Algorithms and Methods Inspired from Nature for Solving Supply Chain and Logistics Optimization Problems: A Survey

View Sample PDF

Author(s): Georgios Dounias (Management and Decision Engineering Lab, University of the Aegean, Greece)and Vassilios Vassiliadis (Management and Decision Engineering Lab, University of the Aegean, Greece)
Copyright: 2015
Pages: 31
Source title: Research Methods: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-7456-1.ch012

Keywords: Information Science Reference / Library & Information Science / Research Methods

Purchase

View Algorithms and Methods Inspired from Nature for Solving Supply Chain and Logistics Optimization Problems: A Survey on the publisher's website for pricing and purchasing information.

Abstract

The current work surveys 245 papers and research reports related to algorithms and methods inspired from nature for solving supply chain and logistics optimization problems. Nature Inspired Intelligence (NII) is a challenging new subfield of artificial intelligence (AI) particularly capable of dealing with complex optimization problems. Related approaches are used either as stand-alone algorithms, or as hybrid schemes i.e. in combination to other AI techniques. Ant Colony Optimization (ACO), Particle Swarm Optimization, Artificial Bee Colonies, Artificial Immune Systems and DNA Computing are some of the most popular approaches belonging to nature inspired intelligence. On the other hand, supply chain management represents an interesting domain of OR applications, including a variety of hard optimization problems such as vehicle routing (VRP), travelling salesman (TSP), team orienteering, inventory, knapsack, supply network problems, etc. Nature inspired intelligent algorithms prove capable of identifying near optimal solutions for instances of those problems with high degree of complexity in a reasonable amount of time. Survey findings indicate that NII can cope successfully with almost any kind of supply chain optimization problem and tends to become a standard in related scientific literature during the last five years.

The IRMA Community

Research IRM

Algorithms and Methods Inspired from Nature for Solving Supply Chain and Logistics Optimization Problems: A Survey

Purchase

Abstract

Related Content

IRMA Sponsors