Integrating genetic algorithm and heuristic methods to solve the project selection and scheduling problem

This paper considers the integrated project selection and scheduling problem as a proposed recent model to optimize expected benefits and satisfy the resource, priority, end time and other constraints. The used model, regarded given different payments for activities of each project that will be selected; which depend on completion time of each activity. This paper develops a two-layer genetic algorithm that uses genetic algorithm as an agent to deal with projects in a first layer and heuristic methods for second one. To evaluate the proposed algorithms, some small-scale examples were considered and they are compared with Gams modeling application results and an available similar algorithm that used random search for the second layer. To realize the efficiency of suggested methods, some real medium-scale design projects of a research institute of Ferdowsi University were studied.