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Data publikacji: 3 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

Feng, Yinda. "Ant colony for TSP." Thesis, Högskolan Dalarna, Datateknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4824.

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The aim of this work is to investigate Ant Colony Algorithm for the traveling salesman problem (TSP). Ants of the artificial colony are able to generate successively shorter feasible tours by using information accumulated in the form of a pheromone trail deposited on the edges of the TSP graph. This paper is based on the ideas of ant colony algorithm and analysis the main parameters of the ant colony algorithm. Experimental results for solving TSP problems with ant colony algorithm show great effectiveness.

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Angus, Daniel John. "Niching ant colony optimisation." Swinburne Research Bank, 2008. http://hdl.handle.net/1959.3/36804.

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Thesis (Ph.D) - Swinburne University of Technology, Faculty of Information & Communication Technologies, Complex Intelligent Systems Laboratory, 2008.<br>Submitted in partial fulfilment for the degree of Doctor of Philosophy, Complex Intelligent Systems Laboratory, Faculty of Information and Communication Technologies, Swinburne University of Technology, 2008. Typescript. Includes bibliographical references (p. 169.181).

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Krenzke, Tom (Tom Paul). "Ant colony optimization for agile motion planning." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/35292.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2006.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Includes bibliographical references (p. 67-69).<br>With the need for greater autonomy in unmanned vehicles growing, design of algorithms for mission-level planning becomes essential. The general field of motion planning for unmanned vehicles falls into this category. Of particular interest is the case of operating in hostile environments with unk

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4

Pettersson, Lars, and Johansson Christoffer Lundell. "Ant Colony Optimization - Optimal Number of Ants." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229764.

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The focus of this thesis paper is to study the impact the number of ants has on the found solution of the Ant Colony Optimization (ACO) metaheuristic when solving the Traveling Salesman Problem. The goal was to find out how the length of the computed tours change for different amounts of ants within a limited number of iterations. To study this, three well known versions of the ACO algorithm were implemented and tested: Min-Max Ant System (MMAS), Elitist Ant System (EliteAS) and Ranked Ant System (RankedAS). The results showed trends that were consistent over several test cases. EliteAS and Ra

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Renfrew, David T. "TRAFFIC SIGNAL CONTROL WITH ANT COLONY OPTIMIZATION." DigitalCommons@CalPoly, 2009. https://digitalcommons.calpoly.edu/theses/190.

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Traffic signal control is an effective way to improve the efficiency of traffic networks and reduce users’ delays. Ant Colony Optimization (ACO) is a metaheuristic based on the behavior of ant colonies searching for food. ACO has successfully been used to solve many NP-hard combinatorial optimization problems and its stochastic and decentralized nature fits well with traffic flow networks. This thesis investigates the application of ACO to minimize user delay at traffic intersections. Computer simulation results show that this new approach outperforms conventional fully actuated control under

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CHEN, Yijun. "Ant colony optimization approach for stacking configurations." Digital Commons @ Lingnan University, 2011. https://commons.ln.edu.hk/cds_etd/2.

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In data mining, classifiers are generated to predict the class labels of the instances. An ensemble is a decision making system which applies certain strategies to combine the predictions of different classifiers and generate a collective decision. Previous research has empirically and theoretically demonstrated that an ensemble classifier can be more accurate and stable than its component classifiers in most cases. Stacking is a well-known ensemble which adopts a two-level structure: the base-level classifiers to generate predictions and the meta-level classifier to make collective decisions.

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7

Kollin, Felix, and Adel Bavey. "Ant Colony Optimization Algorithms : Pheromone Techniques for TSP." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-208374.

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Ant Colony Optimization (ACO) uses behaviour observed in real-life ant colonies in order to solve shortest path problems. Short paths are found with the use of pheromones, which allow ants to communicate indirectly. There are numerous pheromone distribution techniques for virtual ant systems and this thesis studies two of the most well known, Elitist and Max-Min. Implementations of Elitist and Max-Min ACO algorithms were tested using instances of the Traveling Salesman Problem (TSP). The performance of the different techniques are compared with respect to runtime, iterations and approximation

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8

Blum, Christian. "Theoretical and practical aspects of ant colony optimization." Doctoral thesis, Universite Libre de Bruxelles, 2004. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211187.

