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Journal articles on the topic 'Ant colony sytem algorithm'

Author: Grafiati

Published: 5 June 2025

Last updated: 15 July 2025

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1

Suo, Xiang Feng, Yun Hui Gao, and Xue Han. "University Course Arrangement System Based on Improved Ant Colony Algorithm Design." Applied Mechanics and Materials 651-653 (September 2014): 2536–40. http://dx.doi.org/10.4028/www.scientific.net/amm.651-653.2536.

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This paper starts from learning the basic ant colony algorithm, studies the working principle of ant colony algorithm, summarizes the advantages and disadvantages of ant colony algorithm .And it proposed artificial improved ant colony algorithm based on the basic ant colony algorithm, the improved ant colony algorithm is more suitable for the university experimental class course scheduling, and carries on the overall analysis and detailed research on the actual timetabling problem, find out the reasons of conflict prone to course scheduling, according to the actual situation to solve, and fina

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Zhang, Yan, Hui Ling Wang, Xu Li, Yong Hua Zhang, and Hao Wang. "Parallel Ant System Based on OpenMP." Advanced Materials Research 765-767 (September 2013): 658–61. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.658.

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To overcome the limitation of precocity and stagnation in classical ant colony algorithm, this article presents a Parallel Ant System Based on OpenMP. The ant colony is divided into three children ant colonies according to the characteristics of natural ant colony multi-group and pheromone updating features of ant colony algorithm. By Open Multi-Processing parallel programming idea, the parallel and cooperating optimization of children ant colonies was obtained. It organically combines local search and global search, makes full use of computing power of multi-core CPU, and improves the efficie

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Abeer, A. Abdul-Razaq, Karem Nasser Huda, Shakir Hameed Asaad, et al. "Implementation of the enhanced ant colony system algorithm to solve reliable communication network design." Eastern-European Journal of Enterprise Technologies 3, no. 9 (117) (2022): 44–52. https://doi.org/10.15587/1729-4061.2022.259693.

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The problem of communication design has been defined as one of the problems that belong to the category of NP-hard problem, and the aim of the topological communication network design is to identify component placement locations and connectivity aspects. On the other hand, the Reliable Communication Network Design (RCND) is a popular optimization problem used for maximizing network reliability. In addition, finding an accurate calculation of RCND explains the problem of NP-hard problem. To this end, literature studies suggested various metaheuristic algorithms that have been used as approximat

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Yi, Wei. "Research on the Application of Ant Colony Algorithm in University Teaching Management Service System." MATEC Web of Conferences 359 (2022): 01020. http://dx.doi.org/10.1051/matecconf/202235901020.

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The ant colony algorithm is based on the real ant colony foraging behavior research algorithm, based on the ant colony algorithm university teaching management service system, through the development of one-click automatic course scheduling, drag-and-drop Manual course scheduling, the multi-mode, service-oriented perspective to promote college teaching management, greatly improve the efficiency of college teaching management services, fully adapt to the intelligent college teaching management environment. Based on the ant colony algorithm, this paper analyzes the background of the application

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Jing, Lu. "Optimization Simulation of English Speech RecognitionAccuracy Based on Improved Ant Colony Algorithm." Complexity 2020 (November 6, 2020): 1–10. http://dx.doi.org/10.1155/2020/8858399.

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This paper is aimed at the problems of low accuracy, long recognition time, and low recognition efficiency in English speech recognition. In order to improve the accuracy and efficiency of English speech recognition, an improved ant colony algorithm is used to deal with the dynamic time planning problem. The core is to adopt an adaptive volatilization coefficient and dynamic pheromone update strategy for the basic ant colony algorithm. Using new state transition rules and optimal ant parameter selection and other improved methods, the best path can be found in a shorter time and the execution

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Cui, Shi Gang, Jiang Lei Dong, and Fan Liang. "The Mixing Algorithm of ACO and GA Based Global Path Planning Method for Mobile Robot." Applied Mechanics and Materials 494-495 (February 2014): 1290–93. http://dx.doi.org/10.4028/www.scientific.net/amm.494-495.1290.

