Simple heuristic for the constrained two-dimensional cutting problem

Cui, Yi-Ping; Chen, Q

doi:10.1177/0954405411421996

Cited by 11 publications

(13 citation statements)

References 17 publications

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“…Their method optimally solved previously unsolved literature instances. Cui (2012) and Cui and Chen (2012) developed a heuristic with extended block cutting schemes based on dynamic programming. Contrary to Chen (2008), homogeneous strips of equivalent pieces are considered instead of single pieces, as previously described in Section 2.1.…”

Section: Heuristic and Metaheuristic Approachesmentioning

confidence: 99%

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Constrained two‐dimensional guillotine cutting problem: upper‐bound review and categorization

Russo¹,

Boccia

Sforza³

et al. 2019

Int Trans Operational Res

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In the two‐dimensional (2D) cutting (2DC) problem, a large rectangular sheet has to be dissected into smaller rectangular pieces with the aim of maximizing the total profit associated with the extracted pieces. When the number of copies of each piece to be extracted is bounded, it is referred to as constrained 2DC (C2DC) problem. The C2DC has been widely studied by the operations research community for its applications and theoretical issues. In this work, we recall the best exact and heuristic solving approaches for the C2DC and we provide a review and a categorization of the available upper bounds. We also discuss improvements and combinations of these upper bounds and give directions for their effective exploitation. Finally, we demonstrate the loss of accuracy of several exact methods present in literature because of the effect of the used antiredundancy strategies on the implemented bounding criteria. This work, based on more than 90 contributions, has a twofold target. For researchers working in C2DC, it provides a useful insight on the topic. For expert practitioners, it represents a systematic collection of the main findings and achievements, posing also the basis for future research.

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Section: Heuristic and Metaheuristic Approachesmentioning

confidence: 99%

“…This strategy, based on relation , is similar to the ones used in the heuristics of León et al. () and Cui and Chen (). In particular, in the first contribution, just one pattern B ( l , w ) is recorded for each rectangle ( l , w ).…”

Section: C2dc Solving Approaches and Literature Reviewmentioning

confidence: 99%

Constrained two‐dimensional guillotine cutting problem: upper‐bound review and categorization

Russo¹,

Boccia

Sforza³

et al. 2019

Int Trans Operational Res

View full text Add to dashboard Cite

show abstract

“…An overall cutting plan is obtained for the current problem. Cui and Chen 6 also proposed a simple heuristic algorithm to maximize the pattern value with the constraint that the number produced of a piece cannot exceed the demand for that piece.…”

Section: Literature Reviewmentioning

confidence: 99%

A balance approach for the one-dimensional multiple stock size cutting stock problem with setup cost

Yan

2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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A balance approach is presented to solve one-dimensional multiple stock size cutting stock problem with setup cost. The approach first utilizes a sequential pattern generation algorithm to generate a series of cutting plans based on each stock size, respectively. Then, a measure standard of cost balance utilization is used to select a current optimized cutting pattern from a cutting plan corresponding to each stock size. All item demands are dealt by the previous two steps to obtain many optimized cutting plans, and an ideal cutting plan is extracted according to the minimum sum of stock and setup costs at last. The approach is applied to two tests, and the computational results demonstrate that it possesses good cost adaptability and optimization performance.

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“…Many algorithms and approaches are used to address the cutting-stock problem, including conventional optimization algorithms and various metaheuristic algorithms. For instance, Gomes, 1 Song and Bennell, 2 Bennell et al, 3 Cui and Chen, 4 Xie et al, 5 and others proposed some nesting algorithms and offered some suggestions regarding the two-dimensional cutting-stock problem. There are some articles concerning the combined cutting-stock and lot-sizing problems.…”

Section: Introductionmentioning

confidence: 99%

An improved hierarchical genetic algorithm for collaborative optimization of manufacturing processes in metal structure manufacturing systems

Zhang

Liu

et al. 2017

Advances in Mechanical Engineering

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The multi-objective optimization problem includes plate nesting, production planning, scheduling, and equipment capacity optimization in the complex manufacturing process of metal structures. For the best optimization results, a global collaborative optimization of the manufacturing system is necessary. A multi-objective optimization model for optimized nesting, optimized scheduling, dispatch optimizing, and equipment load balancing is constructed, and an improved hierarchical genetic algorithm is then developed for a better solution. A hierarchical structure of three chromosomes is designed in this algorithm. The algorithm can be used to simultaneously solve the layout selection, process sequencing, and machine selection problems. The algorithm shortens the production cycle, reduces the number of work in process, and improves equipment utilization through the application of collaborative optimization. The computational result and comparison prove that the presented approach is quite effective to address the considered problem.

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Simple heuristic for the constrained two-dimensional cutting problem

Cited by 11 publications

References 17 publications

Constrained two‐dimensional guillotine cutting problem: upper‐bound review and categorization

Constrained two‐dimensional guillotine cutting problem: upper‐bound review and categorization

A balance approach for the one-dimensional multiple stock size cutting stock problem with setup cost

An improved hierarchical genetic algorithm for collaborative optimization of manufacturing processes in metal structure manufacturing systems

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