An integrated algorithm for cutting stock problems in the thin-film transistor liquid crystal display industry

Lu, Hao-Chun; Huang, Yao‐Huei; Tseng, Kuo-An

doi:10.1016/j.cie.2013.02.009

Cited by 11 publications

(4 citation statements)

References 32 publications

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“…Karaca et al proposed the DA for the pattern generation procedure, stating that, unlike the CSP, metaheuristics are under-utilized in the SSP realm. Well-known metaheuristics in this area are Tabu search [29], simulated annealing (SA) [30][31][32], ant colony optimization (ACO) [33], and its variants or hybridizations [34], genetic algorithm [35][36][37], genetic symbiotic algorithm [38], evolutionary programming (EP) [39], and hybrid chemical reaction optimization (CRO) [40].…”

Section: Literature Reviewmentioning

confidence: 99%

A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process

Karaca,

Samanlioglu,

Altay

2023

Applied Computational Intelligence and Soft Computing

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The stochastic skiving stock problem (SSP), a relatively new combinatorial optimization problem, is considered in this paper. The conventional SSP seeks to determine the optimum structure that skives small pieces of different sizes side by side to form as many large items (products) as possible that meet a desired width. This study studies a multiproduct case for the SSP under uncertain demand and waste rate, including products of different widths. This stochastic version of the SSP considers a random demand for each product and a random waste rate during production. A two-stage stochastic programming approach with a recourse action is implemented to study this stochastic N P -hard problem on a large scale. Furthermore, the problem is solved in two phases. In the first phase, the dragonfly algorithm constructs minimal patterns that serve as an input for the next phase. The second phase performs sample-average approximation, solving the stochastic production problem. Results indicate that the two-phase heuristic approach is highly efficient regarding computational run time and provides robust solutions with an optimality gap of 0.3% for the worst-case scenario. In addition, we also compare the performance of the dragonfly algorithm (DA) to the particle swarm optimization (PSO) for pattern generation. Benchmarks indicate that the DA produces more robust minimal pattern sets as the tightness of the problem increases.

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Section: Literature Reviewmentioning

confidence: 99%

A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process

Karaca,

Samanlioglu,

Altay

2023

Applied Computational Intelligence and Soft Computing

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“…Constraints (18) ensure that the length of the item should not exceed that of the block. Constraints (19) ensure that the width of the item should not exceed that of the block. Constraints (20) ensure that the height of the item should not exceed that of the block.…”

Section: Fig 1 Cut Blocks Of a Tunnelmentioning

confidence: 99%

“…Some works in the literature have been devoted to industrial cases studies such as [19] for cutting stock problems in the thin-film transistor liquid crystal display industry and [20], who propose a beam search algorithm, a greedy algorithm and a tree search enumeration algorithm to solve a packing problem in a major automobile manufacturer in Turkey.…”

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confidence: 99%

A Mathematical formulation and a lower bound for the three-dimensional multiple-bin-size bin packing problem (MBSBPP): A Tunisian industrial case

Baazaoui

Hanafi

Kamoun

2014

2014 International Conference on Control, Decision and Information Technologies (CoDIT)

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In our research, we are interested in the three-dimensional multiple-bin-size bin packing problem (MBSBPP). We deal with the real word application of cutting mousse blocks proposed by a Tunisian industrial company. First, we present the general context related to our optimization problem. Second we formulate it as a mathematical problem without considering the guillotine constraint, and then we tested it on small instances taken from the industry. Thereafter, we propose and test a lower bound for large instances from the same industrial company. Finally, some computational results are presented.

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“…In the 2DCSP, a set of given rectangular items is cut from a set of rectangular materials with the aim of determining the minimum number of materials [1,2]. These applications include sawing plates from wood stocks [3], reel and sheet cutting at a paper mill [4], cutting plates of thin-film-transistor liquidcrystal display (TFT-LCD) from glass substrate [5,6], placing devices into a system-on-a-chip circuit [7], and container loading or calculation of containers [8,9]. Minimizing the number of materials is normally the target in this type of the problem because it does not only reduce the overhead consumption but also enhances environmental protection.…”

Section: Introductionmentioning

confidence: 99%

A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

Huang¹,

Lu²,

Wang³

et al. 2020

Application of Decision Science in Business and Management

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A two-dimensional cutting stock problem (2DCSP) needs to cut a set of given rectangular items from standard-sized rectangular materials with the objective of minimizing the number of materials used. This problem frequently arises in different manufacturing industries such as glass, wood, paper, plastic, etc. However, the current literatures lack a deterministic method for solving the 2DCSP. However, this study proposes a global method to solve the 2DCSP. It aims to reduce the number of binary variables for the proposed model to speed up the solving time and obtain the optimal solution. Our experiments demonstrate that the proposed method is superior to current reference methods for solving the 2DCSP.

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An integrated algorithm for cutting stock problems in the thin-film transistor liquid crystal display industry

Cited by 11 publications

References 32 publications

A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process

A Two-Phase Pattern Generation and Production Planning Procedure for the Stochastic Skiving Process

A Mathematical formulation and a lower bound for the three-dimensional multiple-bin-size bin packing problem (MBSBPP): A Tunisian industrial case

A Global Method for a Two-Dimensional Cutting Stock Problem in the Manufacturing Industry

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