A genetic algorithm for a 2D industrial packing problem
Computers and Industrial Engineering
A Review of the Application ofMeta-Heuristic Algorithms to 2D Strip Packing Problems
Artificial Intelligence Review
Genetic Algorithm Coding Methods for Leather Nesting
Applied Intelligence
An innovative virtual-engineering system for supporting integrated footwear design
International Journal of Intelligent Engineering Informatics
Genetic regulatory network-based symbiotic evolution
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
This paper proposes a methodology that integrates in-house placement heuristics with genetic algorithms to solve the nesting problems of shoe making. The problems are classified as placing a set of irregular patterns on a regular area and limited to at most two different types of patterns on the area. Because of the intractability of the nesting problem, our objective is to utilize genetic algorithms' fast convergence and solution quality to improve material utilization and reduce the calculation time of the pattern. Using the real-life data of two international brands of athletic shoes, the empirical results show that our proposed methodology can reduce average material requirements by 2.64% and average nesting time by 69.15% compared to those of current in-house software. The reduction of materials is becoming more important given that the industry is facing continuingly declining profit margins.