Combining the ant system algorithm and simulated annealing for 3D/2D fixed-outline floorplanning

Xu, Qi; Chen, Song; Li, Bin

doi:10.1016/j.asoc.2015.10.045

Cited by 24 publications

(8 citation statements)

References 13 publications

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“…In order to be able to optimize them accordingly, an annealing algorithm is used to optimize the implementation of response measures in the execution plan system. The implementation of the program not only enables the implementation of the law, but also finds a balance between the more humane and fair [5].…”

Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Research on the perfection of the countermeasures of the judicial execution scheme in the administrative law system based on annealing algorithm

2019

J Wireless Com Network

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With the continuous development of computer technology and the popularization and application of various types of intelligent algorithms, there are also applications in the current administrative judicial system in China. In order to be able to reasonably realize the fairness of criminal justice activities, the relevant deficiencies in the implementation of the supervision of criminal penalty enforcement are made up. In order to reasonably improve the execution plan, the legal authority of judicial administration is established. The implementation of the judicial enforcement program in the administrative law system is researched based on the annealing algorithm. The optimization of the annealing algorithm is used to optimize the execution of the program flow. The results show that the annealing algorithm can optimize this solution.

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Section: Introductionmentioning

confidence: 99%

RETRACTED ARTICLE: Research on the perfection of the countermeasures of the judicial execution scheme in the administrative law system based on annealing algorithm

2019

J Wireless Com Network

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“…Compared with SMA, adding the annealing operator strengthens the robustness of the algorithm and reduces the probability of the algorithm falling into a local optimal solution during the search process. This method has also been extensively validated in solving problems such as TSP problems and 3D/2D fixed-outline floor planning [ 54 , 55 ].…”

Section: Methodsmentioning

confidence: 99%

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

Zhang

Liu

Bai³

2023

PLoS ONE

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In this article, an improved slime mould algorithm (SMA-CSA) is proposed for solving global optimization and the capacitated vehicle routing problem (CVRP). This improvement is based on the mixed-strategy optimization of Cauchy mutation and simulated annealing to alleviate the lack of global optimization capability of the SMA. By introducing the Cauchy mutation strategy, the optimal solution is perturbed to increase the probability of escaping from the local extreme value; in addition, the annealing strategy is introduced, and the Metropolis sampling criterion is used as the acceptance criterion to expand the global search space to enhance the exploration phase to achieve optimal solutions. The performance of the proposed SMA-CSA algorithm is evaluated using the CEC 2013 benchmark functions and the capacitated vehicle routing problem. In all experiments, SMA-CSA is compared with ten other state-of-the-art metaheuristics. The results are also analyzed by Friedman and the Wilcoxon rank-sum test. The experimental results and statistical tests demonstrate that the SMA-CSA algorithm is very competitive and often superior compared to the algorithms used in the experiments. The results of the proposed algorithm on the capacitated vehicle routing problem demonstrate its efficiency and discrete solving ability.

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“…The SA played the role of a mutation operator in the GA part of the hybrid. In a paper by Xi et al [44] the solutions generated by the ant system were later improved by the SA when solving the 3D/2D fixed-outline floor planning problem. McKendall and Shang [32] used the SA as the LS method in one of their Hybrid Ant System algorithms for solving the dynamic facility layout problem.…”

Section: Related Workmentioning

confidence: 99%

An improved Ant Colony System for the Sequential Ordering Problem

Skinderowicz

2017

Computers & Operations Research

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It is not rare that the performance of one metaheuristic algorithm can be improved by incorporating ideas taken from another. In this article we present how Simulated Annealing (SA) can be used to improve the efficiency of the Ant Colony System (ACS) and Enhanced ACS when solving the Sequential Ordering Problem (SOP). Moreover, we show how the very same ideas can be applied to improve the convergence of a dedicated local search, i.e. the SOP-3-exchange algorithm. A statistical analysis of the proposed algorithms both in terms of finding suitable parameter values and the quality of the generated solutions is presented based on a series of computational experiments conducted on SOP instances from the well-known TSPLIB and SOPLIB2006 repositories. The proposed ACS-SA and EACS-SA algorithms often generate solutions of better quality than the ACS and EACS, respectively. Moreover, the EACS-SA algorithm combined with the proposed SOP-3-exchange-SA local search was able to find 10 new best solutions for the SOP instances from the SOPLIB2006 repository, thus improving the state-of-the-art results as known from the literature. Overall, the best known or improved solutions were found in 41 out of 48 cases.Comment: 30 pages, 8 tables, 11 figure

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Combining the ant system algorithm and simulated annealing for 3D/2D fixed-outline floorplanning

Cited by 24 publications

References 13 publications

RETRACTED ARTICLE: Research on the perfection of the countermeasures of the judicial execution scheme in the administrative law system based on annealing algorithm

RETRACTED ARTICLE: Research on the perfection of the countermeasures of the judicial execution scheme in the administrative law system based on annealing algorithm

Improved slime mould algorithm based on hybrid strategy optimization of Cauchy mutation and simulated annealing

An improved Ant Colony System for the Sequential Ordering Problem

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