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Research Article Open access CC BY 3.0

A Method for Two-Dimensional Cutting Stock Problem with Triangular Shape Items

W. N. P. Rodrigo, W. B. Daundasekera, A. A. I. Perera

Journal of Advances in Mathematics and Computer Science · pp. 750–771 · Published 21 Aug 2013

10.9734/BJMCS/2013/5165

Abstract

Increasing cost of raw material and need to avoid industrial wastage, solving cutting stock problems became of great interest in the area of Operations Research. An optimum cutting stock problem can be defined as cutting a main sheet into smaller pieces while minimizing total wastage of the raw material or maximizing overall profit obtained by cutting smaller pieces from the main sheet. Objective of this study is to generate feasible cutting patterns for two-dimensional triangular shape cutting items. An algorithm is presented based on modified Branch and Bound Algorithm. A computer program is developed using Matlab software package to generate feasible cutting patterns. As a case study, four different sizes of triangular shape items with their demands are selected to cut from a main sheet with known dimensions. Applying proposed algorithm, demand is satisfied and total wastage is minimized. Proposed algorithm can be exploited to generate cutting patterns for rectangular and triangular cutting items at the same time and more suitable for medium size two dimensional cutting stock problem.

Cutting stock problem Branch and Bound Algorithm pattern generation Matlab software package

Cited by 7

The N-Sheet Model in Capacitated Multi-Period Cutting Stock Problem with Pattern Set-Up Cost

S. Octarina, P. Bangun, Sisca Pebrina · 2020 3rd International Seminar on Research of Information Technology and Intelligent Systems (ISRITI) · 2020

Set Covering Model in Solving Multiple Cutting Stock Problem

S. Octarina, Devi Gusmalia Juita, Ning Eliyati · 2020

The greedy randomized adaptive search procedure method in formulating set covering model on cutting stock problem

S. Octarina, F. M. Puspita, S. Supadi · Journal of Physics, Conference Series · 2020

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