Academic literature on the topic 'Ant colony sytem algorithm'
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Journal articles on the topic "Ant colony sytem algorithm"
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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 finally find a comparison based on the algorithm of reasonable arrangement of ant colony algorithm, based on the algorithms require the creation of database related data tables, draw flow chart of relevant, according to the above data for design and development of the system.
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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 efficiency significantly. Contrastive experiments show that the algorithm has a better capability of global optimization than traditional ant colony algorithm.
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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 approximation methods to find the best solution to this problem. Some of these algorithms belong to the Evolutionary Algorithms (EAs) category, such as Genetic Algorithms (GAs), and some belong to the Swarm Intelligence Algorithms (SIAs) category, such as Ant Colony Optimization (ACO). However, to the best of our knowledge, the Ant Colony System (ACS) algorithm, which is considered an updated version of ACO, has not yet been used to design reliability-constrained communication network topologies. Therefore, this study aims to apply the updated version of the ACS algorithm for solving RCND in small, medium, and large networks. The proposed algorithm was benchmarked against present state-of-the-art techniques that address this challenge. The research findings show that the proposed algorithm is an optimal solution for a fully connected small network size (n=6, 7, 8, and 9) and it has been achieved as an optimal solution for all not fully connected sets (n=14, 16, and 20). In each case, the results for medium-sized networks were better than the benchmark results
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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 of ant colony algorithm in university teaching management service system, and puts forward the application strategy of ant colony algorithm in University Teaching Management Service System.
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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 efficiency can be improved. Simulation experiments tested the recognition rates of traditional ant colony algorithm and improved ant colony algorithm. The results show that the global search ability and accuracy of improved ant colony algorithm are better than traditional algorithms, which can effectively improve the efficiency of English speech recognition system.
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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. The crossover operation of a genetic algorithm was used in the ant system for path optimization. Experimental results show that the algorithm has better path planning optimization ability than other algorithms.
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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 expectation heuristic function and introducing a ‘reward–penalty system’ for pheromones, the contradictions between convergence speed and the tendency to fall into local optima are avoided. Applying the improved ant colony algorithm to the process planning of large container ship propeller shaft machining, this study constructs a ‘distance’ model for each machining unit and develops a process constraint table. The results show significant improvements in initial search capabilities and convergence speed with the improved ant colony algorithm while also resolving the contradiction between convergence speed and optimal solutions. This verifies the feasibility and effectiveness of the improved ant colony algorithm in intelligent process planning for ships.
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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 can greatly improve the dynamic performance of the control system. So we verify the sophistication and effectiveness of the 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 performance of the algorithm through meticulous parameter fine-tuning and policy improvement. We explored a range of parameter adjustments, including variables such as pheromone evaporation rate, ant colony size, etc. By undertaking this comprehensive investigation, we aspire to push the boundaries of ant colony optimization, unlocking its potential to deliver highly efficient solutions for complex TSP instances. This research holds promise for revolutionizing the efficiency and cost-effectiveness of solutions across a wide range of practical applications.
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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 could always be performed in feasible region and the retrieval process of the algorithm was effectively conducted. It is feasible and efficient to find the optimal unit commitment operation by ant colony optimization algorithm, which was proved by stimulation.
Dissertations / Theses on the topic "Ant colony sytem algorithm"
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Sabri, Dalia. "Performance analysis for network coding using ant colony routing." Thesis, Brunel University, 2011. http://bura.brunel.ac.uk/handle/2438/6435.
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The aim of this thesis is to conduct performance investigation of a combined system of Network Coding (NC) technique with Ant-Colony (ACO) routing protocol. This research analyses the impact of several workload characteristics, on system performance. Network coding is a significant key development of information transmission and processing. Network coding enhances the performance of multicast by employing encoding operations at intermediate nodes. Two steps should realize while using network coding in multicast communication: determining appropriate transmission paths from source to multi-receivers and using the suitable coding scheme. Intermediate nodes would combine several packets and relay them as a single packet. Although network coding can make a network achieve the maximum multicast rate, it always brings additional overheads. It is necessary to minimize unneeded overhead by using an optimization technique. On other hand, Ant Colony Optimization can be transformed into useful technique that seeks imitate the ant’s behaviour in finding the shortest path to its destination using quantities of pheromone that is left by former ants as guidance, so by using the same concept of the communication network environment, shorter paths can be formulated. The simulation results show that the resultant system considerably improves the performance of the network, by combining Ant Colony Optimization with network coding. 25% improvement in the bandwidth consumption can be achieved in comparison with conventional routing protocols. Additionally simulation results indicate that the proposed algorithm can decrease the computation time of system by a factor of 20%.
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Bremang, Appah. "Using ant colonies for solve the multiprocessor task graph scheduling." Thesis, Högskolan Dalarna, Datateknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:du-2381.
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The problem of scheduling a parallel program presented by a weighted directed acyclic graph (DAG) to the set of homogeneous processors for minimizing the completion time of the program has been extensively studied as academic optimization problem which occurs in optimizing the execution time of parallel algorithm with parallel computer.In this paper, we propose an application of the Ant Colony Optimization (ACO) to a multiprocessor scheduling problem (MPSP). In the MPSP, no preemption is allowed and each operation demands a setup time on the machines. The problem seeks to compose a schedule that minimizes the total completion time.We therefore rely on heuristics to find solutions since solution methods are not feasible for most problems as such. This novel heuristic searching approach to the multiprocessor based on the ACO algorithm a collection of agents cooperate to effectively explore the search space.A computational experiment is conducted on a suit of benchmark application. By comparing our algorithm result obtained to that of previous heuristic algorithm, it is evince that the ACO algorithm exhibits competitive performance with small error ratio.
