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Nature-Inspired Intelligence in Supply Chain Management: A Review of Selected Methods and Applications

Nature-Inspired Intelligence in Supply Chain Management: A Review of Selected Methods and Applications
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Author(s): Vassilios Vassiliadis (University of the Aegean, Greece) and Giorgos Dounias (University of the Aegean, Greece)
Copyright: 2011
Pages: 31
Source title: Supply Chain Optimization, Design, and Management: Advances and Intelligent Methods
Source Author(s)/Editor(s): Ioannis Minis (University of the Aegean, Greece), Vasileios Zeimpekis (University of the Aegean, Greece), Georgios Dounias (University of the Aegean, Greece) and Nicholas Ampazis (University of the Aegean, Greece)
DOI: 10.4018/978-1-61520-633-9.ch001

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Abstract

Supply chain management is a vital process for the competitiveness and profitability of companies. Supply chain consists of a large and complex network of components such as suppliers, warehouses, customers etc. which are connected in almost every possible way. Companies’ main aim is to optimize the components of these complex networks to their benefit. This constitutes a challenging optimization problem and often, traditional mathematical approaches fail to overcome complexity and to converge to the optimum solution. More robust methods are required sometimes in order to yield to the optimal. The field of artificial intelligence offers a great variety of meta-heuristic techniques which specialize in solving such complex optimization problems, either accurately, or by obtaining a practically useful approximation, even if real time constraints are imposed. The aim of this chapter is to present a survey of the available literature, regarding the use of nature-inspired methodologies in supply chain management problems. Nature-inspired intelligence is a specific branch of artificial intelligence. Its unique characteristic is the algorithmic imitation of real life systems such as ant colonies, flock of birds etc. in order to solve complex problems.

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