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Abstract: In this paper, we modify a Multi-Objective Evolutionary Algorithm, known as Nondominated sorting Genetic Algorithm-II (NSGA-II) for a parallel machine scheduling problem with three objectives. The objectives are – (1) minimization of total cost due tardiness, (2) minimization of the deterioration cost and (3) minimization of makespan. The formulated problem has been solved by three Multi-Objective Evolutionary Algorithms which are: (1) the original NSGA-II (Non-dominated Sorting Genetic Algorithm–II), (2) SPEA2 (Strength Pareto Evolutionary Algorithm-2) and (3) a modified version of NSGA-II as proposed in this paper. A new mutation algorithm has also been proposed depending on the type of problem and embedded in the modified NSGA-II. The results of the three algorithms have been compared and conclusions have been drawn. The modified NSGA-II is observed to perform better than the original NSGA-II. Besides, the proposed mutation algorithm also works effectively, as evident from the experimental results. [Copyright &y& Elsevier]

Abstract: In this paper we consider parallel identical machines scheduling problems with deteriorating jobs. In this model, job processing times are defined by functions of their starting times. We concentrate on two goals separately, namely, minimizing the total absolute differences in completion times (TADC) and the total absolute differences in waiting times (TADW). We show that the problems remains polynomially solvable under the proposed model. [ABSTRACT FROM AUTHOR]

Abstract: The aim of this paper is to show by counterexamples that Theorems 3–10 and Corollaries 2–5 in Wang et al. [Appl. Math. Model. 34 (2010) 2831–2839] are incorrect. [Copyright &y& Elsevier]