Mathematical Modeling and Optimal Blank Generation in Glass Manufacturing
Author(s) -
Raymond E. Phillips,
Matthew Woolway,
D. Fanucchi,
M. Montaz Ali
Publication year - 2014
Publication title -
journal of applied mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.307
H-Index - 43
eISSN - 1687-0042
pISSN - 1110-757X
DOI - 10.1155/2014/959453
Subject(s) - heuristics , mathematical optimization , blank , upper and lower bounds , mathematics , branch and bound , selection (genetic algorithm) , integer (computer science) , combinatorial optimization , matrix (chemical analysis) , function (biology) , combinatorics , computer science , mathematical analysis , materials science , artificial intelligence , evolutionary biology , composite material , biology , programming language , mechanical engineering , engineering
This paper discusses the stock size selection problem (Chambers and Dyson, 1976), which is of relevance in the float glass industry. Given a fixed integer N, generally between 2 and 6 (but potentially larger), we find the N best sizes for intermediate stock from which to cut a roster of orders. An objective function is formulated with the purpose of minimizing wastage, and the problem is phrased as a combinatorial optimization problem involving the selection of columns of a cost matrix. Some bounds and heuristics are developed, and two exact algorithms (depth-first search and branch-and-bound) are applied to the problem, as well as one approximate algorithm (NOMAD). It is found that wastage reduces dramatically as N increases, but this trend becomes less pronounced for larger values of N (beyond 6 or 7). For typical values of N, branch-and-bound is able to find the exact solution within a reasonable amount of time
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