A new artificial immune system algorithm for multi objective fuzzy flow shop scheduling: a real world application

Abstract

In this paper a new artificial immune system (AIS) algorithm is proposed to solve multi objective fuzzy flow shop scheduling problem. The objectives are considered to be minimizing the average tardiness and the number of tardy jobs. The developed new AIS algorithm is applied in an engine cylinder liner manufacturing process. The feasibility and effectiveness of the proposed new AIS is demonstrated by comparing with the Genetic algorithm. Computational results demonstrate that the proposed new AIS algorithm is a more effective meta-heuristic for the multi objective, flow shop scheduling problem with fuzzy processing time and due date.