applications of ant colony optimizationapplications of ant colony optimization

{\displaystyle p_{xy}^{k}} Ant colony optimization is a technique for optimization that was introduced in the early 1990's. The inspiring source of ant colony optimization is the foraging behavior of real ant colonies. x k The following applications could be mentioned: multiple knapsack problem, which is an important economical problem; grid scheduling problem; GPS surveying problem; E. coli cultivation modeling; wireless sensor network positioning; image edges detection; workforce planning. Ant colony optimization (ACO) based optimization of 45nm CMOS-based sense amplifier circuit could converge to optimal solutions in very minimal time. Randomly place Ant Colony Optimization and Applications - ResearchGate Colonies of ants have a very high capacity to adapt themselves to changes in the environment as well as an enormous strength in dealing with situations where one individual fails to carry out a given task. Gambardella et M.Dorigo. Ant colony algorithms are used for path searching and routing if I'm not mistaken. Multi-objective Ant Colony Optimization: An Updated Review of There are several ACO algorithms. 1996, publication of the article on ant system; 1997, Dorigo and Gambardella proposed ant colony system hybridized with local search; 1997, Schoonderwoerd and his colleagues published an improved application to. ". The fifth section introduces the application of RLMOEA/D-ACO in primer design problem. Includes result of the author's work, over the last 20 years, on applying Ant Colony Optimization to a variety of problems coming from real life and Industry. 1 Site design / logo 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA. J Natl Sci Found Sri Lanka 46(2), Selvarajan D, Jabar ASA, Ahmed I (2019) Comparative analysis of PSO and ACO based feature selection techniques for medical data preservation. This is made possible by the EU reverse charge method. {\displaystyle P_{x,y}}. ( 9780262256032 Publication date: 2004 An overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications. This page was last edited on 26 May 2023, at 17:46. I would suggest you to start with the travelling salesman problem, which was the first application of these algorithms. of the move, indicating how proficient it has been in the past to make that particular move. PDF Concise Overview of Applications of Ant Colony Optimization Why do I get different sorting for the same query on the same data in two identical MariaDB instances. Google Scholar, Brand M, Masuda M, Wehner N, Yu X-H (2010) Ant colony optimization algorithm for robot path planning. The artificial ants are partitioned into several groups. Ant Colony Optimization: A Review of Literature and Application in Feature Selection. Step 7: Decision process. Artificial ants stand for multi-agent methods inspired by the behavior of real ants. Introduction The optimization of traffic signal control is at the heart of urban traffic control. (It should now be clear the reason behind the queues real ants form). J Water Resour Plan Manage 129(3):200209, Lpez-IbezM, Prasad TD, Paechter B (2008) Ant colony optimization for optimal control of pumps in water distribution networks. provided immediately after the recommended institution details are received. {\displaystyle \tau _{xz}} ACO algorithms are often combined with local search algorithms (like the 2-opt or 3-opt). 24 As a heuristic search algorithm, ACO has been widely and satisfactorily applied in coping with the discrete . Expert Syst Appl 53:2742, Peng H, Ying C, Tan S, Bing Hu, Sun Z (2018) An improved feature selection algorithm based on ant colony optimization. {\displaystyle I} Parallel Ant Colony Optimization: Algorithmic Models and Hardware Implementations, 3. In: Handbook of metaheuristics, pp 311351. Ant Colony Optimization by Marco Dorigo and Thomas Sttzle, MIT Press, 2004. As an IntechOpen contributor, you can buy this book for an Exclusive Author price with discounts from 30% to 50% on retail price. In ACO algorithms, (articial) ants construct candidate solutions to the problem be-ing tackled, making decisions that are stochastically biased by numerical information Thus, each ant Comput Methods Programs in Biomed 145:115125, Sinoquet C, Niel C (2018) Ant colony optimization for markov blanket-based feature selection. It is, for example, impossible to integrate a high performance calculator with the power to solve any kind of mathematical problem into a biochip that is implanted into the human body or integrated in an intelligent tag which is designed to trace commercial articles. Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method, Alice in pheromone land: An experimental setup for the study of ant-like robots, COS: artificial pheromone system for robotic swarms research, A practical multirobot localization system, Ant system: optimization by a colony of cooperating agents, Ant Colony System: A Cooperative Learning Approach to the Traveling Salesman Problem. This paper portrays how current literature utilizes the ACO approach for performing feature selection. 