A new evolutionary approach to cutting stock problems with and without contiguity

A new evolutionary approach to cutting stock problems with and without contiguity

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Article ID: iaor2003241
Country: United Kingdom
Volume: 29
Issue: 12
Start Page Number: 1641
End Page Number: 1659
Publication Date: Oct 2002
Journal: Computers and Operations Research
Authors: , , ,
Keywords: heuristics
Abstract:

Evolutionary algorithms (EAs) have been applied to many optimization problems successfully in recent years. The genetic algorithm (GA) and evolutionary programming (EP) are two different types of EAs. GAs use crossover as the primary search operator and mutation as a background operator, while EP uses mutation as the primary search operator and does not employ any crossover. This paper proposes a novel EP algorithm for cutting stock problems with and without contiguity. Two new mutation operators are proposed. Experimental studies have been carried out to examine the effectiveness of the EP algorithm. They show that EP can provide a simple yet more effective alternative to GAs in solving cutting stock problems with and without contiguity. The solutions found by EP are significantly better (in most cases) than or comparable to those found by GAs.

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