A Competitive Nature-Inspired Cuckoo Search Algorithm for Solving the Resource Constrained Project Scheduling Problem

Since its advent, the resource constrained project scheduling problem has been a favorite NP-Hard problem studied by many researchers. In this paper, we examine this problem with a focus on the total project time minimization, usually known as the makespan minimization. To this end, a nature-inspired Cuckoo Search Algorithm (CSA) has been introduced that works by simulating the brooding parasitism of some cuckoo birds in nature. In a nutshell, the proposed cuckoo search algorithm has two main capabilities including: a) a global random search using Levy flights, and b) a local random refinement strategy. In addition, a double justification method has been employed to improve the generated solutions. Simultaneous use of these features can maximize the efficiency of resource searches in uncertain environments. Experimental results on the standard J30, J60, and J120 test sets from the PSPLIB are also presented, showing that the CSA has satisfying results compared with the other well-reported algorithms