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Combinatorial optimization problems are of high academical as well as practical importance. Many instances of relevant combinatorial optimization problems are, due to their dimensions, intractable for complete methods such as branch and bound. Therefore, approximate algorithms such as metaheuristics received much attention in the past 20 years. Examples of metaheuristics are simulated annealing, tabu search, and evolutionary computation. One of the most recent metaheuristics is ant colony optimization (ACO), which was developed by Prof. M. Dorigo (who is the supervisor of this thesis) and coll

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9

Sharkey, Jeffrey Allen. "Automated radio network design using ant colony optimization." Thesis, Montana State University, 2008. http://etd.lib.montana.edu/etd/2008/sharkey/SharkeyJ0508.pdf.

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Radio networks can provide reliable communication for rural intelligent transportation systems (ITS). Engineers manually design these radio networks by selecting tower locations and equipment while meeting a series of constraints such as coverage, bandwidth, maximum delay, and redundancy, all while minimizing network cost. As network size and constraints grow, the design process can quickly become overwhelming. In this thesis we model the network design problem (NDP) as a generalized Steiner tree-star (GSTS) problem. Any solution to the minimum Steiner tree (MST) problem on a constructed GSTS

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10

Schultze, Martin [Verfasser]. "Constructing Subtests Using Ant Colony Optimization / Martin Schultze." Berlin : Freie Universität Berlin, 2017. http://d-nb.info/1138980714/34.

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Askut, Ann Ahu. "Population-Based Ant Colony Optimization for Multivariate Microaggregation." NSUWorks, 2013. http://nsuworks.nova.edu/gscis_etd/81.

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Numerous organizations collect and distribute non-aggregate personal data for a variety of different purposes, including demographic and public health research. In these situations, the data distributor is responsible with the protection of the anonymity and personal information of individuals. Microaggregation is one of the most commonly used statistical disclosure control methods. In microaggregation, the set of original records is first partitioned into several groups. The records in the same group are similar to each other. The minimum number of records in each group is k. Each record is r

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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 ar

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Mavrovouniotis, Michalis. "Ant colony optimization in stationary and dynamic environments." Thesis, University of Leicester, 2013. http://hdl.handle.net/2381/27971.

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The ant colony optimization (ACO) metaheuristic is inspired by the foraging behaviour of real ant colonies. Similarly with other metaheuristics, ACO suffers from stagnation behaviour, where all ants construct the same solution from early stages. In result, the solution quality may be degraded because the population may get trapped on local optima. In this thesis, we propose a novel approach, called direct communication (DC) scheme, that helps ACO algorithms to escape from a local optimum if they get trapped. The experimental results on two routing problems showed that the DC scheme is effectiv

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Socha, Krzysztof. "Ant colony optimization for continuous and mixed-variable domains." Doctoral thesis, Universite Libre de Bruxelles, 2008. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/210533.

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In this work, we present a way to extend Ant Colony Optimization (ACO), so that it can be applied to both continuous and mixed-variable optimization problems. We demonstrate, first, how ACO may be extended to continuous domains. We describe the algorithm proposed, discuss the different design decisions made, and we position it among other metaheuristics.<p>Following this, we present the results of numerous simulations and testing. We compare the results obtained by the proposed algorithm on typical benchmark problems with those obtained by other methods used for tackling continuous optimizatio

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Shih, Pang-shi. "TRAFFIC SIGNAL CONTROL WITH SWAM INTELLIGENCE ANT COLONY OPTIMIZATION." DigitalCommons@CalPoly, 2013. https://digitalcommons.calpoly.edu/theses/1039.

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Traffic signal control with swam intelligence ant colony optimization Pang-shi Shih Ant colony optimization (ACO) is a meta-heuristic based on the indirect communication of a colony of artificial ants mediated by pheromone trails with collaboration and knowledge-sharing mechanism during their food-seeking process. ACO has been successfully applied to solve many NP-hard combinational optimization problems such as travel salesman problem, quadratic problem, just to name a few. In this research, we apply the ACO algorithm to the traffic signal control in order to minimize the user delay at a traf

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16

Laptik, Raimond. "Ant colony technologies for image processing." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2010. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2009~D_20100303_133726-51617.

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In this work ant colony technologies for image processing are analyzed. Modifications of Max-Min ant system for automatic image pre-processing are proposed. Image segmentation by multiple ant colonies technique based on pheromone competition is proposed. Modified ant system is implemented in FPGA and MicroBlaze core units influence on performance is analyzed.<br>Darbe nagrinėjamos skruzdžių kolonijų technologijos vaizdams apdoroti. Pasiūlomos max-min skruzdžių sistemos modifikacijos tinkamos automatizuoti pirminį vaizdų apdorojimą. Pristatoma vaizdų segmentavimo metodika grįsta skruzdžių kolon

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17

Burvall, Benjamin. "Improvement of Container Placement Using Multi-Objective Ant Colony Optimization." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-249709.

