A genetic approach to the quadratic assignment problem

A genetic approach to the quadratic assignment problem

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Article ID: iaor19951089
Country: United Kingdom
Volume: 22
Issue: 1
Start Page Number: 73
End Page Number: 83
Publication Date: Jan 1995
Journal: Computers and Operations Research
Authors: ,
Keywords: programming: quadratic
Abstract:

The quadratic assignment problem (QAP) is a well-known combinatorial optimization problem with a wide variety of practical applications. Although many heuristics and semi-enumerative procedures for QAP have been proposed, no dominant algorithm has emerged. In this paper, the authors describe a genetic algorithm (GA) approach to QAP. Genetic algorithms are a class of randomized parallel search heuristics which emulate biological natural selection on a population of feasible solutions. The authors present computational results which show that this GA approach finds solutions competitive with those of the best previously-known heuristics, and argue that genetic algorithms provide a particularly robust method for QAP and its more complex extensions.

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