Article
Computer Science, Information Systems
Fadl Dahan
Summary: In this study, an efficient agent-based ant colony optimization (ACO) algorithm is introduced to solve the cloud service composition problem, which aims to meet the complex and challenging requirements of enterprises/users in a cloud environment. The computational results demonstrate the effectiveness of the multi-agent ACO approach across 25 real datasets, showing competitiveness with state-of-the-art algorithms in literature comparisons.
Article
Automation & Control Systems
Serap Ercan Comert, Harun Resit Yazgan
Summary: This paper introduces three multi-objective electric vehicle routing problems that consider different charging strategies and electric vehicle charger types while optimizing five conflicting objectives. A new hierarchical approach consisting of Hybrid Ant Colony Optimization (HACO) and Artificial Bee Colony Algorithm (ABCA) is developed to solve these problems. The proposed approach is examined on test-based instances and achieves the best new results in most cases.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Yaping Zhang, Xu Chen, Danjv Lv, Yan Zhang
Summary: A new land use search and exchange strategy is proposed in this paper to mitigate the adverse impacts of the urban heat effect. The method, applied to a case study in Kunming, China, effectively reduces the average surface temperature of the city core area, providing a basis for sustainable urban planning and design.
APPLIED SOFT COMPUTING
(2021)
Article
Energy & Fuels
Adarsh Kumar Arya
Summary: This paper discusses the use of ant colony optimization strategy to minimize the operating costs of a natural gas pipeline grid. The study constructs a multi-objective modeling framework based on data from a French gas pipeline network corporation, focusing on reducing fuel usage in compressors and increasing throughput at distribution centers. The approach aims to guide pipeline managers in selecting the most preferred solutions by providing the optimum solution for each fuel consumption level at each compressor through a Pareto front analysis.
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
(2021)
Article
Thermodynamics
Bin Sun, Zhenbiao Hu, Xiaojiang Liu, Zhao-Dong Xu, Dajun Xu
Summary: We have developed a physical model-free ant colony optimization network algorithm to predict the ceiling temperature distribution and maximal ceiling temperature in tunnel fires. Experimental results have shown the effectiveness and superiority of the algorithm, making it suitable for rapid fire disaster evaluation.
INTERNATIONAL JOURNAL OF THERMAL SCIENCES
(2022)
Article
Optics
Dan Liu, Xiulian Hu, Qi Jiang
Summary: This paper combines the improved ant colony algorithm to study the logistics distribution path design and optimization. The fusion of genetic algorithm and improved ant colony algorithm transforms the path optimal solution into the initial distribution of pheromone, and the mutation operator expands the search space and accelerates the convergence to the optimal solution. The logistics distribution route optimization design and optimization method based on the improved ant colony algorithm proposed in this paper has good results.
Article
Biotechnology & Applied Microbiology
Kangjing Shi, Li Huang, Du Jiang, Ying Sun, Xiliang Tong, Yuanming Xie, Zifan Fang
Summary: This article proposes an improved genetic and ant colony hybrid algorithm to address the problem of unsmooth path planning for intelligent vehicles. By improving the heuristic function in the ant colony optimization algorithm and making adaptations to the fitness function, crossover factor, mutation factor, and other aspects of the genetic algorithm, the improved hybrid algorithm achieves optimized new populations. Simulation and physical experiments demonstrate the effectiveness of the improved hybrid algorithm, reducing the average number of turns in simple and complex grids.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Environmental Sciences
Ravinder Bhavya, Kaveri Sivaraj, Lakshmanan Elango
Summary: The quality of groundwater is crucial for human health and the environment, especially as it is the main source of drinking water in many parts of the world. Traditional water-quality monitoring methods are expensive and time-consuming, but data-driven models using artificial intelligence offer a more efficient way to predict groundwater quality. This study aims to build an optimized neural network using ant colony optimization and artificial neural network techniques for predicting groundwater quality parameters.
Article
Computer Science, Artificial Intelligence
Sheng Gao, Jiazheng Wu, Jianliang Ai
Summary: The study introduces a novel mathematical model and heuristic algorithm for the multiple UAV reconnaissance task allocation problem, which classifies targets into different types. The new algorithm outperforms existing methods in terms of optimality of results, especially with the scale of the reconnaissance task allocation problem expanding.
Article
Computer Science, Interdisciplinary Applications
Eunseo Oh, Hyunsoo Lee
Summary: This study combines existing metaheuristic algorithms with a prediction method to solve the path planning problem. By modifying the ant colony optimization algorithm and using predicted pheromone traits, the efficiency of the algorithm is improved.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Multidisciplinary
Sihao Li, Tian Gao, Zhipeng Ye, Yaxing Wang
Summary: A mobile ad hoc network is a complex distributed system organized by mobile terminals or wireless nodes through wireless connections, where nodes can move and maintain connections when connecting or leaving. Routing technology is crucial in wireless networks, especially in a dynamic network like a mobile ad hoc network.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Engineering, Civil
Juan Cheng
Summary: Dynamic path optimization is crucial in intelligent transportation systems, and this study proposes an improved ant colony algorithm to achieve this goal. The influencing factors of the multiobjective planning model are determined through investigation and analysis. The algorithm is enhanced by using the analytic hierarchy process (AHP) to calculate the comprehensive weight of path length, travel time, and traffic flow. Directional guidance and dynamic optimization are also incorporated. The experimental results show that the improved ant colony algorithm outperforms the basic ant colony algorithm and the spatial shortest distance algorithm, providing more accurate and effective optimal paths.
JOURNAL OF ADVANCED TRANSPORTATION
(2023)
Article
Engineering, Multidisciplinary
Feng Wu
Summary: In the context of normalization of the epidemic, contactless delivery has become a major research area. This paper proposes a contactless distribution path optimization algorithm based on an improved ant colony algorithm, which analyzes traffic factors and customer satisfaction in the epidemic environment, and improves efficiency and user satisfaction. Through simulation optimization and comparative analysis, the effectiveness of the proposed model and algorithm is verified.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2021)
Article
Computer Science, Information Systems
Yuanyuan Wei, Nan Jiang, Ziwei Li, Dongdong Zheng, Minjie Chen, Miaomiao Zhang
Summary: This article proposes a public transportation network optimization method based on an ant colony optimization algorithm coupled with existing routes, which increases the rationality and practical feasibility of the new bus-line structure.
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
(2022)
Article
Engineering, Chemical
Leonardo Gomez-Coronel, Jorge Alejandro Delgado-Aguinaga, Ildeberto Santos-Ruiz, Adrian Navarro-Diaz
Summary: This paper proposes a methodology using genetic algorithms (GA) to calibrate the parameters of a chlorine decay model in a water distribution system (WDS). The methodology first uses historical measurements to calibrate the reaction coefficients and then predicts the chlorine concentration decay at each node using the optimal-fit decay model. A second GA-based algorithm is used to optimize the required chlorine concentration at the input to meet normativity requirements. The proposed methodology performed well in the simulated WDS.