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: | Newton Charles, Liang Ko-Hsin, Yao Xin, Hoffman David |
Keywords: | heuristics |
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.