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An ant colony algorithm is a stochastic searching optimization algorithm that is based on the heuristic behavior of the biologic colony. Its positive feedback and coordination make it possible to be applied to a distributed system. It has favorable adaptability in solving combinatorial optimization and has great development potential for its connotative parallel property. This study focused on global path planning with an ant colony algorithm in an environment based on grids, which explores a new path planning algorithm. How to present and update the pheromone of an ant system was investigated

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Du, Guotai, Hongkui Ma, Yu Bai, and Ning Mei. "Process Planning for Large Container Ship Propeller Shaft Machining Based on an Improved Ant Colony Algorithm." Journal of Marine Science and Engineering 12, no. 5 (2024): 841. http://dx.doi.org/10.3390/jmse12050841.

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To accommodate the production and manufacture of complex and customized marine components and to avoid the empirical nature of process planning, machining operations can be automatically sequenced and optimized using ant colony algorithms. However, traditional ant colony algorithms exhibit issues in the context of machining process planning. In this study, an improved ant colony algorithm is proposed to address these challenges. The introduction of a tiered distribution of initial pheromones mitigates the blindness of initial searches. By incorporating the number of iterations into the expecta

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8

Wu, Shaofei. "Study on an improved algorithm for optimization of PID parameters." International Journal of Online Engineering (iJOE) 12, no. 02 (2016): 58. http://dx.doi.org/10.3991/ijoe.v12i02.5050.

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The improved ant colony algorithm is the hybrid algorithm consisting of the genetic algorithm and ant colony algorithm convergence. Through the introduction of the gauss mutation, we achieve the goal of improving ant colony algorithm. Using coal-fired power plant unit as main steam temperature controlled object, we design the PID controller based on improved ant colony algorithm. And setting of PID parameters by Z - N method has carried on the comparative analysis of the main steam temperature control system. Simulation results show that PID optimization based on improved ant colony algorithm

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Shen, Zhengyang. "Application of ant algorithm in solving TSP problems." Applied and Computational Engineering 48, no. 1 (2024): 232–36. http://dx.doi.org/10.54254/2755-2721/48/20241549.

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Ant colony system algorithms, as a new class of global search algorithms, can solve the TSP (Traveling Salesman Problem). At the same time, the TSP problem is a classical NP-C problem, the solution of TSP problem involves many fields, such as network routing, vehicle routing, logistics and transportation, so it is very important to solve TSP problem effectively. In this experiment, the ant colony optimization algorithm is simulated and experimented using Matlab software on bayg29 dataset and the algorithm strategy is improved by controlling different parameters. Our main goal is to improve the

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10

Liu, Qing Song, Jia Tong, and Yi Feng Li. "Study on the Application of Simulated Evolutionary Optimization Algorithm in Optimizing the Combination of Unit Commitments in Power System." Applied Mechanics and Materials 48-49 (February 2011): 1186–90. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.1186.

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This study adopted a simulated evolutionary optimization algorithm, ant colony optimization algorithm to find the optimal unit commitment operation. The concepts such as status, strategy, and path, etc. were introduced to devise the optimization of unit commitment operation by ant colony optimization algorithm mode, so that the optimal unit commitment operation could be found by ant colony optimization algorithm. To cope with different constraints by additional penalties and restrict the statuses not satisfying the constraints by tabu table, the retrieval of ant colony optimization algorithm c

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11

Bi, Jun, Jie Zhang, and Wen Le Xu. "An Improved Ant Colony Algorithm for the Shortest Path in City’s Road Network." Applied Mechanics and Materials 121-126 (October 2011): 1296–300. http://dx.doi.org/10.4028/www.scientific.net/amm.121-126.1296.

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The shortest path between the start node and end node plays an important role in city’s road traffic network analysis system. The basic ant colony system algorithm which is a novel simulated evolutionary algorithm is studied to solve the shortest path problem. But the basic ant colony system algorithm is easy to run into the local optimum solution for shortest path. In order to solve the problem, the improved ant colony system algorithm is proposed. The improvement methods for selection strategy, local search, and information quantity modification of basic ant colony system are discussed in de

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Yang, Jin Qiu, Jian Gang Yang, and Gen Lang Chen. "An Improved Ant Colony System Based on Negative Biased." Key Engineering Materials 439-440 (June 2010): 558–62. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.558.

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Ant System (AS) was the first Ant Colony Optimization (ACO) algorithm, which converged too slowly and consumed huge computation. Among the variants of AS, Ant Colony System (ACS) was one of the most successful algorithms. But ACS converged so rapidly that it always was in early stagnation. An improved Ant Colony System based on Negative Biased (NBACS) was introduced in the paper to overcome the early stagnation of the ACS. Experiments for Traveling Salesman Problem (TSP) showed that better solutions were obtained at the same time when the convergence rate accelerated more rapidly.

