A heuristic approach to minimize the number of saw cycles in small-scale furniture factories

Alyne Toscano (), Socorro Rangel () and Horacio Hideki Yanasse ()
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Alyne Toscano: UFTM - Universidade Federal do Triângulo Mineiro
Socorro Rangel: UNESP - Univ Estadual Paulista
Horacio Hideki Yanasse: Universidade Federal de São Paulo

Annals of Operations Research, 2017, vol. 258, issue 2, No 23, 719-746

Abstract: Abstract This paper addresses a two-dimensional cutting stock problem arising in furniture factories. The problem involves the simultaneous optimization of two, usually conflicting, objectives: minimizing the total number of objects and maximizing the cutting machine productivity in terms of the number of objects that are simultaneously cut. A heuristic algorithm to solve the problem is proposed based on variables and constraints generation. The main idea is to add, in a dynamic way, bounds to the frequency of some chosen cutting patterns. At each iteration a solution is generated and at the end we have a set of non-dominated solutions. A computational study was conducted using real data from a small-scale furniture factory. The results show that the proposed algorithm finds solutions that are as good as or better than the ones used in practice in the furniture factory.

Keywords: Two-dimensional cutting stock; Saw cycles; Machine productivity; Column generation; Heuristic; Furniture production (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10479-015-1955-9

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