Maximizing availability for task scheduling in on‐demand computing–based transaction processing system using ant colony optimization

Mahato, Dharmendra Prasad; Singh, Ravi Shankar

doi:10.1002/cpe.4405

Cited by 14 publications

(4 citation statements)

References 71 publications

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“…Energy is essential for the improvement of human beings and society as a whole. With the continuous improvement of social economy, the energy supply is far insufficient for the needs of the society [3]. Due to the scarcity of energy, human needs cannot be endless, which is contrary to the theory of sustainable improvement.…”

Section: Research Background and Significancementioning

confidence: 94%

Energy Efficiency Calculation Based on Ant Colony Algorithm

2020

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The energy issue has always been the focus of attention of the international community. On the one hand, it is due to the limited and scarcity of energy, and on the other hand, energy is of great significance to the sustainable improvement of human society. In this context, as an important economic improvement area in China, the exploration of energy efficiency is of great significance for accelerating the realization of sustainable economic improvement in the future. The purpose of this paper is to calculate the energy efficiency based on the ant colony algorithm. Using the ant colony algorithm and the stochastic frontier model, the results based on the common frontier model, the results of the subregional frontier model and the empirical results of the input of classified energy elements are respectively carried out in the experiments.

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Section: Research Background and Significancementioning

confidence: 94%

Energy Efficiency Calculation Based on Ant Colony Algorithm

2020

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“…The exact approach can locate the exact solution to a problem, but it requires extensive computation. Moreover, as the size of the problem increases, the solution computation becomes more timeconsuming and complex (Bräysy & Gendreau, 2005;Mahato & Singh, 2018). In recent years, metaheuristic algorithm was widely used for optimizing the design of green supply chain networks.…”

Section: Introductionmentioning

confidence: 99%

Municipal Solid Waste Collection and Transportation Routing Optimization Based on Iac-Sfla

Hu,

Ju,

Peng

et al. 2024

Journal of Environmental Engineering and Landscape Management

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In order to realize the efficient collection and low-carbon transport of municipal garbage and accelerate the realize the “dual-carbon” goal for urban transport system, based on the modeling and solving method of vehicle routing problem, the municipal solid waste (MSW) collection and transport routing optimization of an Improved Ant Colony-Shuffled Frog Leaping Algorithm (IAC-SFLA) is proposed. In this study, IAC-SFLA routing Optimization model with the goal of optimization collection distance, average loading rate, number of collections, and average number of stations is constructed. Based on the example data of garbage collection and transport in southern Baohe District, the comparative analysis with single-vehicle models, multiple-vehicle models, and basic ant colony algorithms. The multi-vehicle model of collection and transportation is superior to the single-vehicle model and the improved ant colony algorithm yields a total collection distance that is 19.76 km shorter and an average loading rate that rises by 4.15% from 93.95% to 98.1%. Finally, the improved ant colony algorithm solves for the domestic waste collection and transportation path planning problem in the north district of Baohe. Thus, the effectiveness and application of the proposed algorithm is verified. The research result can provide reference for vehicle routing in the actual collection and transport process, improve collection and transport efficiency, and achieve the goal of energy conservation and emission reduction.

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“…Whether the non-cooperative strategic behavior of product competition is proposed as a technical trade barrier depends on the degree of damage or threat of damage to the market power of the importing country's enterprises 3,4 . Therefore, in theory, it is completely possible to give an early warning of possible technical barriers to trade by establishing an early warning system for technical trade barriers 5 .…”

Section: Introductionmentioning

confidence: 99%

Ant colony optimization algorithm in the design of international trade early warning system

Li¹

2023

International Conference on Computer Application and Information Security (ICCAIS 2022)

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Establishing and improving a scientific system and a system that fully extracts and utilizes commercial data plays an extremely important role in promoting the normal development of China’s foreign trade and maintaining the fundamental interests of the country and the industry. This paper aims to design an early warning system for international trade based on ant colony optimization algorithm. A method of dividing the optimized weights and thresholds into small sets is proposed for the optimization algorithm. The early warning indicator system, early warning model and early warning system construction of TBT are introduced in detail, and the design of TBT early warning system is described and demonstrated in detail. In the verification part, the algorithm after ant colony optimization is compared with the ordinary BP network before the improvement, and it is found that the error of the improved method is smaller, which shows the superiority of the algorithm in solving the problem of international trade early warning.

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Maximizing availability for task scheduling in on‐demand computing–based transaction processing system using ant colony optimization

Cited by 14 publications

References 71 publications

Energy Efficiency Calculation Based on Ant Colony Algorithm

Energy Efficiency Calculation Based on Ant Colony Algorithm

Municipal Solid Waste Collection and Transportation Routing Optimization Based on Iac-Sfla

Ant colony optimization algorithm in the design of international trade early warning system

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