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G. H. Zhang, X. Y. Shao, P. G. Li and L. Gao, “An Effective Hybrid Particle Swarm Optimization Algorithm for Multi-Objective Flexible Job-Shop Scheduling Problem,” Computers & Industrial Engineering, Vol. 56, No. 4, 2009, pp. 1309-1318. doi:10.1016/j.cie.2008.07.021

has been cited by the following article:

• TITLE: Modified NSGA-II for a Bi-Objective Job Sequencing Problem

  AUTHORS: Susmita Bandyopadhyay

  KEYWORDS: Job Sequencing; Multi-Objective Evolutionary Algorithm (MOEA); NSGA-II (Non-Dominated Sorting Genetic Algorithm-II); Tardiness; Deterioration Cost

  JOURNAL NAME: Intelligent Information Management, Vol.4 No.6, November 20, 2012

  ABSTRACT: This paper proposes a better modified version of a well-known Multi-Objective Evolutionary Algorithm (MOEA) known as Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The proposed algorithm contains a new mutation algorithm and has been applied on a bi-objective job sequencing problem. The objectives are the minimization of total weighted tardiness and the minimization of the deterioration cost. The results of the proposed algorithm have been compared with those of original NSGA-II. The comparison of the results shows that the modified NSGA-II performs better than the original NSGA-II.