Abstract
The resource constrained project scheduling problem is considered as a complex scheduling problem. In order to solve this NP-hard problem, an efficient differential evolution DE algorithm is proposed in this paper. In the algorithm, improved mutation and crossover operators are introduced with an aim to maintain feasibility for generated individuals and hence being able to converge quickly to the optimal solutions. The algorithm is tested on a set of well-known project scheduling problem library PSPLIB, with instances of 30, 60, 90 and 120 activities. The proposed DE is shown to have superior performance in terms of lower average deviations from the optimal solutions compared to some of the state-of-the-art algorithms.
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