Solution of the resource-constrained activity networks.

Abstract

Resource available for the completion of each activity of a project (represented as an activity network) are always limited in the real life and so, finding the optimal schedule for the activities is very hard. Such a problem is termed as Resouce-Constrained Project Scheduling (RCPS) Problem, which is classed as an NP-hard combinatorial optimization problem. Three solution methodologies based on simulated annealing, genetic algorithm and tabu search are developed. The proposed approaches are implemented on the 110 benchmark problems of Patterson. The parameters needed for each proposed algorithm were determined. Also, to validate the solution methodologies, a comparison is done with the popular procedures existing in the literature and the results are encouraging.