Artificial immune system based approach for solving resource constraint project scheduling problem

In this paper, resource-constrained project scheduling problem (RCPSP) is discussed with an objective of minimizing the makespan of a project. Due to its universality, it has a variety of applications as in manufacturing, production planning, project management and elsewhere. It is a well known computationally complex problem, thus warrants the application of heuristics techniques or AI based optimization tools to achieve optimal or near optimal solution in real time. In this research, the artificial immune system (AIS) approach is proposed to solve the aforementioned problem. It exploits the beauty of learning and memory acquisition to ensure the convergence with faster rate. During extensive computational experiment, it is found that the performance of the AIS algorithm on a well known data set of resource-constrained project scheduling problem is superior as compared to GA, fuzzy-GA, LFT, GRU, SIO, MINSLK, RSM, RAN, and MJP based approaches.