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13

Bukhovtsev, Danil D. "Application of the modified ant colony algorithm for solving the problem of scheduling of distributed enterprises." Modern Innovations, Systems and Technologies 1, no. 1 (2021): 29–42. http://dx.doi.org/10.47813/2782-2818-2021-1-1-29-42.

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The task of scheduling of distributed enterprises is to assign tasks to geographically remote enterprises and to determine a convenient work schedule for each of the enterprises. The goal of solving this problem is to minimize the total production time at all enterprises. This article is the first step towards solving the scheduling problem using different versions of the ant colony algorithm: the classic ant colony algorithm, the ant colony system algorithm, and the modified ant colony algorithm.

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14

Cheng, Cheng, Yuguang Xu, and Graciela Daniels. "Efficient Management and Application of Human Resources Based on Genetic Ant Colony Algorithm." Journal of Sensors 2022 (August 1, 2022): 1–13. http://dx.doi.org/10.1155/2022/9903319.

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With the increasing demand of human resources, the cost of staffing and management is increasing, and it is difficult to dynamically allocate and adjust personnel among different parts. It is the key of intelligent management technology to realize efficient application and mining in human resource management. In the aspect of human resource allocation and management, this paper puts forward the efficient management and application of human resource based on the genetic ant colony algorithm. Firstly, this paper describes the process management and parameter application of the genetic algorithm

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15

Gu, Chonglin, Ansong Feng, Guozhan Wang, and Xiqing Liu. "Robot Path Planning of Improved Adaptive Ant Colony System Algorithm Based on Dijkstra." Journal of Robotics 2022 (December 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/9229155.

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Path planning is one of the key technologies of robot. Aiming at the problems of slow convergence speed and inefficient search of traditional Ant Colony System Algorithm, an adaptive Ant Colony System Algorithm based on Dijkstra is proposed in the paper. Firstly, Dijkstra algorithm is applied to searching the initial path in the grid environment, constructing the initial path, optimizing the initial pheromone in the region, therefore, the Ant Colony System Algorithm avoid falling into blind search in the initial stage; In the transition probability, the disguised angle probability function and

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16

Perepelkin, D. A., M. A. Ivanchikova, and V. T. Nguyen. "Intelligent Multipath Routing in Software Defined Networks Based on Ant Colony Optimization Algorithms." Informacionnye Tehnologii 28, no. 10 (2022): 520–28. http://dx.doi.org/10.17587/it.28.520-528.

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The software defined networks (SDN) are a modern trend in building of new generation computer networks. The SDN provide flexibility and control in management of data flows in the network, as well as requirement level of quality of service for applications. An approach to intelligent multipath routing in SDN based on ant colony optimization algorithms is proposed in this paper. Research and analysis of two types of ant colony optimization algorithms was carried out: ant system (AS) and ant colony system (ACS). The visual software system SDNLoadBalancer was developed and the experimental SDN top

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17

Zhang, Li Hong, and Shu Qian Chen. "Research of Hybrid Mobile Agent Routing in Wireless Sensor Network." Applied Mechanics and Materials 341-342 (July 2013): 1181–86. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.1181.

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The mobile agent route is essentially a multi-constraint optimization problem, Genetic Algorithms has fast random global search ability, but the feedback information of the system does not use and has the problem of low efficiency of finding exact solutions, propose a genetic hybrid ant colony algorithm for WSN mobile agent route. Use of the fast random global search capabilities of genetic algorithm to find better solutions, then the better solution replaced by the initial pheromone of the ant colony algorithm, finally use the advantages of convergence speed of ant colony algorithm to find th

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18

Gülcü, Sevda Dayıoğlu, Şaban Gülcü, and Humar Kahramanli. "Solution of Travelling Salesman Problem Using Ant Colony Algorithm." Applied Mechanics and Materials 548-549 (April 2014): 1206–12. http://dx.doi.org/10.4028/www.scientific.net/amm.548-549.1206.