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Björk, Carl Johan. "PID tuning with Ant Colony Optimization (ACO) : A framework for a step response based tuning algorithm." Thesis, Mittuniversitetet, Avdelningen för elektronikkonstruktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-33903.
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The building automation industry lacks an affordable, simple, solution for autonomous PID controller tuning when overhead variables fluctuate. In this project, requested by Jitea AB, a solution was developed, utilising step response process modelling, numerical integration of first order differential equations, and Ant Colony Optimization (ACO). The solution was applied to two control schemes; simulated outlet flow from a virtual water tank, and the physical air pressure in the ventilation system of a preschool in Sweden. An open-loop step response provided the transfer function in each case, which, after some manipulation, could be employed to predict the performance of any given set of PID parameters, based on a weighted cost function. This prediction model was used in ACO to find optimal settings. The program was constructed in both Structured Control Language and Structured Text and documented in an approachable way. The results showed that the program was, in both cases, able to eliminate overshoot and retain the settling time (with a slightly raised rise time) achieved with settings tuned per the current methods of Jitea AB. Noise and oscillations present in the physical system did not appear to have any major negative influence on the tuning process. The program performed above Jitea AB’s expectation, and will be tested in more scenarios, as it showed promise. Autonomous implementation could be of societal benefit through increased efficiency and sustainability in a range of processes. In future studies, focus should be on improving the prediction model, and further optimising the ACO variables.<br>Byggnadsautomationsbranschen saknar en kostnadseffektiv lösning för att autonomt trimma in PID-regulatorer när överordnade variabler fluktuerar. I detta (av Jitea AB beställda) arbete, utvecklades en lösning baserad på stegsvarsmodellering, numerisk integration av första gradens ordinära differentialekvationer och myrkolonisoptimering (ACO). Lösningen applicerades i två regleringsfall; en simulerad utloppsventil från en virtuell vattentank, och det fysiska lufttrycket i ventilationssystemet på en förskola i Sverige. Ett stegsvar med öppen slinga gav en överföringsfunktion i respektive fall, som efter viss manipulering kunde nyttjas för att förutspå prestandan för en uppsättning PID-parametrar baserat på en samlad, viktad kostnadsfunktion. Predikteringsmodellen implementerades i ACO för att finna optimala parametrar. Programmet konstruerades i Structured Control Language och Structured Text, och dokumenterades på ett pedagogiskt sätt. Resultaten visade att programmet (i båda fallen) klarade att eliminera översläng med bibehållen stabiliseringstid (och något förskjuten stigningstid) jämfört med Jitea AB:s existerande trimningsmetod. Signalbrus och oscillationer i det fysiska systemet verkade inte ha någon avsevärd negativ inverkan på trimningsprocessen. Programmet presterade över Jitea AB:s förväntan, och kommer (med tanke på de lovande resultaten) fortsatt att testas i fler scenarion. Implementation av en autonom version skulle kunna innebära flera samhälleliga förmåner i form av ökad verkningsgrad och hållbarhet i en rad processer. I framtida studier bör fokus läggas på att ytterligare förbättra prediktionsmodellen, samt att vidare utforska de optimala myrkolonisvariablerna.
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Deilami, Sara. "Optimal dispatch of shunt capacitors and load tap changers in distorted distribution systems using ant colony algorithms." Thesis, Curtin University, 2010. http://hdl.handle.net/20.500.11937/92.
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This thesis investigates the performances of a class of intelligent system algorithms in solving the volt/VAr/THD control problem for large distribution systems. For this purpose, optimal dispatch of Load Tap Changers (LTCs) and Switched Shunt Capacitors in distribution networks with high penetration of nonlinear loads is studied. The optimization problem consists of determination of LTC positions, switched shunt capacitors statuses and proper coordination of these switched elements such that power loss is minimized, voltage profile is improved and total harmonic voltage distortion (THDv) is acceptable while network and operational constraints are satisfied. The Decoupled Harmonic Power Flow (DHPF) is employed for solving the optimization problem. In the next step, an Ant Colony algorithm (ACA) is developed and implemented as an effective and new technique to capture the near global solution of the dispatch problem. Simulation results based on ACA, Genetic Algorithm (GA) and Fuzzy-GA are presented and compared to show the accuracy of the proposed approach.Finally, the application of the developed dispatch ACA in smart grids with Plug-In Electric Vehicle (PEV) charging activities in the residential networks is considered. ACA is first applied on the distribution part of the smart grid to minimize losses, improve voltage profile and mitigate harmonic distortions. Then, a smart load management (SLM) algorithm is proposed and tested for the coordination of PEVs on the residential feeders. The developed algorithm is tested on smart grid configuration with 449 buses consisting of the IEEE 31-bus distribution system connected to a number of low voltage residential feeders populated with PEVs. Simulation results are presented and compared for uncoordinated (random) and SLM coordinated PEV charging considering consumer designated priorities and charging zones.
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Korgo, Jakub. "Nové aplikace mravenčích algoritmů." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-385942.
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Ant algorithms have been used for a variety of combinatorial optimization problems. One of these problems, where ant algorithms haven't been used, is the design of transition rules for cellular automata (CA). Which is a problem that this master's thesis is focused on. This work begins with an introduction into ant algorithms and a overview of its applications, followed by an introduction into CA. In the next part the author proposes a way how to encode rules of CA into a graph which is used in ant algorithms. The last part of this thesis contains an application of encoded graph on elitist ant system and MAX-MIN ant system. This is followed by experimental results of creating transition rules for CA problems by these algorithms.