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High resource requirements on software containers lead to the need for cloud users to find an optimal placement for each container to maximize the resource utilization in the cloud environment. Previous methods have scheduled containers in a cloud environment, optimizing a single objective, both in theory and practice. This thesis presents a Multi-Objective Container Placement Ant Colony Optimization (MOCP-ACO) algorithm, which has not been previously researched. MOCP-ACO is a modified implementation of Ant Colony Optimization, known for solving similar optimization problems, and is compared t

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Riadi, I. C. J. "Cognitive Ant Colony Optimization : a new framework in swarm intelligence." Thesis, University of Salford, 2014. http://usir.salford.ac.uk/30721/.

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Ant Colony Optimization (ACO) algorithms which belong to metaheuristic algorithms and swarm intelligence algorithms have been the focus of much attention in the quest to solve optimization problems. These algorithms are inspired by colonies of ants foraging for food from their nest and have been considered state-of-art methods for solving both discrete and continuous optimization problems. One of the most important phases of ACO algorithms is the construction phase during which an ant builds a partial solution and develops a state transition strategy. There have been a number of studies on the

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19

Doerner, Karl, Richard F. Hartl, and Marc Reimann. "Ant colony optimization applied to the pickup and delivery problem." SFB Adaptive Information Systems and Modelling in Economics and Management Science, WU Vienna University of Economics and Business, 2000. http://epub.wu.ac.at/1434/1/document.pdf.

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In this paper we propose an ACO algorithm to optimize the total costs associated with the pickup and delivery of full truckloads under time window constraints in a hub network. We perform a thorough technical analysis of the ACO by comparing different pheromone decoding schemes, different visibility information and various population sizes. Furthermore we propose a post-optimization technique to improve the solutions. Our results show that appropriate data structures significantly improve the solution quality.<br>Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economi

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Shahi, Durlabh, and Ankit Gupta. "Forecasting Components Failure Using Ant Colony Optimization For Predictive Maintenance." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-42457.

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Failures are the eminent aspect of any machine and so is true for vehicle as it is one of the sophisticated machines of today’s time. Early detection of faults and prioritized maintenance is a necessity of vehicle manufactures as it enables them to reduce maintenance cost and increase customer satisfaction. In our research, we have proposed a method for processing Logged Vehicle Data (LVD) that uses Ant-Miner algorithm which is a Ant Colony Optimization (ACO) based Algorithm. It also utilizes processes like Feature engineering, Data preprocessing. We tried to explore the effectiveness of ACO f

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21

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

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22

Chen, Jiun-Shiun, and 陳俊勳. "An Ant Colony Optimization Clustering Algorithm." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/83304156993590898222.

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碩士<br>元智大學<br>工業工程與管理學系<br>92<br>Cluster analysis is a technique used to forecast and infer a great deal of data in the domain of data mining. Its major objective is to differentiate the data that have unknown categories. Decision manager can obtain the reference information through the result of cluster analysis. Therefore developing an efficient clustering algorithm is important for many applications. K-Means algorithm is commonly used to conduct clustering task since it can quickly cluster data. However, K-Means algorithm has many drawbacks when used to real world cluster problem.

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Tang, Chang Tai, and 張泰堂. "Timetable Scheduling Using Ant Colony Optimization." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/75121778428825122873.

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碩士<br>國立高雄應用科技大學<br>電子工程系<br>98<br>In a timetable scheduling problem, examination subjects must be slotted to certain times so as to avoid conflicting as well as meet some specific requirements. They are combinatorial optimization problems and exactly NP-Complete. Modern optimization methods have emerged. Tremendous efforts have been made in dealing with these problems in recent years. Methods and techniques such as Genetic Algorithms, Tabu Search techniques, Particle Swarm Optimization, and Neural Networks have been applied in tackling these problems. Ant Colony System, as a randomized search

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Wang, Chi-jer, and 王啟哲. "Topology Optimization of Structure Using Ant Colony Optimization." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/w43c9s.

