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Overlapped Grouping Genetic Algorithm for Optimization of Reels Cutting Planning Problems

[+] Author Affiliations
Waleed M. A. Abd El-Hady

Unionaire, 6th of October City, Egypt

Sayed M. Metwalli

Cairo University, Cairo, Egypt

Paper No. DETC2007-35012, pp. 3-13; 11 pages
  • ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 6: 33rd Design Automation Conference, Parts A and B
  • Las Vegas, Nevada, USA, September 4–7, 2007
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4807-8 | eISBN: 0-7918-3806-4
  • Copyright © 2007 by ASME


The optimization of Reel-Cutting Planning Problem “RCPP” is concerned with finding the best selection of a strategic reel set and the corresponding tactical cutting lengths “sheets set”, from a wide feasible space, to be used in producing a set of blanks. The problem is classified as a weighted multi objectives two-staged guillotine two-dimensional Cutting Stock Problem “CSP” of Dyckoff’s type 2/V/D/M. This paper presents a tailored metaheuristic solution using grouping genetic algorithms (GGAs). Overlapped Chromosome representation is newly developed for optimization. Developed also an especial database to create the cutting patterns of resulting solution. The objective in this application is to minimize the total cost, which includes the total material cost required to achieve a lot size, the cost of selecting reels set size, and the cost of cutting lengths from these reels “sheet set size”. An industrial case study is considered. The attained optimum cutting plan provides an overall improvement of 4.3% over the current professional cutting plan. The reduction in the reel set size is from five to an optimum of three reels. The developed procedure also provides reduction of trim loss of 4% over the current plan. The developed approach also proved to be faster than the currently used techniques.

Copyright © 2007 by ASME



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