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Pinto, E.G. (2004) Supply Chain Optimization Using Multi-Objective Evolutionary Algorithms. Department of Industrial and Manufacturing Engineering, the Pennsylvania State University, University Park, 15-26.

has been cited by the following article:

• TITLE: Models for Optimization of Supply Chain Network Design Integrating the Cost of Quality: A Literature Review

  AUTHORS: Lamiae Douiri, Abdelouahhab Jabri, Abdellah El Barkany

  KEYWORDS: Cost of Quality, Supply Chain Management, Multi-Objective Optimization, Genetic Algorithm, Simulated Annealing

  JOURNAL NAME: American Journal of Industrial and Business Management, Vol.6 No.8, August 12, 2016

  ABSTRACT: After focusing on Cost of Quality (CoQ), the companies must now move into integrating the CoQ into Supply Chain upstream and downstream, to address CoQ issues across Supply Chain Network Design (SCND) modeling. In this preliminary study, we propose a state of the art of the published works on models and classifications of SCND incorporating the CoQ existing in the literature. In the second part of this paper, we will present a review by studying and analyzing the application of some meta-heuristics to solve supply chain models. The reviewed meta-heuristics include: the genetic algorithm (GA), and simulated annealing (SA). Finally, we suggest directions for future research.