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Aidov, Alexandre. "Modified continuous ant colony algorithm for function optimization." FIU Digital Commons, 2008. http://digitalcommons.fiu.edu/etd/1166.
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Many classical as well as modern optimization techniques exist. One such modern method belonging to the field of swarm intelligence is termed ant colony optimization. This relatively new concept in optimization involves the use of artificial ants and is based on real ant behavior inspired by the way ants search for food. In this thesis, a novel ant colony optimization technique for continuous domains was developed. The goal was to provide improvements in computing time and robustness when compared to other optimization algorithms. Optimization function spaces can have extreme topologies and are therefore difficult to optimize. The proposed method effectively searched the domain and solved difficult single-objective optimization problems. The developed algorithm was run for numerous classic test cases for both single and multi-objective problems. The results demonstrate that the method is robust, stable, and that the number of objective function evaluations is comparable to other optimization algorithms.
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Gambardella, Luca Maria. "Coupling ant colony system with local search." Doctoral thesis, Universite Libre de Bruxelles, 2015. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209045.
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In the last decades there has been a lot of interest in computational models and metaheuristics algorithms capable to solve combinatorial optimization problems. The recent trend is to define these algorithms taking inspiration by the observation of natural systems. In this thesis the Ant Colony System (ACS) is presented which has been inspired by the observation of real ant colonies. ACS is initially proposed to solve the symmetric and asymmetric travelling salesman problems where it is shown to be competitive with other metaheuristics. Although this is an interesting and promising result, it was immediately clear that ACS, as well as other metaheuristics, in many cases cannot compete with specialized local search methods. An interesting trend is therefore to couple metaheuristics with a local optimizer, giving birth to so-called hybrid methods. Along this line, the thesis investigates MACS-VRPTW (Multiple ACS for the Vehicle Routing Problem with Time Windows) and HAS-SOP: Hybrid Ant System for the Sequential Ordering Problem (SOP). In the second part the thesis introduces some modifications of the original ACS algorithm. These modifications are able to speed up the method and to make it more competitive in case of large problem instances. The resulting framework, called Enhanced Ant Colony System is tested for the SOP. Finally the thesis presents the application of ACS to solve real-life vehicle routing problems where additional constraints and stochastic information are included.<br>Doctorat en Sciences de l'ingénieur<br>info:eu-repo/semantics/nonPublished
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Natanasihamani, Hariharan. "Behavior integration for Prometheus using real world ant colony algorithm." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=121468.
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Prometheus aims to explore artificial intelligence in a controlled but flexible environment by mimicking the properties of the real world using a swarm intelligence implementation. Swarm Intelligence has been used for solving problems in the domain of self organization, complexity and collective intelligence for a group of agents. The collective behavior of the entity considered here - ants, are modeled as a decentralized and self-organized system in which the ants communicate indirectly and thrive by modifying the environment. This novel approach combines the widely established stigmergy theory with real-time fluid dynamics by using Pheromones and the Navier-Stokes equations respectively to subject the environment to natural conditions like wind, and spread and decay of smell thus making the environment more suitable to real time conditions. The chosen real-time fluid dynamics method proves to be computationally fast, robust and far more realistic than traditional approaches. Also, for evaporation, instead of choosing a random fixed value for every timestep, we take into consideration the effect of temperature, vapor pressure, wind and humidity on evaporation and consequences of that. It is hoped that this model will be a step closer to achieving results substantially closer to the real world and also, observing the changes that the aforementioned natural properties might impose on the experimental world.<br>Le projet d'intelligence artificielle Prometheus vise à explorer, dans un environnement contrôlé mais flexible, les propriétés du monde réel sur une intelligence en essaim. L'intelligence distribuée a été utilisée afin de résoudre les problèmes dans le domaine de l'auto-organisation, la complexité et l'intelligence collective d'un groupe d'agents. Le comportement collectif de l'entité considérée, ici la fourmi, est modélisé comme un système décentralisé et auto-organisé dans lequel les fourmis communiquent indirectement et prospèrent en modifiant l'environnement. Celle nouvelle approche combine la théorie de stigmergie avec la mécanique des fluides, utilisant respectivement les phéromones et les équations de Navier-Stokes, afin de soumettre à l'environnement des conditions naturelles comme le vent ou encore la propagation et la désintégration de l'odeur. Ainsi l'environnement correspond mieux à des conditions réelles. La méthode de mécanique des fluides en temps réel choisie, s'avère être rapidement calculable, robuste et beaucoup plus réaliste que les approches traditionnelles. De plus, pour modéliser l'évaporation, au lieu de choisir une valeur aléatoire fixée pour chaque itération, nous prenons en compte l'effet de la température, de la pression de la vapeur, du vent, de l'humidité de l'évaporation et leurs conséquences. Nous pensons que ce modèle contribuera à l'obtention de résultats nettement plus proches du monde réel et à l'observation des changements que les propriétés naturelles susmentionnées pourraient imposer à l'environnement expérimental.
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Wang, Yuan. "Localized Ant Colony of Robots for Redeployment in Wireless Sensor Networks." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30706.
