The Resource Leveling Problem with multiple resources using an adaptive genetic algorithm

Resource management ensures that a project is completed on time and at cost, and that its quality is as previously defined; nevertheless, resources are scarce and their use in the activities of the project leads to conflicts in the schedule. Resource leveling problems consider how to make the resource consumption as efficient as possible. This paper presents an Adaptive Genetic Algorithm for the Resource Leveling Problem, and its novelty lies in using the Weibull distribution to establish an estimation of the global optimum as a termination condition. The extension of the project deadline with a penalty is allowed, avoiding the increase in the project criticality. The algorithm is tested with the Project Scheduling Problem Library PSPLIB. The proposed algorithm is implemented using VBA for Excel 2010 to provide a flexible and powerful decision support system that enables practitioners to choose between different feasible solutions to a problem in realistic environments.