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The Journal of Operations Research, Statistics, Econometrics and Management Information Systems
Solution Approach to Cutting Stock Problems Using Iterative Trim Loss Algorithm and Monte-Carlo Simulation
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Abstract
Cutting Stock Problems are the most studied NP-Hard combinatorial problems among optimization problems. An One-dimensional Cutting Stock Problem (1-CSP), which aims to create cutting patterns to minimize trim loss, is one of the best known optimization problems. The difficulty of the solution stages and the lack of a definite solution method that can be applied to all problems have caused these problems to attract a lot of attention by researchers. This study includes a hybrid solution algorithm combined with iterative trim loss algorithm and Monte Carlo simulations, and a comparative study of the method with the solution methods in the literature, for the solution of orders to be obtained with minimum cutting loss from the same type of stocks.
Keywords: Combinatorial Optimization, Cutting Stock Problems, NP-Hard
Jel Classification: C46
Suggested citation
(). Solution Approach to Cutting Stock Problems Using Iterative Trim Loss Algorithm and Monte-Carlo Simulation. Alphanumeric Journal, 11(2), 125-136. https://doi.org/10.17093/alphanumeric.1293487
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2023.11.02.OR.02
alphanumeric journal
Pages 125-136
Received: May 6, 2023
Accepted: Dec. 19, 2023
Published: Dec. 31, 2023
2023 Köksal, Ö., Eroğlu, E.
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