An Improved Artificial Immune System for Solving Loading Problems in Flexible Manufacturing Systems

Abstract

Flexible manufacturing system (FMS) has been a focal point in manufacturing related research for improving competitiveness. Machine loading problem in FMS is known to be NP-hard problems and its complexity so extensive that even small problems take excessive computational time to reach the optimal solution. Since the problem has been recognized as one of the most important planning problems, it needs to be solved before actual manufacturing. The objective of the loading problems is to minimize the system unbalance and maximize the throughput satisfying the technological constraints such as availability of machining time and tool slots. To ease the tedious computations, and to get a good solution for large problems, this paper proposes an improved artificial immune system algorithm. It demonstrated the capabilities of the proposed algorithm to converge faster and to a better solution than other comparable techniques. For the same cause, the proposed algorithm has been tested over a set of benchmark problems taken from open literature.