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Sensor failures or oversupply in wireless sensor networks (WSNs), especially initial
random deployment, create both spare sensors (whose area is fully covered by other
sensors) and sensing holes. We envision a team of robots to relocate sensors and
improve their area coverage. Existing algorithms, including centralized ones and the
only localized G-R3S2, move only spare sensors and have limited improvement because
non-spare sensors, with area coverage mostly overlapped by neighbour sensors,
are not moved, and additional sensors are deployed to fill existing holes. We propose
a localized algorithm, called Localized Ant-based Sensor Relocation Algorithm with
Greedy Walk (LASR-G), where each robot may carry at most one sensor and makes
decision that depends only on locally detected information. In LASR-G, each robot
calculates corresponding pickup or dropping probability, and relocates sensor with
currently low coverage contribution to another location where sensing hole would be
significantly reduced. The basic algorithm optimizes only area coverage, while modified algorithm includes also the cost of robot movement. We compare LASR-G with
G-R3S2, and examine both single robot and multi robots scenarios. The simulation
results show the advantages of LASR-G over G-R3S2.
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Raya, Lilysuriazna Binti. "A metaheuristic ant colony optimization algorithm for symmetric and asymmetric traveling salesman problems." Thesis, Brunel University, 2018. http://bura.brunel.ac.uk/handle/2438/17617.
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This research addresses solving two types of Travelling Salesman Problems (TSP) which are the symmetric TSP (STSP) and the asymmetric TSP (ATSP). The TSP is a problem of finding a minimal length closed tour that visits each city once. If the distances between each pair of cities are the same in both directions, the problem is a STSP, otherwise, it is an ATSP. In this thesis, a new metaheuristic algorithm which is based on Ant Colony Optimization (ACO) is proposed to solve these problems. The key idea is to enhance the ability of exploration and exploitation by incorporating a metaheuristic approach with an exact method. A new strategy for creating 'Intelligent Ants' is introduced to construct the solution tours. This strategy aims at reducing the computational time by heuristically fixing part of the solution tour and improving the accuracy of the solutions through the usage of a solver, specifically for large size instances. Moreover, this proposed algorithm employs new ways of depositing and evaporating pheromone. A different approach of global updating of pheromone is proposed in which the pheromone is deposited only on the edges belonging to the colony-best ant and evaporated only on the edges belonging to the colony-worst ant that are not in the colony-best ant. Additionally, the parameters of the proposed algorithm which include the number of colonies, the number of ants in each colony, the relative influence of the pheromone trail α and the pheromone evaporation rate ρ are expressed as a function of the problem size. Comparisons with other sets of parameter values suggested in the literature have been investigated which illustrate the advantages of the choice of the proposed parameter settings. Further, in order to evaluate the performance of the proposed algorithm, a set of standard benchmark problems from the TSPLIB with up to 442 cities were solved and the results obtained were compared with other approaches from the literature. The proposed algorithm has proven to be competitive and shows better performance in 63% of the 16 algorithms in terms of solution quality and obtained the optimum solutions in 70% of the 33 instances, proving that it is a good alternative approach to solve these hard combinatorial optimisation problems.
Books on the topic "Ant colony sytem algorithm"
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Ant Colony Optimization Algorithm for Load Balancing in Grid Computing. Penerbit Universiti Utara Malaysia, 2012.
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Ryoo, Jean J., Jane Margolis, and Charis JB. Power On! The MIT Press, 2022. http://dx.doi.org/10.7551/mitpress/14166.001.0001.
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A diverse group of teenage friends learn how computing can be personally and politically empowering and why all students need access to computer science education. This lively graphic novel follows a diverse group of teenage friends as they discover that computing can be fun, creative, and empowering. Taylor, Christine, Antonio, and Jon seem like typical young teens—they communicate via endless texting, they share jokes, they worry about starting high school, and they have each other's backs. But when a racially-biased artificial intelligence system causes harm in their neighborhood, they suddenly realize that tech isn't as neutral as they thought it was. But can an algorithm be racist? And what is an algorithm, anyway? In school, they decide to explore computing classes, with mixed results. One class is only about typing. The class that Christine wants to join is full, and the school counselor suggests that she take a class in “Tourism and Hospitality” instead. (Really??) But Antonio's class seems legit, Christine finds an after-school program, and they decide to teach the others what they learn. By summer vacation, all four have discovered that computing is both personally and politically empowering. Interspersed through the narrative are text boxes with computer science explainers and inspirational profiles of people of color and women in the field (including Katherine Johnson of Hidden Figures fame). Power On! is an essential read for young adults, general readers, educators, and anyone interested in the power of computing, how computing can do good or cause harm, and why addressing underrepresentation in computing needs to be a top priority.
Book chapters on the topic "Ant colony sytem algorithm"
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Cheng, Ni, and Anli Teekaraman. "Urban Ecotourism Evaluation System Based on Ant Colony Algorithm." In Lecture Notes on Data Engineering and Communications Technologies. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28893-7_12.
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Dong, Gaifang, and William W. Guo. "A Cooperative Ant Colony System and Genetic Algorithm for TSPs." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13495-1_73.
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He, Jian-min, Rui Min, and Yuan-yuan Wang. "Implementation of Ant Colony Algorithm Based-On Multi-agent System." In Networking and Mobile Computing. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11534310_129.
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Ma, Deyong, and Jun Wang. "Practice System of Ant Colony Optimization Algorithm in Business Administration." In New Approaches for Multidimensional Signal Processing. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-7842-5_15.
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Guallichico, Ruben, and William Montalvo. "Identification of a Ball-Plate System Using Ant Colony Algorithm." In Lecture Notes in Electrical Engineering. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08280-1_1.
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Pérez-Delgado, M. L., and J. Escuadra Burrieza. "A Post-optimization Method to Improve the Ant Colony System Algorithm." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_60.
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Shi, Jing, and Li Tao. "Design of English Machine Translation System Based on Ant Colony Algorithm." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-6318-4_30.
