A genetic algorithm for resource investment project scheduling problem, tardiness permitted with penalty

In this paper a genetic algorithm for solving a class of project scheduling problems, called Resource Investment Problem, is presented. Tardiness of project is permitted with defined penalty. Elements of algorithm such as chromosome structure, unfitness function, crossover, mutation, immigration and local search operations are explained.The performance of this genetic algorithm is compared with the performance of other published algorithms for Resource Investment Problem. Also 690 problems are solved and their optimal solutions are used for the performance tests of the genetic algorithm. The tests results are quite satisfactory.