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Recently some studies have been revealed by inspiring from animals which live as colonies in the nature. Ant Colony System is one of these studies. This system is a meta-heuristic method which has been developed based upon food searching characteristics of the ant colonies. Ant Colony System is applied in a lot of discrete optimization problems such as travelling salesman problem. In this study solving the travelling salesman problem using ant colony system is aimed.

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19

Kim, In-Kyeom, and Min-Young Yun. "A Classification Algorithm Using Ant Colony System." KIPS Transactions:PartB 15B, no. 3 (2008): 245–52. http://dx.doi.org/10.3745/kipstb.2008.15-b.3.245.

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20

AL-Salami, Nada M. A. "System Evolving using Ant Colony Optimization Algorithm." Journal of Computer Science 5, no. 5 (2009): 380–87. http://dx.doi.org/10.3844/jcssp.2009.380.387.

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21

Sinitsyn, I. N., and Yu P. Titov. "Control of Set of System Parameter Values by the Ant Colony Method." Avtomatika i telemehanika, no. 8 (December 15, 2023): 153–68. http://dx.doi.org/10.31857/s000523102308010x.

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The paper considers the modification and application of the ant colony method for the problem of directed enumeration of the values of system parameters when performing calculated multiple calculations. Interaction with the user makes it possible to stop the process of exhaustive enumeration of sets of parameter values, and the application of a modification of the ant colony method will allow us to consider rational sets at early iterations. If the user does not terminate the algorithm, then the proposed modifications allow one to enumerate all solutions using the ant colony method. To modify

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22

Zhang, Xu, Shilong Wang, Lili Yi, Hong Xue, Songsong Yang, and Xin Xiong. "An integrated ant colony optimization algorithm to solve job allocating and tool scheduling problem." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 232, no. 1 (2016): 172–82. http://dx.doi.org/10.1177/0954405416636038.

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In this article, max–min ant colony optimization algorithm is proposed to determine how to allocate jobs and schedule tools with the objective of minimizing the makespan of processing plans in flexible manufacturing system. To expand the application range of max–min ant colony optimization algorithm, tool movement policy is selected as the running mode of flexible manufacturing system, which assumes that tools are shared among work centers and each operation is allowed to be machined by different kinds of tools. In the process of converting this scheduling problem into traveling salesman probl

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23

Zhu, Wuyang, and Yifei Pu. "A Study of Fractional-Order Memristive Ant Colony Algorithm: Take Fracmemristor into Swarm Intelligent Algorithm." Fractal and Fractional 7, no. 3 (2023): 211. http://dx.doi.org/10.3390/fractalfract7030211.

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As the fourth fundamental circuit element, the memristor may execute computations while storing data. Fracmemristor takes advantage of the fractional calculate’s long-term memory, non-locality, weak singularity, and the memristor’s storage–computational integration. Since the physical structure of the fracmemristor is similar to the topology of the ant transfer probability flow in ACO, we propose the fractional-order memristive ant colony algorithm (FMAC), which uses the fracmemristor physical system to record the probabilistic transfer information of the nodes that the ant will crawl through

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24

Wei, Li Feng. "Design and Implementation of Airline Customer Segmentation System Based on Ant Colony Clustering Algorithm." Advanced Materials Research 433-440 (January 2012): 3357–61. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.3357.

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Segmentation based on customer value and needs can better guide marketing decision-making of airlines as well as better understand needs of high-value passengers. To address customer segmentation in Customer Relationship Management (CRM), the paper proposed and designed airline customer segmentation system structure based on ant colony clustering. The key ant colony clustering algorithm was also designed and implemented. The ant colony clustering algorithm mainly used adaptively adjusted group similarity to perform clustering and access to initial clustering result. Then all data representatio

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Chiha, Ibtissem, Noureddine Liouane, and Pierre Borne. "Tuning PID Controller Using Multiobjective Ant Colony Optimization." Applied Computational Intelligence and Soft Computing 2012 (2012): 1–7. http://dx.doi.org/10.1155/2012/536326.

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This paper treats a tuning of PID controllers method using multiobjective ant colony optimization. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controllers (Kp,Ki, andKd) by minimizing the multiobjective function. The potential of using multiobjective ant algorithms is to identify the Pareto optimal solution. The other methods are applied to make comparisons between a classic approach based on the “Ziegler-Nichols” method and a metaheuristic approach based on the genetic algorithms. Simulation results demonstrate that the new t

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Hou, Yuan Bin, Yi Qian Yuan, and Bai Ping Li. "Path Optimization for Automatic Guided Vehicle Based on Fusion Algorithm of Particle Swarm and Ant Colony." Applied Mechanics and Materials 182-183 (June 2012): 1452–57. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1452.