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碩士<br>大同大學<br>機械工程學系(所)<br>95<br>The ant algorithm has been applied to solve the TSP, QAP, and VRP and there are only a few papers using it to solving problem of topology optimization. This study combines the topology optimization of structure with an ant algorithm that derives from specific pheromone and cooperation mechanism between ants. The best advantage of the ant algorithm is rapid convergence while the benefit of topology optimization can get rid of the subjective ideas of designers and provides them with unexpected results .The contribution of this paper is to integrate ant algorithm

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CHENG, Yung-Tsan, and 鄭永燦. "Utilize Ant Colony Optimization Theory to develop Ant Decision System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/83186317490035324610.

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鄭永燦. "Utilize Ant Colony Optimization Theory to develop Ant Decision System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/98698105772037936010.

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Sarangi, Sangita. "Optimization of Robot Motion Planning using Ant Colony Optimization." Thesis, 2011. http://ethesis.nitrkl.ac.in/2821/1/Binder1.pdf.

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Motion planning in robotics is a process to compute a collision free path between the initial and final configuration among obstacles. To plan a collision free path in the workspace, it would need to plan the motion of every point of its shaping according its degree of freedom. The motion of robot between obstacles is represented by a path in configuration space. It is an imaginary concept. Motion planning is aimed at enabling robots with capabilities of automatically deciding and executing a sequence motion in order to achieve a task without ollision with other objects in a given environme

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Chien-Ju, Wu, and 吳建儒. "GPU Accelerated Ant Colony Optimization using CUDA." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/34705736372354175402.

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碩士<br>國立彰化師範大學<br>資訊工程學系<br>101<br>Graph Processing Units (GPUs) have recently evolved into a super multi-core and a fully programmable architecture. In the CUDA programming model, the programmers can simply implement parallelism ideas of a task on GPUs. The purpose of this paper is to accelerate Ant Colony Optimization (ACO) for Traveling Salesman Problems (TSP) with GPUs. In this paper, we propose a new parallel method, which is called the Transition Condition Method. Experimental results are extensively compared and evaluated on the performance side and the solution quality side. The TSP pr

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Lu, De-Sian, and 盧德賢. "Edge Detection Improvement Using Ant Colony Optimization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/91818470030889298650.

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碩士<br>玄奘大學<br>資訊管理學系碩士班<br>94<br>Edge detection is important in further analyzing image content. However, traditional edge detection approaches always accompany with broken pieces and some important edges may then lose. In this paper, we propose an ant colony optimization based mechanism to compensate broken edges. The proposed procedure adopts several moving policies to reduce the computation time. Remainders of pheromone as compensable edges are acquired after finite iterations. Experimental results demonstrate the efficiency of our proposed edge detection improvement approach.

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Chiu, Yung-Yi, and 邱永益. "Applying Ant Colony Optimization to Data Association." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/97680944460605330433.

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碩士<br>大葉大學<br>電機工程學系<br>96<br>Targets tracking is an extremely important task in the radar system. By tracking technique, we can know the information such as the location and the dynamic of targets. To get the complete targets by analyzing the signal that obtained by detection module, and seek the corresponding relationship between them in a continuous dynamic in order to achieve the purpose of tracking. The key developments of this subject are data association techniques and maneuvering targets’ estimation algorithm. In this thesis, a systematic tracking mode is developed by using an adaptive

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Cheng, Ming-shun, and 鄭明順. "Dominant Point Detection Using Ant Colony Optimization." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/32545989509998974602.

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碩士<br>義守大學<br>工業工程與管理學系碩士班<br>94<br>Recently, the application of machine vision has used in our life widely. One of the applications of machine vision is object dominant point detection. In this paper, the object dominant point detection consists of four steps: (1) Image Pre-processing: thresholding is used to extract the object i need, and then noise is reduced and object contour is smoothed by closing and opening, respectively; (2) Contour Tracking: search for the contour of extracted object; (3) Break Point Detection: detect break points using freeman chain code, and (4) Dominant Point Det

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Chen, Wei-Hsiang, and 陳偉翔. "Fractal Image Compression using Ant Colony Optimization." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/48610850219290596789.

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碩士<br>義守大學<br>資訊工程學系碩士班<br>95<br>Due to the growth of computer science and internet, the information capacity of multimedia data is getting larger. We need a lot of storage space to store all kind of multimedia data, like audio, video, and image. If we don’t compress these multimedia data, it will be a serious load of the storage space and the transmission bandwidth. Therefore, it is an important topic to reduce the redundancy of multimedia data. Fractal Image Compression (FIC) is a kind of image compression technology. FIC possesses the advantages of resolution independence, high compression

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Yang, Min-Hao, and 楊閔皓. "SOPC Based Ant Colony Optimization Algorithm Design." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/50255562295566376033.

