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