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Aim at search precocity of particle swarm algorithm and slow convergence speed problem for ant colony algorithm, in the automatic guided vehicle path optimization a path optimization algorithm is proposed, which is fused by particle swarm algorithm and ant colony algorithm. Firstly, robot motion space model of the algorithm is created using link figure. After got fixed circulation rapid global, search to get more optimal path by means of improved fastest convergence ant system, then using a particle ants information communication method to update pheromone, finally, optimal path is drew. The s

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Hong, Guo. "A Hybrid Ant Colony Algorithm for Quadratic Assignment Problem." Open Electrical & Electronic Engineering Journal 7, no. 1 (2013): 51–54. http://dx.doi.org/10.2174/1874129001307010051.

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Quadratic assignment problem (QAP) is one of fundamental combinatorial optimization problems in many fields. Many real world applications such as backboard wiring, typewriter keyboard design and scheduling can be formulated as QAPs. Ant colony algorithm is a multi-agent system inspired by behaviors of real ant colonies to solve optimization problems. Ant colony optimization (ACO) is one of new bionic optimization algorithms and it has some characteristics such as parallel, positive feedback and better performances. ACO has achieved in solving quadratic assignment problems. However, its solutio

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Bai, Ya Nan, Yong Chang Shi, and Xiao Yu Shi. "A Novel Combinatorial Ant Colony Optimization Algorithm with Detection Zone Rule." Applied Mechanics and Materials 568-570 (June 2014): 1511–15. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.1511.

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For solving the Ant Colony System own inherent defects, this paper proposes a novel combinatorial ant Colony Optimization algorithm with detection zone rule. In the proposed algorithm, the pheromone and the search path are modified dynamically. By using the detection method, the artificial ants are detected automatically per m iterations during the detection zone. When the ant colony falls into the local optimum, the variable will be adaptive modified by the algorithm. Meanwhile, for improving the search abilities of artificial ants, it changes the global rate of pheromone evaporation and the

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Shao, Nan. "Research on Architectural Planning and Landscape Design of Smart City Based on Computational Intelligence." Computational Intelligence and Neuroscience 2022 (July 19, 2022): 1–9. http://dx.doi.org/10.1155/2022/1745593.

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City brain is a complex system, including online center, server network, and system with given algorithm. The core of the city brain is the intelligent system. After putting the urban brain into the intelligent nerve center, on the basis of not changing its original data structure, combining its own characteristics for design and then integrating into application, it can intelligently change the urban management mode. Urban planning leads the development of smart cities on a certain meaning, and smart city planning must have scientific and rational urban planning. The intelligent model is used

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Song, Chang Hui. "Global Path Planning Method for USV System Based on Improved Ant Colony Algorithm." Applied Mechanics and Materials 568-570 (June 2014): 785–88. http://dx.doi.org/10.4028/www.scientific.net/amm.568-570.785.

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An improved ant colony algorithm based grid environment model for global path planning method for USV was introduced. The main idea of the improved ant colony algorithm was distributing each ant route dynamically. When the active ant was selecting the next route, this algorithm program determined the nearest direction to the end point. There were many possible route points which were distributed artificially. Thereby, the probability for each ant to choose the right direction was increased. The simulating results demonstrate that the improved ant colony algorithm in this paper is very suitable

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Zhang, Ran, and Yan Zhou. "Thermal control system based on ant colony algorithm." Thermal Science 25, no. 4 Part B (2021): 3179–89. http://dx.doi.org/10.2298/tsci2104179z.

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In order to improve the accuracy and speed of solving the inverse problem of source-seeking heat conduction, the paper proposes a correlation-based ant colony optimization algorithm for the inverse problem of source-seeking heat conduction based on the characteristics of the influence of the heat source position on the boundary temperature distribution in the heat conduction problem. This method is used to construct the corresponding heuristic information value for each co-ordinate of the heat source location, which can reflect the degree of similarity between the temperature curve of the calc

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Abbasi, H., A. Afshar, and M. R. Jalali. "Ant-colony-based simulation–optimization modeling for the design of a forced water pipeline system considering the effects of dynamic pressures." Journal of Hydroinformatics 12, no. 2 (2009): 212–24. http://dx.doi.org/10.2166/hydro.2009.147.