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Yang, Yong. "Optimization Design of Optical Film System Based on Ant Colony Algorithm." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-9416-8_8.
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Deng, Hongwei, Jiahao Duan, and Xinjun Liu. "Design of Intelligent Light Control System with Improved Ant Colony Algorithm." In Sustainable Civil Infrastructures. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-78276-3_10.
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Liao, Jianjun, Jianhui Chen, Xiaoming Liu, and Xiaoning Li. "Semantic Video Retrieval System Based on Ant Colony Algorithm and Relevant Feedback." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24273-1_43.
Full textConference papers on the topic "Ant colony sytem algorithm"
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Wang, Yuqi, Zhenyuan Zhang, Zheng Wang, and Yuesheng Xian. "An Ant Colony Optimization-Enhanced LightGBM Algorithm." In 2024 IEEE/IAS Industrial and Commercial Power System Asia (I&CPS Asia). IEEE, 2024. https://doi.org/10.1109/icpsasia61913.2024.10761910.
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Wang, Jingfeng, Minggong Wu, Xiangxi Wen, Zhifang Chen, Lei Wu, and Liudong Pu. "Improved ant colony algorithm-based research on UAV trajectory planning." In Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), edited by Xiantao Xiao and Jia Yao. SPIE, 2024. https://doi.org/10.1117/12.3054883.
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Shen, Feng, Lingdan Shi, and Changguo Ke. "A fault diagnosis method of electric propulsion system based on ant colony algorithm." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039877.
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Jia, Yanling, and Yao Xing. "Design of Human Resource Management System Based on Ant Colony Algorithm." In 2024 IEEE International Conference on Information Technology, Electronics and Intelligent Communication Systems (ICITEICS). IEEE, 2024. http://dx.doi.org/10.1109/iciteics61368.2024.10625203.
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He, Xiaolin, and Yan Wang. "Research and Implementation of Logistics Distribution System Based on Ant Colony Algorithm." In 2024 First International Conference on Software, Systems and Information Technology (SSITCON). IEEE, 2024. https://doi.org/10.1109/ssitcon62437.2024.10796838.
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Liu, Shen, Yong Zeng, XiaoBo Xu, and YaFei Wang. "Ant colony algorithm-based path planning for drone cargo transportation in remote areas." In Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), edited by Xiantao Xiao and Jia Yao. SPIE, 2024. https://doi.org/10.1117/12.3054606.
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XianMin Wei. "Clustering processing ant colony algorithm." In 2010 Second Pacific-Asia Conference on Circuits,Communications and System (PACCS). IEEE, 2010. http://dx.doi.org/10.1109/paccs.2010.5626990.
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Hu, Xiayun, and Yanfei Zhu. "Researches and Applications of Ant Colony Algorithm." In 2nd International Conference on Computer Application and System Modeling. Atlantis Press, 2012. http://dx.doi.org/10.2991/iccasm.2012.219.
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Shao, Ming, and Xianghong Xu. "Edge detection using ant colony system algorithm." In Fourth International Conference on Digital Image Processing (ICDIP 2012), edited by Mohamed Othman, Sukumar Senthilkumar, and Xie Yi. SPIE, 2012. http://dx.doi.org/10.1117/12.952480.
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Ming-Wei Zhang, Xue-Mei Sun, and Xiao-Yu Lv. "A QoS routing algorithm based on Culture-Ant Colony Algorithm." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5622234.
Full textReports on the topic "Ant colony sytem algorithm"
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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.
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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detection, refractometer and a scale (mass). Data were analyzed and provided input for five classification models. Chlorophyll from fluorescence was found to give the best estimation for ripeness stage while the combination of machine vision and firmness from impact performed best for quality sorting. A new algorithm was developed to estimate and minimize training size for supervised classification. A new criteria was established to choose a training set such that a recurrent auto-associative memory neural network is stabilized. Moreover, this method provides for rapid and accurate updating of the classifier over growing seasons, production environments and cultivars. Different classification approaches (parametric and non-parametric) for grading were examined. Statistical methods were found to be as accurate as neural networks in grading. Classification models by voting did not enhance the classification significantly. A hybrid model that incorporated heuristic rules and either a numerical classifier or neural network was found to be superior in classification accuracy with half the required processing of solely the numerical classifier or neural network. In Israel: A multi-sensing approach utilizing non-destructive sensors was developed. Shape, color, stem identification, surface defects and bruises were measured using a color image processing system. Flavor parameters (sugar, acidity, volatiles) and ripeness were measured using a near-infrared system and an electronic sniffer. Mechanical properties were measured using three sensors: drop impact, resonance frequency and cyclic deformation. Classification algorithms for quality sorting of fruit based on multi-sensory data were developed and implemented. The algorithms included a dynamic artificial neural network, a back propagation neural network and multiple linear regression. Results indicated that classification based on multiple sensors may be applied in real-time sorting and can improve overall classification. Advanced image processing algorithms were developed for shape determination, bruise and stem identification and general color and color homogeneity. An unsupervised method was developed to extract necessary vision features. The primary advantage of the algorithms developed is their ability to learn to determine the visual quality of almost any fruit or vegetable with no need for specific modification and no a-priori knowledge. Moreover, since there is no assumption as to the type of blemish to be characterized, the algorithm is capable of distinguishing between stems and bruises. This enables sorting of fruit without knowing the fruits' orientation. A new algorithm for on-line clustering of data was developed. The algorithm's adaptability is designed to overcome some of the difficulties encountered when incrementally clustering sparse data and preserves information even with memory constraints. Large quantities of data (many images) of high dimensionality (due to multiple sensors) and new information arriving incrementally (a function of the temporal dynamics of any natural process) can now be processed. Furhermore, since the learning is done on-line, it can be implemented in real-time. The methodology developed was tested to determine external quality of tomatoes based on visual information. An improved model for color sorting which is stable and does not require recalibration for each season was developed for color determination. Excellent classification results were obtained for both color and firmness classification. Results indicted that maturity classification can be obtained using a drop-impact and a vision sensor in order to predict the storability and marketing of harvested fruits. In conclusion: We have been able to define quantitatively the critical parameters in the quality sorting and grading of both fresh market cantaloupes and tomatoes. We have been able to accomplish this using nondestructive measurements and in a manner consistent with expert human grading and in accordance with market acceptance. This research constructed and used large databases of both commodities, for comparative evaluation and optimization of expert system, statistical and/or neural network models. The models developed in this research were successfully tested, and should be applicable to a wide range of other fruits and vegetables. These findings are valuable for the development of on-line grading and sorting of agricultural produce through the incorporation of multiple measurement inputs that rapidly define quality in an automated manner, and in a manner consistent with the human graders and inspectors.
