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- W1993950002 abstract "Best-first search is a widely used problem solving technique in the field of artificial intelligence. The method has useful applications in operations research as well. Here we describe an application to constrained two-dimensional cutting stock problems of the following type: A stock rectangle S of dimensions (L, W) is supplied. There are n types of demanded rectangles r 1 , r 2 , …, r n , with the ith type having length l i , width w i , value v i , and demand constraint b i . It is required to produce, from the stock rectangle S, a i copies of r i , 1 ≤ i ≤ n, to maximize a 1 v 1 + a 2 v 2 + · + a n v n subject to the constraints a i ≤ b i . Only orthogonal guillotine cuts are permitted. All parameters are integers. A best-first tree search algorithm based on Wang's bottom-up approach is described that guarantees optimal solutions and is more efficient than existing methods." @default.
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- W1993950002 date "1993-08-01" @default.
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- W1993950002 title "Best-First Search Methods for Constrained Two-Dimensional Cutting Stock Problems" @default.
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- W1993950002 doi "https://doi.org/10.1287/opre.41.4.768" @default.
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