Job shop scheduling optimization using multi-modal immune algorithm

Abstract

A multi-modal immune algorithm is utilized for finding optimal solutions to job-shop scheduling problem emulating the features of a biological immune system. Inter-relationships within the algorithm resemble antibody molecule structure, antibody-antigen relationships in terms of specificity, clonal proliferation, germinal center, and the memory characteristics of adaptive immune responses. In addition, Gene fragment recombination and several antibody diversification schemes were incorporated into the algorithm in order to improve the balance between exploitation and exploration. Moreover, niche scheme is employed to discover multi-modal solutions. Numerous well-studied benchmark examples were utilized to evaluate the effectiveness of the proposed approach. © Springer-Verlag Berlin Heidelberg 2007.