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Lee, W. S., Victor Alchanatis, and Asher Levi. Innovative yield mapping system using hyperspectral and thermal imaging for precision tree crop management. United States Department of Agriculture, 2014. http://dx.doi.org/10.32747/2014.7598158.bard.
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Original objectives and revisions – The original overall objective was to develop, test and validate a prototype yield mapping system for unit area to increase yield and profit for tree crops. Specific objectives were: (1) to develop a yield mapping system for a static situation, using hyperspectral and thermal imaging independently, (2) to integrate hyperspectral and thermal imaging for improved yield estimation by combining thermal images with hyperspectral images to improve fruit detection, and (3) to expand the system to a mobile platform for a stop-measure- and-go situation. There were no major revisions in the overall objective, however, several revisions were made on the specific objectives. The revised specific objectives were: (1) to develop a yield mapping system for a static situation, using color and thermal imaging independently, (2) to integrate color and thermal imaging for improved yield estimation by combining thermal images with color images to improve fruit detection, and (3) to expand the system to an autonomous mobile platform for a continuous-measure situation. Background, major conclusions, solutions and achievements -- Yield mapping is considered as an initial step for applying precision agriculture technologies. Although many yield mapping systems have been developed for agronomic crops, it remains a difficult task for mapping yield of tree crops. In this project, an autonomous immature fruit yield mapping system was developed. The system could detect and count the number of fruit at early growth stages of citrus fruit so that farmers could apply site-specific management based on the maps. There were two sub-systems, a navigation system and an imaging system. Robot Operating System (ROS) was the backbone for developing the navigation system using an unmanned ground vehicle (UGV). An inertial measurement unit (IMU), wheel encoders and a GPS were integrated using an extended Kalman filter to provide reliable and accurate localization information. A LiDAR was added to support simultaneous localization and mapping (SLAM) algorithms. The color camera on a Microsoft Kinect was used to detect citrus trees and a new machine vision algorithm was developed to enable autonomous navigations in the citrus grove. A multimodal imaging system, which consisted of two color cameras and a thermal camera, was carried by the vehicle for video acquisitions. A novel image registration method was developed for combining color and thermal images and matching fruit in both images which achieved pixel-level accuracy. A new Color- Thermal Combined Probability (CTCP) algorithm was created to effectively fuse information from the color and thermal images to classify potential image regions into fruit and non-fruit classes. Algorithms were also developed to integrate image registration, information fusion and fruit classification and detection into a single step for real-time processing. The imaging system achieved a precision rate of 95.5% and a recall rate of 90.4% on immature green citrus fruit detection which was a great improvement compared to previous studies. Implications – The development of the immature green fruit yield mapping system will help farmers make early decisions for planning operations and marketing so high yield and profit can be achieved.
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Alchanatis, Victor, Stephen W. Searcy, Moshe Meron, W. Lee, G. Y. Li, and A. Ben Porath. Prediction of Nitrogen Stress Using Reflectance Techniques. United States Department of Agriculture, 2001. http://dx.doi.org/10.32747/2001.7580664.bard.
