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Abstract Resources constrained project scheduling problem is very common in industry and one of the most complicated problems to be tackled. The problem is considered as an NP-Hard optimization problem; especially, when a set of large number of activities need to be finished as soon as possible, subject to two sets of constraints (precedence constraints, and resources constraints). Researchers have developed numerous scheduling methods and techniques to overcome the complex nature of this problem. Genetic Algorithms are very promising approaches to solve this problem, in terms of the computational feasibility, and the quality of the solutions. However, the most common models of the genetic algorithms are difficult to be implemented in scheduling problems. On the other hand, using specific and proper design of the genetic algorithms can make the scheduling problems tractable. |