Mathematical models and decomposition algorithms for cutting and packing problems

Delorme, Maxence

doi:10.1007/s10288-017-0365-z

Cited by 3 publications

(3 citation statements)

References 210 publications

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“…Naturally, the last few years have also seen numerous papers trying to find solutions in the field by using different techniques. In the dissertation [17], relying on data obtained from Google Scholar, Scopus and Web of Science, one can see an upward trend in the number of these papers in the 2011-2016 period. Generally, the papers can be grouped in different ways, e.g., according to the CLP type they are addressing (IIPP, SLOPP, MILOPP, MHLOPP, SKP or MIKP), outlined in Section 2.2.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of a Novel Freight Railcar Load Planning and Monitoring System

et al. 2019

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Rail transport has unmistakable sustainable (environmental and economic) advantages in goods transportation on a massive scale. Goods loading constitutes an important segment of goods transportation by rail. Incorrect loading can be a serious threat to traffic safety as well as a generator of unforeseen expenses related to goods, railway infrastructure and vehicles. At the beginning, the paper identifies the presence of incorrect loading into freight railcars. The analysis of the available loading software has led to the conclusion that no software offers adequate support to the planning and monitoring of the loading of goods into a covered railcar using a forklift truck. For this reason, the main aim of the research is to formulate a mathematical model that includes real-world constraints, as well as the design and implementation of an original user-friendly load planning and monitoring software system. Experimental evaluations of the implemented software have been made based on single and multiple railcar pallet loading problems, considering the following three optimization criteria: maximization of wagon load weight, maximization of wagon volume utilization and maximization of weighted profit. By testing the optimization and visualization features of the software and analyzing the results, it has been concluded that it can offer full support to real load planning and monitoring problems.

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Section: Literature Reviewmentioning

confidence: 99%

Development of a Novel Freight Railcar Load Planning and Monitoring System

et al. 2019

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“…The rapid development of space technology and industrialization has put forward new goals for spacecraft design, including shortening the design cycle, reducing development cost and ensuring design reliability. The spacecraft equipment layout optimization design (SELOD) is a vital part of the overall spacecraft design [1][2][3], which refers to the study of how to make full use of the limited space of the spacecraft and arrange instruments and equipment optimally under the premise of satisfying the engineering and technical conditions and various constraints of the internal and surrounding environment. It requires the integrated use of multidisciplinary knowledge [4,5] like aerospace, mechanics, graphics, and geometry.…”

Section: Introductionmentioning

confidence: 99%

A Spacecraft Equipment Layout Optimization Method for Diverse and Competitive Design

Zhao¹,

Du²,

Huo³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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The spacecra equipment layout optimization design (SELOD) problems with complicated performance constraints and diversity are studied in this paper. The previous literature uses the gradient-based algorithm to obtain optimized non-overlap layout schemes from randomly initialized cases e ectively. However, these local optimal solutions are too di cult to jump out of their current relative geometry relationships, signi cantly limiting their further improvement in performance indicators. Therefore, considering the geometric diversity of layout schemes is put forward to alleviate this limitation. First, similarity measures, including modi ed cosine similarity and gaussian kernel function similarity, are introduced into the layout optimization process. Then the optimization produces a set of feasible layout candidates with the most remarkable di erence in geometric distribution and the most representative schemes are sampled. Finally, these feasible geometric solutions are used as initial solutions to optimize the physical performance indicators of the spacecra , and diversi ed layout schemes of spacecra equipment are generated for the engineering practice. The validity and e ectiveness of the proposed methodology are demonstrated by two SELOD applications.

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“…CSP solution solves many real life problems in mass production industries such as steel, wood, glass, paper, textiles, and others (Yan Chen, Xiang Song, Djamila Ouelhadj, 2017) (Ogunranti & Oluleye, 2016). There are one-, two-, three-, and multi-dimensional CSP (Delorme, 2017). Several other variations like with and without contiguity gives more variety of CSP solutions.…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm Approach for Cutting Stock Problems in Construction Industries

Bambang Santoso,

Heri Haerudin

2023

IJIS

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Cutting Stock Problem (CSP) is a classic problem involving cutting long stocks into smaller products with certain quantities. The optimization is to find cutting patterns with minimum waste. In construction industries, CSP applies to steel bar cutting. The steel bar is an important element in making reinforced concrete. The length of the steel bars from the steel manufacturers is fixed, while the requirements for the constructions are varying. The problem is to find optimized way to cut long, fixed-length steel bars into smaller, varying length bars required in the constructions. The requirements are different from building to building, both in the lengths and quantities. Many studies have been extensively done on the subject, from Brute Force, Greedy Search to Linear Programming. In this paper the study focuses on Genetic Algorithm approach. The results look promising for Fitness Function 1 where the focus is to minimize waste. Waste ranges from 2.03% to 4.31%. Fitness function 2 and 3 do not emphasize merely on minimizing the waste, but also on contiguity. Therefore the residues are more, ranges from 2.21% to 4.91% for Fitness Function 2 and from 2.03% to 30.7% for Fitness Function 3

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Mathematical models and decomposition algorithms for cutting and packing problems

Cited by 3 publications

References 210 publications

Development of a Novel Freight Railcar Load Planning and Monitoring System

Development of a Novel Freight Railcar Load Planning and Monitoring System

A Spacecraft Equipment Layout Optimization Method for Diverse and Competitive Design

Genetic Algorithm Approach for Cutting Stock Problems in Construction Industries

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