2021 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. Nayar, N., Gautam, S., Singh, P., Mehta, G. (2021). In the case of certain problems, this type of intelligence can be superior to the reasoning of a centralized system similar to the brain. This algorithm corresponds to the one presented above. M. den Besten, "Ants for the single machine total weighted tardiness problem," Master's thesis, University of Amsterdam, 2000. Ant Colony Optimization (ACO) [1,2,3] is a metaheuristic for solving hard com-binatorial optimization problems inspired by the indirect communication of real ants. PhD diss., PhD thesis, Facult des Sciences Appliques, Universit Libre de Bruxelles, Brussels, Belgium, Khan I, Huang JZ, Tung NT (2013) Learning time-based rules for prediction of alarms from telecom alarm data using ant colony optimization. d 1. A performance analysis of a continuous ant colony algorithm with respect to its various parameters (edge selection strategy, distance measure metric, and pheromone evaporation rate) showed that its performance and rate of convergence are sensitive to the chosen parameter values, and especially to the value of the pheromone evaporation rate. is a parameter to control the influence of 1 Swarm Intelligence (SI) is a popular field of research that is motivated by the natural phenomenon of the population (group) of various living organisms in their natural habitat for the search of. can be calculated using the following functions: The parameter th ant, typically given for a TSP problem (with moves corresponding to arcs of the graph) by. [4] Artificial 'ants' (e.g. Books > In the ant colony system algorithm, the original ant system was modified in three aspects: In this algorithm, the global best solution deposits pheromone on its trail after every iteration (even if this trail has not been revisited), along with all the other ants. Lima, Danielli A., and Gina MB Oliveira. The wide variety of algorithms (for optimization or not) seeking self-organization in biological systems has led to the concept of "swarm intelligence",[11] which is a very general framework in which ant colony algorithms fit. Preliminary. 1 422427. Get your Discount. Nandini Nayar . ; Gupta, J.P.; Arora, Y.; Shankar, U., ". In that case, the exploration of the solution space would be constrained. 693 - 698, 10.1109/BIBE.2007.4375636. A Hybrid Feature Selection Approach for Data Clustering Based on Ant x ( Anyone you share the following link with will be able to read this content: Sorry, a shareable link is not currently available for this article. M The application of ant colony optimization in the solution of 3D traveling salesman problem on a sphere - ScienceDirect Engineering Science and Technology, an International Journal Volume 20, Issue 4, August 2017, Pages 1242-1248 Full Length Article x M 0 The pheromone-based communication of biological ants is often the predominant paradigm used. Int J Adv Res Ideas Innovations Technol 4(4), Manoj RJ, Praveena MDA, Vijayakumar K (2019) An ACOANN based feature selection algorithm for big data. {\displaystyle k} y In: 2018 12th international symposium on medical information and communication technology (ISMICT), pp 16. MathSciNet i Ant colony optimization is between the best method for solving difficult optimization problems arising in real life and industry. J Water Resour Plann Manage 134(4):337346, Zheng F, Zecchin AC, Newman JP, Maier HR, Dandy GC (2017) An adaptive convergence-trajectory controlled ant colony optimization algorithm with application to water distribution system design problems. where In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. CRC Press (Oct 3), Dorigo M, Sttzle T (2019) Ant colony optimization: overview and recent advances. L.M. Device sizing problem in nanoelectronics physical design. [29], The pheromone deposit mechanism of COAC is to enable ants to search for solutions collaboratively and effectively. IEEE, Liu J, Yang J, Liu H, Tian X, Gao M (2017) An improved ant colony algorithm for robot path planning. Ant Colony Optimization or simply ACO is a meateuristic that is used to solve optimization problems that are complex combinatorial [1,2]. and In the second step, the paths found by the different ants are compared. This algorithm controls the maximum and minimum pheromone amounts on each trail. [9], Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength. IEEE Access 7:1964319652, Huang G, Cai Y, Cai H (2018) Multi-agent ant colony optimization for vehicle routing problem with soft time windows and road condition. How do I troubleshoot a zfs dataset that the server when the server can't agree if it's mounted or not? [108] Ants mark the best solutions and take account of previous markings to optimize their search. G. Leguizamon, Z. Michalewicz and Martin Schutz, ", O. Okobiah, S. P. Mohanty, and E. Kougianos, ", M. Sarkar, P. Ghosal, and S. P. Mohanty, ", Ermolaev S.Y., Slyusar V.I. to state An ant colony optimization algorithm with evolutionary experience of moving from state Lecture Notes in Networks and Systems, vol 173. Optimization Methods for Image Edge Detection Using Ant and Bee Colony Ant Colony Optimization - Marco Dorigo, Thomas Stutzle - Google Books However, those implementations were not able to replicate all the aspects of pheromones as seen in nature. Chu S C, Roddick J F, Pan J S. Ant colony system with communication strategies[J]. The ant colony optimization (ACO) algorithms are stochastic search techniques inspired by the behavior of real ants [12]. By analyzing the literature, it can be concluded that ACO is a suitable approach for feature selection. Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling the behavior of ants and other social insects can provide inspiration for the development of computational algorithms for the solution of difficult mathematical problems. URL: Learn how and when to remove these template messages, Learn how and when to remove this template message, A cellular automata ant memory model of foraging in a swarm of robots. Ant Colony Optimization - Methods and Applications | IntechOpen Pheromone matrix Learn more about Stack Overflow the company, and our products. I This is of interest in network routing and urban transportation systems. x Inf Sci 490:166190, CrossRef The following are the steps involved in edge detection using ACO:[81][82][83]. ", Sakakibara, Toshiki, and Daisuke Kurabayashi. For the below example the heuristic matrix was calculated based on the local statistics: In: Smys, S., Balas, V.E., Kamel, K.A., Lafata, P. (eds) Inventive Computation and Information Technologies. j There are various methods to determine the heuristic matrix. Cluster Comput 22(2):39533960, Jayaprakash A, KeziSelvaVijila C (2019) Feature selection using ant colony optimization (ACO) and road sign detection and recognition (RSDR) system. Recursive ant colony optimization: a new technique for the estimation of function parameters from geophysical field data, ACO for Continuous Function Optimization: A Performance Analysis, Classification with Ant Colony Optimization, Beam-ACO, Hybridizing ant colony optimization with beam search. PubMed For any assistance during ordering process, contact us at orders@intechopen.com, Edited by is the pheromone evaporation coefficient, 1998, Dorigo launches first conference dedicated to the ACO algorithms; 1999, Gambardella, Taillard and Agazzi proposed, 1999, Bonabeau, Dorigo and Theraulaz publish a book dealing mainly with artificial ants, 2000, special issue of the Future Generation Computer Systems journal on ant algorithms, 2000, Gutjahr provides the first evidence of, 2001, the first use of COA algorithms by companies (, 2001, Iredi and his colleagues published the first. Particle Swarm and Ant Colony Algorithms and Their Applications in This book is interesting and full of new ideas. Ant Colony Optimization - Techniques and Applications | IntechOpen {\displaystyle \eta _{xz}} Institute of Information and Communication Technology, Bulgarian Academy of Sciences, Sofia, Bulgaria, You can also search for this author in This paper proposes a hybrid feature selection technique based on ant colony optimization . Axioms | Free Full-Text | Application of Ant Colony Optimization - MDPI He's still one of the leading figures in the field of swarm intelligence (having also written or co-written several papers and books). Sound for when duct tape is being pulled off of a roll. Gambardella, M. Dorigo, "An Ant Colony System Hybridized with a New Local Search for the Sequential Ordering Problem", INFORMS Journal on Computing, vol.12(3), pp. x {\displaystyle \lambda } M. Dorigo, M. Birattari & T. Sttzle, 2006. It was developed by Dorigo.[26]. For ant , where Application of improved ant colony optimization in mobile robot All edges are initialized to max to force a higher exploration of solutions. k This model is based on the co-operation of independent units with simple and unpredictable behavior. {\displaystyle y} New methods and theory such as multi colony ant algorithm based upon a new pheromone arithmetic crossover and a repulsive operator, new findings on ant colony convergence, and a diversity of engineering and science . Indeed, their intelligence can be classed as fairly limited. Cogn Syst Res 58:123133, Nayyar A, Le DN, Nguyen NG (eds) (2018) Advances in swarm intelligence for optimizing problems in computer science. Int Arab J Inf Technol 16(4):731736, Khorram T, Baykan NA (2018) Feature selection in network intrusion detection using metaheuristic algorithms. Eur Water 55:4151, Shahraki J, Sardar SA, Nouri S (2019) Application of met heuristic algorithm of ant Colony optimization in optimal allocation of water resources of Chah-Nime of Sistan under managerial scenarios. Springer, Singapore, Manoharan S (2019) Study on Hermitian graph wavelets in feature detection. Here are some of the most popular variations of ACO algorithms. ( Is there a reliable way to check if a trigger being fired was the result of a DML action from another *specific* trigger? An ant colony system (ACS) with communication strategies is developed. Front. . Theophile Theophanides, IntechOpen Limited . However, the current ant colony optimization algorithm applied to the path planning of mobile robots still has some limitations, including early blind search, slow convergence speed, and more