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Commercial agriculture has come under increasing pressure to reduce nitrogen fertilizer inputs in order to minimize potential nonpoint source pollution of ground and surface waters. This has resulted in increased interest in site specific fertilizer management. One way to solve pollution problems would be to determine crop nutrient needs in real time, using remote detection, and regulating fertilizer dispensed by an applicator. By detecting actual plant needs, only the additional nitrogen necessary to optimize production would be supplied. This research aimed to develop techniques for real time assessment of nitrogen status of corn using a mobile sensor with the potential to regulate nitrogen application based on data from that sensor. Specifically, the research first attempted to determine the system parameters necessary to optimize reflectance spectra of corn plants as a function of growth stage, chlorophyll and nitrogen status. In addition to that, an adaptable, multispectral sensor and the signal processing algorithm to provide real time, in-field assessment of corn nitrogen status was developed. Spectral characteristics of corn leaves reflectance were investigated in order to estimate the nitrogen status of the plants, using a commercial laboratory spectrometer. Statistical models relating leaf N and reflectance spectra were developed for both greenhouse and field plots. A basis was established for assessing nitrogen status using spectral reflectance from plant canopies. The combined effect of variety and N treatment was studied by measuring the reflectance of three varieties of different leaf characteristic color and five different N treatments. The variety effect on the reflectance at 552 nm was not significant (a = 0.01), while canonical discriminant analysis showed promising results for distinguishing different variety and N treatment, using spectral reflectance. Ambient illumination was found inappropriate for reliable, one-beam spectral reflectance measurement of the plants canopy due to the strong spectral lines of sunlight. Therefore, artificial light was consequently used. For in-field N status measurement, a dark chamber was constructed, to include the sensor, along with artificial illumination. Two different approaches were tested (i) use of spatially scattered artificial light, and (ii) use of collimated artificial light beam. It was found that the collimated beam along with a proper design of the sensor-beam geometry yielded the best results in terms of reducing the noise due to variable background, and maintaining the same distance from the sensor to the sample point of the canopy. A multispectral sensor assembly, based on a linear variable filter was designed, constructed and tested. The sensor assembly combined two sensors to cover the range of 400 to 1100 nm, a mounting frame, and a field data acquisition system. Using the mobile dark chamber and the developed sensor, as well as an off-the-shelf sensor, in- field nitrogen status of the plants canopy was measured. Statistical analysis of the acquired in-field data showed that the nitrogen status of the com leaves can be predicted with a SEP (Standard Error of Prediction) of 0.27%. The stage of maturity of the crop affected the relationship between the reflectance spectrum and the nitrogen status of the leaves. Specifically, the best prediction results were obtained when a separate model was used for each maturity stage. In-field assessment of the nitrogen status of corn leaves was successfully carried out by non contact measurement of the reflectance spectrum. This technology is now mature to be incorporated in field implements for on-line control of fertilizer application.
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Ruiz, Pablo, Craig Perry, Alejando Garcia, et al. The Everglades National Park and Big Cypress National Preserve vegetation mapping project: Interim report—Northwest Coastal Everglades (Region 4), Everglades National Park (revised with costs). National Park Service, 2020. http://dx.doi.org/10.36967/nrr-2279586.
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The Everglades National Park and Big Cypress National Preserve vegetation mapping project is part of the Comprehensive Everglades Restoration Plan (CERP). It is a cooperative effort between the South Florida Water Management District (SFWMD), the United States Army Corps of Engineers (USACE), and the National Park Service’s (NPS) Vegetation Mapping Inventory Program (VMI). The goal of this project is to produce a spatially and thematically accurate vegetation map of Everglades National Park and Big Cypress National Preserve prior to the completion of restoration efforts associated with CERP. This spatial product will serve as a record of baseline vegetation conditions for the purpose of: (1) documenting changes to the spatial extent, pattern, and proportion of plant communities within these two federally-managed units as they respond to hydrologic modifications resulting from the implementation of the CERP; and (2) providing vegetation and land-cover information to NPS park managers and scientists for use in park management, resource management, research, and monitoring. This mapping project covers an area of approximately 7,400 square kilometers (1.84 million acres [ac]) and consists of seven mapping regions: four regions in Everglades National Park, Regions 1–4, and three in Big Cypress National Preserve, Regions 5–7. The report focuses on the mapping effort associated with the Northwest Coastal Everglades (NWCE), Region 4 , in Everglades National Park. The NWCE encompasses a total area of 1,278 square kilometers (493.7 square miles [sq mi], or 315,955 ac) and is geographically located to the south of Big Cypress National Preserve, west of Shark River Slough (Region 1), and north of the Southwest Coastal Everglades (Region 3). Photo-interpretation was performed by superimposing a 50 × 50-meter (164 × 164-feet [ft] or 0.25 hectare [0.61 ac]) grid cell vector matrix over stereoscopic, 30 centimeters (11.8 inches) spatial resolution, color-infrared aerial imagery on a digital photogrammetric workstation. Photo-interpreters identified the dominant community in each cell by applying majority-rule algorithms, recognizing community-specific spectral signatures, and referencing an extensive ground-truth database. The dominant vegetation community within each grid cell was classified using a hierarchical classification system developed specifically for this project. Additionally, photo-interpreters categorized the absolute cover of cattail (Typha sp.) and any invasive species detected as either: Sparse (10–49%), Dominant (50–89%), or Monotypic (90–100%). A total of 178 thematic classes were used to map the NWCE. The most common vegetation classes are Mixed Mangrove Forest-Mixed and Transitional Bayhead Shrubland. These two communities accounted for about 10%, each, of the mapping area. Other notable classes include Short Sawgrass Marsh-Dense (8.1% of the map area), Mixed Graminoid Freshwater Marsh (4.7% of the map area), and Black Mangrove Forest (4.5% of the map area). The NWCE vegetation map has a thematic class accuracy of 88.4% with a lower 90th Percentile Confidence Interval of 84.5%.
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Estimation of Vehicle Miles Traveled Based on Improved Ant Colony Algorithm. SAE International, 2020. http://dx.doi.org/10.4271/2020-01-5195.
Full textAbstract:
Vehicle miles traveled (VMT) statistics is a key parameter which has many applications, such as the assessment of vehicle quality, evaluation of driving behavior and oil consumption, and other applications in vehicle monitoring system. In the earlier studies, the calculation of VMT usually focused on improving the accuracy and frequency of vehicle GPS data, but the VMT estimation error due to them were getting smaller with the development of positioning technology. Nowadays in the practical application of internet of vehicles, errors due to the out-of-order location data which caused by communication mechanism have become increasingly obvious. In this paper, we propose a VMT estimate method based on improved ant colony algorithm and local search method which is suitable for dealing with timestamp chaotic location data sequence. To evaluate our method, we use real-world vehicle data gathered by China mobile’s vehicle fleet management products, the analysis result shows the MRE of proposed ant colony algorithm is usually less than 8%, at least 3 percentage points lower than that of uniform motion distance accumulation statistics, at least 7 percentage points lower than that of Euclid distance accumulation statistics.
