genetic algorithm is applied in the resource levelling data of the boiler construction project, using a new approach that introduces a special time interval for the activities calculation of the early and late start. Accordingly, resource profiles are further evaluated with the use of a special multiple evaluation function approach called sequential function evaluation (SFE).

Online publication date: Tue, 24-Jan-2017

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