turns. https://doi.org/10.1007/978-981-33-4305-4_22, DOI: https://doi.org/10.1007/978-981-33-4305-4_22, eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0). , the probability 2023 Springer Nature Switzerland AG. Open Access is an initiative that aims to make scientific research freely available to all. The probability with which the ant moves is given by the probability equation L. Bianchi, L.M. 4973, Springer-Verlag, Berlin, Heidelberg, Italy, 2008, pp. {\displaystyle x} ) depends on the combination of two values, the attractiveness More specifically, the amount of pheromone is associated with value (e.g. A. V. Donati, V. Darley, B. Ramachandran, "An Ant-Bidding Algorithm for Multistage Flowshop Scheduling Problem: Optimization and Phase Transitions", book chapter in Advances in Metaheuristics for Hard Optimization, Springer. y Is there a faster algorithm for max(ctz(x), ctz(y))? Thus, in the example of the Travelling salesman problem, it is not necessary that an ant actually travels the shortest route: the shortest route can be built from the strongest segments of the best solutions. Ant Colony Optimization | Books Gateway | MIT Press 4 pp. An example of a global pheromone updating rule is, where Wiley Interdisc Rev Data Min Knowl Disc 10(1):e1338, Di Caro G, Dorigo M (2004) Ant colony optimization and its application to adaptive routing in telecommunication networks. y [5] One variation on this approach is the bees algorithm, which is more analogous to the foraging patterns of the honey bee, another social insect. New concepts are required since intelligence is no longer centralized but can be found throughout all minuscule objects. 401-406, 2001. , A. Ajith; G. Crina; R. Vitorino (diteurs). rev2023.6.2.43474. Neurocomputing 98:101107, Yu B, Yang Z-Z, Yao B (2009) An improved ant colony optimization for vehicle routing problem. IEEE, Cong YZ, Ponnambalam SG (2009) Mobile robot path planning using ant colony optimization. {\displaystyle \tau _{xy}} [30], It is a recursive form of ant system which divides the whole search domain into several sub-domains and solves the objective on these subdomains. Connect and share knowledge within a single location that is structured and easy to search. Probabilistic Behaviour in Ants: a Strategy of Errors? Efficient ant colony optimization for image feature selection (PDF) Application of Ant Colony Optimization: An Approach towards What does "Welcome to SeaWorld, kid!" {\displaystyle xy} Stack Exchange network consists of 181 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. IEEE, Jameel S, Ur Rehman S (2018) An optimal feature selection method using a modified wrapper-based ant colony optimisation. Ant colony optimization algorithms have been applied to many combinatorial optimization problems, ranging from quadratic assignment to protein folding or routing vehicles and a lot of derived methods have been adapted to dynamic problems in real variables, stochastic problems, multi-targets and parallel implementations. Meet the Ant Colony For performance reasons, the ants are represented as a set of 2048 wide numpy arrays, which allows for fast vectorized operations; Many of the parameters are tunable, which will affect the internal logic of the ant colony, but have been set to sensible/optimal defaults; The high-level logic of the algorithm is: Each ant needs to construct a solution to move through the graph. To date our community has made over 100 million downloads. The purpose of this study is to apply the workings of the Ant Colony Optimization algorithm in Travelling Problem. Publishing on IntechOpen allows authors to earn citations and find new collaborators, meaning more people see your work not only from your own field of study, but from other related fields too. 163181, December 2008. 5 Princes Gate Court, M . j Part of the book series: Studies in Computational Intelligence (SCI . The related Wikipedia article contains a more exhaustive section dedicated to the applications of these algorithms. Our team is growing all the time, so were always on the lookout for smart people who want to help us reshape the world of scientific publishing. This research article presents a swarm-based optimization algorithm, known as Modified Ant Lion Optimization (MALO) algorithm to solve optimal power flow (OPF) problems. Provided by the Springer Nature SharedIt content-sharing initiative, Over 10 million scientific documents at your fingertips, Not logged in The fundamental ideas of ant colony optimization is reviewed including its biological background and application areas. Methodological Advances and Biomedical Applic Organic Pollutants Ten Years After the Organic Pollutants Ten Years After the Stockholm Convention, 1. Int J Comput Inf Technol 13(1):139147, Shunmugapriya P, Kanmani S (2017) A hybrid algorithm using ant and bee colony optimization for feature selection and classification (AC-ABC Hybrid). Application of ant colony and immune combined optimization algorithm in Google Scholar, Sidiropoulos E, Fotakis D (2016) Spatial water resource allocation using a multi-objective ant colony optimization. ", M. Dorigo, G. Di Caro & L. M. Gambardella, 1999. 