Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems

Mishra, Nishikant; Kumar, Vikas

Abstract

The changing global scenario and increased competitiveness has enforced manufacturers to optimize their processes to sustain their position in the market. Manufacturing firms rely on an effective process plan to efficiently utilize their manufacturing resources. Therefore, process plan selection is a crucial and often very complex task. The complexity further increases when there are alternative machines, setups, and processes during manufacturing operations. This research discusses process plan selection problems using Genetic Algorithms with Chromosome Differentiation (GACD) optimization technique. Comparative results on a case study as well as on randomly generated datasets of increasing complexity confirm that the proposed algorithm achieves an improved balance between exploration and exploitation, and has a better ability to escape from the local minima than other efficient meta-heuristic approaches. © 2011 Scrivener Publishing LLC. All rights reserved.

Citation

Mishra, N., & Kumar, V. (2011). Genetic Algorithms with Chromosome Differentiation (GACD) Based Approach for Process Plan Selection Problems. In M. Tiwari, & J. A. Harding (Eds.), Evolutionary Computing in Advanced Manufacturing (77-94). Wiley. https://doi.org/10.1002/9781118161883.ch5

• Publication Date: Aug 22, 2011
• Deposit Date: Jun 8, 2022
• Publisher: Wiley
• Pages: 77-94
• Book Title: Evolutionary Computing in Advanced Manufacturing
• Chapter Number: 5
• ISBN: 9780470639245
• DOI: https://doi.org/10.1002/9781118161883.ch5
• Public URL: https://hull-repository.worktribe.com/output/3614014