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Valve and pump shut-off in water pipeline systems lead to transient flow. This flow is a complex phenomenon and is potentially a very serious problem causing extra dynamic pressure in the system. Within the last few decades, the evolutionary and meta-heuristic algorithms, such as genetic algorithms, simulated annealing. More recently, however, ant-colony optimization algorithms have received considerable attention. In this paper the procedure and application of the ant-colony optimization algorithm to the design of a water supply pipeline system, considering dynamic pressures arising from valv

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Zong, Xiao Ping, Hai Bin Zhang, Lei Hao, and Pei Guang Wang. "Improved Ant Colony Algorithm and Application in Sequence Images of Prostate DWI Registration." Advanced Materials Research 1049-1050 (October 2014): 530–34. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.530.

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Because of the drift which exists in sequence image of prostate DWI (Diffusion Weighted Imaging), the global ant colony algorithm is introduced into the paper for registration optimization. The paper introduces an ant colony algorithm for continuous function optimization, based on max-min ant system (MMAS). This paper controls the transition probabilities and enhances the abilities of ants seeking globally optimal solutions by adding an adjustable factor in the basic ant colony algorithm and updating the local pheromone and global pheromone. Experimental results verify the effectiveness of the

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Suwoyo, Heru, Zhou Thong, Yingzhong Tian, Andi Adriansyah, and Muhammad Hafizd Ibnu Hajar. "THE ACA-BASED PID CONTROLLER FOR ENHANCING A WHEELED-MOBILE ROBOT." TEKNOKOM 5, no. 1 (2022): 103–12. http://dx.doi.org/10.31943/teknokom.v5i1.74.

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Wall-following control of mobile robot is an important topic in the mobile robot researches. The wall-following control problem is characterized by moving the robot along the wall in a desired direction while maintaining a constants distance to the wall. The existing control algorithms become complicated in implementation and not efficient enough. Ant colony algorithm (ACA), in terms of optimizing parameters, has a faster convergence speed and features that are easy to integrate with other methods. This paper adopts ant colony algorithm to optimize PID controller, and then selects ideal contro

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Suwoyo, Heru, Yingzhong Tian, Andi Adriansyah, Muhammad Hafizd Ibnu Hajar, and Tong Zhou. "The ACA-based PID Controller for Enhancing a Wheeled-Mobile Robot." Journal FORTEI-JEERI 1, no. 2 (2020): 19–23. http://dx.doi.org/10.46962/forteijeeri.v1i2.15.

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Wall-following control of mobile robot is an important topic in the mobile robot researches. The wall-following control problem is characterized by moving the robot along the wall in a desired direction while maintaining a constants distance to the wall. The existing control algorithms become complicated in implementation and not efficient enough. Ant colony algorithm (ACA), in terms of optimizing parameters, has a faster convergence speed and features that are easy to integrate with other methods. This paper adopts ant colony algorithm to optimize PID controller, and then selects ideal contro

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Ding, Dukun. "Research of Immune-Ant Colony Algorithm for the Detection of Weld Pool Image." Journal of Physics: Conference Series 3024, no. 1 (2025): 012028. https://doi.org/10.1088/1742-6596/3024/1/012028.

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Abstract This paper has researched a new immune-ant colony algorithm for weld pool detection.Firstly, the tungsten inert gas welding experiment system has been setup and welding images can be captured in real time. The tungsten inert gas welding experiment system is firstly built up, which can be used for images real time capturing. Based on the experiment system, the immune-ant colony algorithm has been designed.In the end, several testing experiments have been performed, which dictated that the performer of the researched algorithm is better. In testing experiments, after about 35 times iter

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Pu, Bin. "Adaptive Resource Allocation Algorithm for OFDMA System Based on Ant Colony Algorithm." Applied Mechanics and Materials 380-384 (August 2013): 1096–100. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1096.

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This paper has proposed adaptive resources allocative decisions in OFDMA system based on Ant Colony Algorithms.The problem was modeled as finding a minimum cost path in a graph. The antssolution construction was guided by pheromone trail and heuristic information.Due to the unique heuristic searching mechanism of the ant colony algorithm,the proposed algorithm is guaranteed to converge quickly tto an approximately optimal solution.Simulation results show that the performance of the proposed algorithm is close to the optimal solution ,and gains 1-2dB in comparison with the fixed allocation sche

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Boiko, L., and I. Liashenko. "Comparison of the ant colony optimization algorithm and its two modifications." System technologies 2, no. 139 (2022): 40–52. http://dx.doi.org/10.34185/1562-9945-2-139-2022-05.