622-627, 1996; R. Schoonderwoerd, O. Holland, J. Bruten et L. Rothkrantz. is the number of ants and In: International conference on machine learning, optimization, and data science, pp 217230. Edited by: Avi Ostfeld. {\displaystyle y} M, den Bseten, T. Sttzle and M. Dorigo, "Ant colony optimization for the total weighted tardiness problem," Proceedings of PPSN-VI, Sixth International Conference on Parallel Problem Solving from Nature, vol. IEEE, Chia S-H, Su K-L, Guo J-R, Chung C-Y (2010) Ant colony system based mobile robot path planning. VS "I don't like it raining.". M IJ Netw Secur 18.3:420432, Aghdam MH, Ghasem-Aghaee N, Basiri ME (2009) Text feature selection using ant colony optimization. {\displaystyle M_{1}*M_{2}} Designing pheromone communication in swarm robotics: Group foraging behavior mediated by chemical substance, Artificial pheromone system using rfid for navigation of autonomous robots, Investigation of cue-based aggregation in static and dynamic environments with a mobile robot swarm, Imitation of honeybee aggregation with collective behavior of swarm robots, Get in touch: cooperative decision making based on robot-to-robot collisions. ) What is the meaning of the square brackets in ant colony optimization? {\displaystyle y} ) J Med Imaging Health Inf 6(7):15941599, Ding Q, Xiangpei Hu, Sun L, Wang Y (2012) An improved ant colony optimization and its application to vehicle routing problem with time windows. where 12-23. In combinatorial problems, it is possible that the best solution eventually be found, even though no ant would prove effective. Application of ant colony optimization algorithm in process planning Inspired by the foraging behavior of ants, ACO mimics . Ant Colony Optimization (ACO) is the best example of how studies aimed at understanding and modeling the behavior of ants and other social insects can provide inspiration for the development of computational algorithms for the solution of difficult mathematical problems. 1 However, this definition can be problematic in the case of problems in real variables, where no structure of 'neighbours' exists. Ant Colony Optimization Toward Feature Selection, 2. Portfolio Optimization Using Ant Colony Method a Case Study on Tehran Stock Exchange. Ant Colony Optimization: A Review of Literature and Application in Swarm Evol Comput 36:2736, Sweetlin JD, Nehemiah HK, Kannan A (2018) Computer aided diagnosis of pulmonary hamartoma from CT scan images using ant colony optimization based feature selection. We are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including Nobel Prize winners and some of the worlds most-cited researchers. Do ants need to estimate the geometrical properties of trail bifurcations to find an efficient route? [11], Nature offers several examples of how minuscule organisms, if they all follow the same basic rule, can create a form of collective intelligence on the macroscopic level. 1 is a parameter to control the influence of Optimization of integrated process planning and scheduling has important practical significance for balancing the load of the process resources, shortening production cycle, and reducing production costs. An Ant Colony Optimization Algorithm for Area Traffic Control [109] In their versions for combinatorial problems, they use an iterative construction of solutions. k 2 31, No. Does the conduit for a wall oven need to be pulled inside the cabinet? B. Prabhakar, K. N. Dektar, D. M. Gordon, "The regulation of ant colony foraging activity without spatial information ", PLOS Computational Biology, 2012. {\displaystyle \eta _{xy}} Information sciences, 2004, 167(1-4): 63-76. & Tian, D. Ant colony optimization for assembly sequence planning based on parameters optimization. It provokes the curiosity of the readers. This movement causes the highest density of the pheromone to be deposited at the edges. 107ME058 Under the supervision of Dr. Dayal R Parhi Professor x Once the K ants have moved a fixed distance L for N iteration, the decision whether it is an edge or not is based on the threshold T on the pheromone matrix. W. N. Chen and J. ZHANG "Ant Colony Optimization Approach to Grid Workflow Scheduling Problem with Various QoS Requirements", IEEE Transactions on Systems, Man, and Cybernetics--Part C: Applications and Reviews, Vol. Its based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. x Therefore, this paper adopts the ant colony algorithm in the meta-heuristic search method combined with the incomplete quadtree to improve the searchability of the space. In: arXiv: 1908.08007, Nayar N, Ahuja S, Jain S (2019) Swarm intelligence for feature selection: a review of literature and reflection on future challenges. All solutions are ranked according to their length. ". {\displaystyle A_{k}(x)} Application of Ant Colony Optimization: An Approach towards Travelling Salesman Problem Resolution In book: Current Approaches in Science and Technology Research (pp.1-7) Publisher: B P. The orthogonal design method and the adaptive radius adjustment method can also be extended to other optimization algorithms for delivering wider advantages in solving practical problems.