Solving a multi-objective resource-constrained project scheduling problem using a cuckoo optimization algorithm

Scheduling is an important factor in project success. In the real world atmosphere, project scheduling problems involve multiple objectives which must be optimized simultaneously. According to the literature, several meta-heuristic algorithms have been used in single objective resource-constrained project scheduling problems, but very few of them have used a multi-objective framework. In this study, we focus on a multi-objective resource-constrained project scheduling problem by minimizing project completion time and the time value of project costs, which is the main contribution of the current research. The goal is to provide an algorithm that can find optimum Pareto front solutions, using a multi-objective cuckoo optimization algorithm. In order to increase the efficiency of the algorithm, the algorithm parameters are tuned using Taguchi tests. Finally, the solutions derived from the algorithm have been compared to those obtained from NSGA-II. The experiments show the efficiency of the proposed algorithm. (C) 2014 Sharif University of Technology. All rights reserved.