Solving two-dimensional cutting stock problem via a DNA computing algorithm

Dodge, Martin; MirHassani, S. A.; Hooshmand, F.

doi:10.1007/s11047-020-09786-3

Cited by 9 publications

(4 citation statements)

References 32 publications

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“…The first of these processes is the enzyme mutation, which is the process of deleting any DNA sequences randomly selected from the DNA sequence. The second is a virus mutation, which involves replacing a randomly deleted DNA sequence with a newly produced DNA sequence (Dodge et al 2020).…”

Section: The Dna Computing Algorithmmentioning

confidence: 99%

The Optimization of Routes Using Evolutionary Algorithms in Public Transportation Systems

Kaleli¹,

Bayğın²,

Naralan³

2022

Journal of Intelligent Systems: Theory and Applications

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This study aims to examine, regulate, and update the land transportation of the Erzurum Metropolitan Municipality (EMM), Turkey using computerized calculation techniques. In line with these targets, some critical information has been obtained for study: the number of buses, the number of expeditions, the number of bus lines, and the number and maps of existing routes belonging to EMM. By using the information that has been obtained, this study aims at outlining specific outputs according to the input parameters, such as determining the optimal routes, the average travel, and the journey time. Once all of these situations were considered, various optimization algorithms were used to get the targeted outputs in response to the determined input parameters. In addition, the study found that the problem involved in modeling the land transport network of the EMM is in line with the so-called "traveling salesman problem," which is a scenario about optimization often discussed in the literature. This study tried to solve this problem by using the genetic algorithm, the clonal selection algorithm, and the DNA computing algorithm. The location data for each bus stops on the bus lines selected for the study were obtained from the EMM, and the distances between these coordinates were obtained by using Google Maps via a Google API. These distances were stored in a distance matrix file and used as input parameters in the application and then were put through optimization algorithms developed initially on the MATLAB platform. The study's results show that the algorithms developed for the proposed approaches work efficiently and that the distances for the selected bus lines can be shortened.

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Section: The Dna Computing Algorithmmentioning

confidence: 99%

The Optimization of Routes Using Evolutionary Algorithms in Public Transportation Systems

Kaleli¹,

Bayğın²,

Naralan³

2022

Journal of Intelligent Systems: Theory and Applications

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“…Theoretically, the two-dimensional cutting stock problem (CSP) is NP-hard problem (Dodge, 2020). The m2DLCSP considers useable leftovers in consecutive orders is also NP-hard with more EC 39,2 complex combinatorial conditions.…”

Section: Literature Reviewmentioning

confidence: 99%

Manufacturing-oriented silicon steel coil lengthwise cutting stock problem with useable leftover

Yan

2021

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PurposeThis paper propose an algorithm for the multiple silicon steel coils multiperiod two-dimensional lengthwise cutting stock problem (m2DLCSP), so as to minimize the total cost of materials and production.Design/methodology/approachThe authors propose a sequential leftovers utilization correction (SLUC) algorithm for the m2DLCSP. The algorithm primarily considers three optimization strategies. First, it considers usable leftovers to simplify the cutting process and improve material utilization. The total quantity and types of leftovers should be limited in order to avoid leftover overstock. Second, it uses a splice method of items to improve the generated cutting plan. Third, it takes into account operational restrictions in the cutting operations. Operational restrictions include imposing maximum and minimum lengths on the cutting patterns, and the limitation of cutting knives at the slitting machines.FindingsSeveral sets of benchmark with real-world and randomly generated instances are provided to evaluate the algorithm. Compared with literature algorithm and current procedure applied in enterprises, the computational results indicate that proposed algorithm can effectively reduce the total cost, and the computation time is reasonable for practical use.Social implicationsThis algorithm can effectively reduce the total cost.Originality/valueThe proposed method can effectively applied to solve the m2DLCSP and improve the economic efficiency of enterprises.

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“…An algorithm based on DNA self assembly for minimum spanning tree problem was presented in [38]. Some other achievements in the area of solving mathematical problems using DNA molecules can be found in [8,28,16,3,4,9,29,34].…”

Section: Introductionmentioning

confidence: 99%

A DNA Algorithm for Calculating the Maximum Flow of a Network

Sackmann,

Brown,

Formanowicz

et al. 2023

Foundations of Computing and Decision Sciences

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DNA computing is a highly interdisciplinary field which combines molecular operations with theoretical algorithm design. A number of algorithms have been demonstrated in DNA computing, but to date network flow problems have not been studied. We aim to provide an approach to calculate the value of the maximum flow in networks by encoding the mathematical problem in DNA molecules and by using molecular biology techniques to manipulate the DNA. We present results which demonstrate that the algorithm works for an example network problem. This paper presents the first application of DNA computing to network-flow problems. The presented algorithm has a linear time complexity where the calculation itself is done in a constant number of steps.

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Solving two-dimensional cutting stock problem via a DNA computing algorithm

Cited by 9 publications

References 32 publications

The Optimization of Routes Using Evolutionary Algorithms in Public Transportation Systems

The Optimization of Routes Using Evolutionary Algorithms in Public Transportation Systems

Manufacturing-oriented silicon steel coil lengthwise cutting stock problem with useable leftover

A DNA Algorithm for Calculating the Maximum Flow of a Network

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