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The ant optimization algorithm is one of the effective modern algorithms for finding ap-proximate solutions of the salesman problem and similar problems of finding routes on graphs. The first version of this metaheuristic optimization algorithm was proposed by Marco Dorigo in 1992 [1]. After some time, several modifications of this algorithm have been proposed in the literature. The aim of the study is to conduct a comparative analysis of the ant optimization algo-rithm (Ant Colony Optimization, ASO) [1] and its most successful modifications: Ant Colony System (ACS) [2] and Max-Min Ant System

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Koritsas, Elias, Epameinondas Sidiropoulos, and Chris Evangelides. "Optimization of Branched Water Distribution Systems by Means of a Physarum—Inspired Algorithm." Proceedings 2, no. 11 (2018): 598. http://dx.doi.org/10.3390/proceedings2110598.

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Optimizing water distribution systems is an essential part of water resources allocation planning. It leads to challenging combinatorial optimization problems, for which meta-heuristics have been applied, notably genetic algorithms and ant colony optimization. The present paper introduces the application of the physarum algorithm, a recent biologically inspired algorithm, utilized hitherto for path finding problems in networks. Direct comparison is presented to ant colony optimization applied to a typical water supply system.

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Muriel, Javier Biera, and Abbas Fotouhi. "Electric Vehicle Fleet Management Using Ant Colony Optimisation." International Journal of Strategic Engineering 3, no. 1 (2020): 1–16. http://dx.doi.org/10.4018/ijose.2020010101.

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This research is focused on implementation of the ant colony optimisation (ACO) technique to solve an advanced version of the vehicle routing problem (VRP), called the fleet management system (FMS). An optimum solution of VRP can bring benefits for the fleet operators as well as contributing to the environment. Nowadays, particular considerations and modifications are needed to be applied in the existing FMS algorithms in response to the rapid growth of electric vehicles (EVs). For example, current FMS algorithms do not consider the limited range of EVs, their charging time or battery degradat

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Qi, Chen, and Hou Ming. "Research on Gird Task Scheduling Based on Ant Colony Algorithm." Advanced Materials Research 129-131 (August 2010): 1438–43. http://dx.doi.org/10.4028/www.scientific.net/amr.129-131.1438.

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Combining with the advantages of ant colony algorithm to solve optimization problem, this paper designs a grid resource allocation model and task scheduling system based on ant colony algorithm. The algorithm can not only locally update for the pheromone in the allocation of grid computing resources, but also can entirely update for the pheromone after the completion of grid computing resources. Experimental results show that the ant colony algorithm can effectively achieve a reasonable task scheduling and load balancing, its application in the task scheduling in grid environment is very succe

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Zhao, Hong-Yan, Jia-Chen Wang, Xin Guan, Zhi-Hong Wang, Yong-Hui He, and Hong-Lin Xie. "Ant Colony System for Energy Consumption Optimization in Mobile IoT Networks." Journal of Circuits, Systems and Computers 29, no. 09 (2019): 2050150. http://dx.doi.org/10.1142/s0218126620501509.

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In this paper, a new algorithm is proposed for computing the node-disjoint optimal transmission energy consumption route for coded cooperative mobile IoT networks. Inspired by the potential benefits user cooperation can provide, we incorporate user cooperation to the mobile ad-hoc multi-hop IoT networks. Our results include a novel ant colony system-based node-disjoint energy-efficient routing algorithm. Ant colony system can approximate the optimal route by local information and is thus very suitable for mobile IoT network environment. In particular, ant algorithm makes history-sensitive choi

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Mingyue Qiu, Mingyue Qiu, Xueying Zhang Mingyue Qiu, and Xinmeng Wang Xueying Zhang. "2D Patrol Path Planning Based on Ant Colony Algorithm." 電腦學刊 35, no. 3 (2024): 039–51. http://dx.doi.org/10.53106/199115992024063503004.