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Payment Systems Report - June of 2021. Banco de la República, 2022. http://dx.doi.org/10.32468/rept-sist-pag.eng.2021.
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Banco de la República provides a comprehensive overview of Colombia’s finan¬cial infrastructure in its Payment Systems Report, which is an important product of the work it does to oversee that infrastructure. The figures published in this edition of the report are for the year 2020, a pandemic period in which the con¬tainment measures designed and adopted to alleviate the strain on the health system led to a sharp reduction in economic activity and consumption in Colom¬bia, as was the case in most countries. At the start of the pandemic, the Board of Directors of Banco de la República adopted decisions that were necessary to supply the market with ample liquid¬ity in pesos and US dollars to guarantee market stability, protect the payment system and preserve the supply of credit. The pronounced growth in mone¬tary aggregates reflected an increased preference for liquidity, which Banco de la República addressed at the right time. These decisions were implemented through operations that were cleared and settled via the financial infrastructure. The second section of this report, following the introduction, offers an analysis of how the various financial infrastructures in Colombia have evolved and per¬formed. One of the highlights is the large-value payment system (CUD), which registered more momentum in 2020 than during the previous year, mainly be¬cause of an increase in average daily remunerated deposits made with Banco de la República by the General Directorate of Public Credit and the National Treasury (DGCPTN), as well as more activity in the sell/buy-back market with sovereign debt. Consequently, with more activity in the CUD, the Central Securi¬ties Depository (DCV) experienced an added impetus sparked by an increase in the money market for bonds and securities placed on the primary market by the national government. The value of operations cleared and settled through the Colombian Central Counterparty (CRCC) continues to grow, propelled largely by peso/dollar non-deliverable forward (NDF) contracts. With respect to the CRCC, it is important to note this clearing house has been in charge of managing risks and clearing and settling operations in the peso/dollar spot market since the end of last year, following its merger with the Foreign Exchange Clearing House of Colombia (CCDC). Since the final quarter of 2020, the CRCC has also been re¬sponsible for clearing and settlement in the equities market, which was former¬ly done by the Colombian Stock Exchange (BVC). The third section of this report provides an all-inclusive view of payments in the market for goods and services; namely, transactions carried out by members of the public and non-financial institutions. During the pandemic, inter- and intra-bank electronic funds transfers, which originate mostly with companies, increased in both the number and value of transactions with respect to 2019. However, debit and credit card payments, which are made largely by private citizens, declined compared to 2019. The incidence of payment by check contin¬ue to drop, exhibiting quite a pronounced downward trend during the past last year. To supplement to the information on electronic funds transfers, section three includes a segment (Box 4) characterizing the population with savings and checking accounts, based on data from a survey by Banco de la República con-cerning the perception of the use of payment instruments in 2019. There also is segment (Box 2) on the growth in transactions with a mobile wallet provided by a company specialized in electronic deposits and payments (Sedpe). It shows the number of users and the value of their transactions have increased since the wallet was introduced in late 2017, particularly during the pandemic. In addition, there is a diagnosis of the effects of the pandemic on the payment patterns of the population, based on data related to the use of cash in circu¬lation, payments with electronic instruments, and consumption and consumer confidence. The conclusion is that the collapse in the consumer confidence in¬dex and the drop in private consumption led to changes in the public’s pay¬ment patterns. Credit and debit card purchases were down, while payments for goods and services through electronic funds transfers increased. These findings, coupled with the considerable increase in cash in circulation, might indicate a possible precautionary cash hoarding by individuals and more use of cash as a payment instrument. There is also a segment (in Focus 3) on the major changes introduced in regulations on the retail-value payment system in Colombia, as provided for in Decree 1692 of December 2020. The fourth section of this report refers to the important innovations and tech¬nological changes that have occurred in the retail-value payment system. Four themes are highlighted in this respect. The first is a key point in building the financial infrastructure for instant payments. It involves of the design and im¬plementation of overlay schemes, a technological development that allows the various participants in the payment chain to communicate openly. The result is a high degree of interoperability among the different payment service providers. The second topic explores developments in the international debate on central bank digital currency (CBDC). The purpose is to understand how it could impact the retail-value payment system and the use of cash if it were to be issued. The third topic is related to new forms of payment initiation, such as QR codes, bio¬metrics or near field communication (NFC) technology. These seemingly small changes can have a major impact on the user’s experience with the retail-value payment system. The fourth theme is the growth in payments via mobile tele¬phone and the internet. The report ends in section five with a review of two papers on applied research done at Banco de la República in 2020. The first analyzes the extent of the CRCC’s capital, acknowledging the relevant role this infrastructure has acquired in pro¬viding clearing and settlement services for various financial markets in Colom¬bia. The capital requirements defined for central counterparties in some jurisdic¬tions are explored, and the risks to be hedged are identified from the standpoint of the service these type of institutions offer to the market and those associated with their corporate activity. The CRCC’s capital levels are analyzed in light of what has been observed in the European Union’s regulations, and the conclusion is that the CRCC has a scheme of security rings very similar to those applied internationally and the extent of its capital exceeds what is stipulated in Colombian regulations, being sufficient to hedge other risks. The second study presents an algorithm used to identify and quantify the liquidity sources that CUD’s participants use under normal conditions to meet their daily obligations in the local financial market. This algorithm can be used as a tool to monitor intraday liquidity. Leonardo Villar Gómez Governor