Differential Search (DS) algorithm is a new meta-heuristic for solving real-valued numerical optimization. This paper introduces a new method based on DS for solving Resource Constrained Project Scheduling Problem (RCPSP). The RCPSP is aimed to schedule a set of activities at minimal duration subject to precedence constraints and the limited availability of resources. The proposed method is applied to PSPLIB case studies and its performance is evaluated in comparison with some of state of art methods. Experimental results show that the proposed method is effective. Also, it is among the best algorithms for solving RCPSP.

Solving resource constrained project scheduling problem (RCPSP) has important role in the context of project scheduling. Considering a single objective RCPSP, the goal is to find a schedule that minimizes the makespan. This is NP-hard problem (Blazewicz et al., 1983) and one may use meta-heuristics to obtain a global optimum solution or at least a near-optimal one. Recently, various meta-heuristics such as ACO, PSO, GA, SA etc have been applied on RCPSP. Bee algorithms are among most recently introduced meta-heuristics. This study aims at adapting artificial bee colony as an alternative and efficient optimization strategy for solving RCPSP and investigating its performance on the RCPSP. To evaluate the artificial bee colony, its performance is investigated against other meta-heuristics for solving case studies in the PSPLIB library. Simulation results show that the artificial bee colony presents an efficient way for solving resource constrained project scheduling problem.