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<p>Police patrol is an essential and important means to maintain the public security and social stability. However, the role of the experience-based patrol in the development of the social security prevention and control system is also declining. To address the problems of a fuzzy patrol path and irrational path planning in the conventional patrol mode, practical alert data from 2019-2021 was pre-processed and used. On the basis of the Maklink graph theory, optimized patrol paths were improved using the ant colony algorithm. Specifically, 2D path planning in presence of buildings was ana

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Fu, Zhi Qiang, and Lei An Liu. "Improved Ant Colony Optimization and Application on TSP." Applied Mechanics and Materials 182-183 (June 2012): 2055–58. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.2055.

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Ant Colony Optimization is an intelligent optimization algorithm from the observations of ant colonies foraging behavior. However, ACO usually cost more searching time and get into early stagnation during convergence Process. We design the improved ant colony algorithm using perturbation method to avoid early stagnation, adjusting volatilization coefficient to increase the exploration of tours at first phase and searching speed at second phase, using hortation method to improved searching efficiency. We apply the improved algorithm on traveling salesman problem showing that the improved algori

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Herianto, Tejo. "Implementation of the Ant Colony System Algorithm in the Lecture Scheduling Process." Instal : Jurnal Komputer 12, no. 02 (2021): 54–60. http://dx.doi.org/10.54209/jurnalkomputer.v12i02.23.

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Scheduling lectures using the ant algorithm is able to provide alternative solutions for scheduling lectures that want a certain time optimally. In this research, the method used is literature study. This literature study was carried out by reading books and literature related to scheduling and ant algorithms. In addition to using literature studies, researchers also use field studies. This is intended to get a true picture of the state of the institution by observing directly at the institution, by means of observation or data collection methods by conducting interviews on the parts involved

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She, Yongming. "Algorithm Research and Implementation Based on Component Optical Detection System." Journal of Physics: Conference Series 2066, no. 1 (2021): 012019. http://dx.doi.org/10.1088/1742-6596/2066/1/012019.

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Abstract With the development of the times, gradually there is a new thing called electronic components born. Electronic components are collectively called components of electronic components and small machine instruments, such as diodes used in light bulbs. Components can be used in optical inspection systems, but they require some help from computer technology. Therefore, the purpose of this paper is to use algorithms to study component-based optical detection systems. After consulting the literature on components and optical detection systems, we analyzed the suitability of components and o

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Xu, Kaiming, Jianjun Wu, Tengchao Huang, and Lei Liang. "An Improvement of a Mapping Method Based on Ant Colony Algorithm Applied to Smart Cities." Applied Sciences 12, no. 22 (2022): 11814. http://dx.doi.org/10.3390/app122211814.

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The ant colony algorithm has been widely used in the field of data analysis of smart cities. However, the research of the traditional ant colony algorithm is more focused on one-to-one scenarios and there is insufficient research on many-to-one scenarios. Therefore, for the many-to-one topology mapping problem, this paper proposes a mapping method based on the ant colony algorithm. The design purpose of the mapping algorithm is to study the optimal mapping scheme, which can effectively reduce the cost of solving the problem. The core of the mapping algorithm is to design the objective function

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He, Rong, Xinli Wei, and Nasruddin Hassan. "Multi-objective performance optimization of ORC cycle based on improved ant colony algorithm." Open Physics 17, no. 1 (2019): 48–59. http://dx.doi.org/10.1515/phys-2019-0006.

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Abstract To solve the problem of multi-objective performance optimization based on ant colony algorithm, a multi-objective performance optimization method of ORC cycle based on an improved ant colony algorithm is proposed. Through the analysis of the ORC cycle system, the thermodynamic model of the ORC system is constructed. Based on the first law of thermodynamics and the second law of thermodynamics, the ORC system evaluation model is established in a MATLAB environment. The sensitivity analysis of the system is carried out by using the system performance evaluation index, and the optimal wo

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Kim, In-Kyeom, and Min-Young Yun. "Improved Edge Detection Algorithm Using Ant Colony System." KIPS Transactions:PartB 13B, no. 3 (2006): 315–22. http://dx.doi.org/10.3745/kipstb.2006.13b.3.315.

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Mehfuz, Shabana, and Farah Rashid. "Ant colony system algorithm for optimal network reconfiguration." International Journal of Computational Intelligence Systems 7, no. 5 (2014): 973–78. http://dx.doi.org/10.1080/18756891.2014.960235.

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