Solving the discrete time/resource trade-off problem in project scheduling with genetic algorithms

In this paper, we develop a metaheuristic procedure for solving the discrete time/resource trade-off problem in the field of project scheduling. In this problem, a project contains activities interrelated by finish–start-type precedence constraints with a time lag of zero, which require a single constrained renewable resource. Each activity has a specified work content and can be performed in different modes, i.e. with different durations and resource requirements; as long as the required work content is met. The objective is to schedule each activity in one of its modes in order to minimize the project makespan. To tackle this problem, we use a genetic algorithm in which a new method based on the resource utilization ratio is developed for generation of crossover points and also a local search method is incorporated with the algorithm. Comparative computational results reveal that this procedure outperforms the best available results in the literature.