A Hybrid Genetic Algorithm for Optimization of Two-Dimensional Cutting-Stock Problem

In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfill the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.

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A Hybrid Genetic Algorithm for Optimization of Two-dimensional Cutting-Stock Problem

International Journal of Applied Metaheuristic Computing ◽

10.4018/jamc.2010040103 ◽

2010 ◽

Vol 1 (2) ◽

pp. 34-49 ◽

Cited By ~ 1

Author(s):

Ahmed Mellouli ◽

Faouzi Masmoudi ◽

Imed Kacem ◽

Mohamed Haddar

Keyword(s):

Genetic Algorithm ◽

Linear Programming ◽

Production Cost ◽

Programming Model ◽

Hybrid Genetic Algorithm ◽

Cutting Stock Problem ◽

Cutting Stock ◽

Two Dimensional ◽

Genetic Approach ◽

Cutting Pattern

In this paper, the authors present a hybrid genetic approach for the two-dimensional rectangular guillotine oriented cutting-stock problem. In this method, the genetic algorithm is used to select a set of cutting patterns while the linear programming model permits one to create the lengths to produce with each cutting pattern to fulfil the customer orders with minimal production cost. The effectiveness of the hybrid genetic approach has been evaluated through a set of instances which are both randomly generated and collected from the literature.

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An Innovative Genetic Algorithm for a Multi-Objective Optimization of Two-Dimensional Cutting-Stock Problem

Applied Artificial Intelligence ◽

10.1080/08839514.2019.1583857 ◽

2019 ◽

Vol 33 (6) ◽

pp. 531-547 ◽

Cited By ~ 2

Author(s):

Ahmed Mellouli ◽

Racem Mellouli ◽

Faouzi Masmoudi

Keyword(s):

Genetic Algorithm ◽

Cutting Stock Problem ◽

Cutting Stock ◽

Two Dimensional ◽

Multi Objective Optimization ◽

Multi Objective

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3-Phase Matheuristic Model in Two-Dimensional Cutting Stock Problem of Triangular Shape Items

Science & Technology Indonesia ◽

10.26554/sti.2020.5.1.23-27 ◽

2020 ◽

Vol 5 (1) ◽

pp. 23

Author(s):

Putra Bahtera Jaya Bangun ◽

Sisca Octarina ◽

Sisca Puspita Sepriliani ◽

Laila Hanum ◽

Endro Sastro Cahyono

Keyword(s):

Branch And Bound ◽

Consumer Demand ◽

Cutting Stock Problem ◽

Cutting Stock ◽

Two Dimensional ◽

Triangular Shape ◽

Optimum Cutting ◽

Trim Loss ◽

Cutting Pattern ◽

Optimum Solution

Cutting Stock Problem (CSP) is a problem of cutting stocks with certain cutting rules. This study used the data of rectangular stocks, which cut into triangular shape items with various order sizes. The Modified Branch and Bound Algorithm (MBBA) was used to determine the optimum cutting pattern then formulated it into the 3-Phase Matheuristic model which consisted of constructive phase, improvement phase, and compaction phase. Based on the results, it showed that the MBBA produces three optimum cutting patterns, which was used six times, eight times, and four times respectively to fulfill the consumer demand. Then the cutting patterns were formulated into the 3-Phase Matheuristic model whereas the optimum solution was the minimum trim loss for the first, second and third patterns.

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