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碩士<br>淡江大學<br>電機工程學系碩士班<br>100<br>In this thesis, proposed ant colony algorithm based on a SOPC (System on a Programmable Chip) technique on the FPGA chip. In the design and implementation of ant colony algorithm based on a SOPC (System on a Programmable Chip) technique is applied to design two processing method: (1) Selecting path, (2) Path analysis. Selecting path belongs to the pre-processing of the ant colony algorithm takes a longer computing processing time, so design into a hardware circuit, in order to speed up processing. (2) path analysis will be to the C language software in the NIO

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Cheng, Chia-Hui, and 鄭佳惠. "Ant Colony Optimization For Storage Recombination Problems." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/2j6y2m.

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碩士<br>中原大學<br>資訊管理研究所<br>106<br>In a company, warehousing accounts for 20% of the operating costs, and picking operations account for 50% of storage costs. Therefore, storage through the reorganization can be effectively reused these spaces, thereby affecting the follow-up operation of the warehouse staff picking operation time. In this study, after the rearrangement of storage spaces, the optimal spatial applications are sorted out. By constructing the mathematical programming model of problems and using the ant algorithm to solve the storage and the reconstruction path problem. Within a reas

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Jena, Sthitaprajna, and Jyotiprakash Lakra. "Application of Ant Colony optimization for MANETS." Thesis, 2009. http://ethesis.nitrkl.ac.in/1321/1/project.pdf.

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All networks tend to become more and more complicated. They can be wired, with lots of routers, or wireless, with lots of mobile nodes… The problem remains the same: in order to get the best from the network, there is a need to find the shortest path. The more complicated the network is, the more difficult it is to manage the routes and indicate which one is the best. The Nature gives us a solution to find the shortest path. The ants, in their necessity to find food and brings it back to the nest, manage not only to explore a vast area, but also to indicate to their peers the location of the f

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Peng, Yu-Hsien, and 彭裕賢. "Optimization for High-Speed Machining Design Using Ant Colony Optimization." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/44510243255701027318.

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碩士<br>明新科技大學<br>工程管理研究所<br>96<br>Nowadays the enterprise in order to strives for the survival under the global steep competition, they must pursue the best efficiency regarding each work or the duty, and the production satisfies the product or the service which the customer needs in the shortest time. The high-speed cutting machine industry in order to maintain the competitive ability must shorten time of products design phase look for optimum design parameter, This research develops the algorithm by the ant colony optimization to take the acceleration search best solution. The Ant Colony

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Blackman, Anthony Curtis. "Ant colony optimization and rectilinear Steiner minimal trees." Thesis, 2006. http://hdl.handle.net/2429/17733.

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This paper consists of two distinct parts. In the first part, we introduce the Rectilinear Steiner Minimal Tree (RSMT) problem and describe the Ant Colony algorithm which we use to construct the RSMT. The development of an Ant Colony algorithm called AntCol Steiner is described and we create a working program of the algorithm using the Sun Microsystems Java programming language (see appendix A to H for details). We investigate the effectiveness of our algorithm by using AntCol Steiner to construct; and draw RSMT a given a random set of terminals. In the second part, we look at an applic

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Lee, Li-wei, and 李立薇. "Apply Ant Colony Optimization to Dynamic Scheduling Systems." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/10075277662878626876.

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碩士<br>逢甲大學<br>工業工程與系統管理學研究所<br>95<br>In practical scheduling environment, customer orders arrive one after one as time goes by. It is required to integrate the new coming order into the shop schedule with the scheduled jobs. Thus, a dynamical scheduling problem has been evolved. Job shop scheduling is the most complicated scheduling problem among various types of scheduling. It is considered to be a NP-Hard problem. Researchers have used approximation approach such as GA, Tabu search to solve job-shop problems. Ant colony approach proposed by Dorigo in 1992 has been applied to various schedul

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WANG, JIUN JIE, and 王俊傑. "Ant Colony Optimization Approach for Cell Formation Problem." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/87408697353600358239.

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碩士<br>大同大學<br>資訊經營研究所<br>91<br>The research is primarily to apply Ant Colony System to solve Cell Formation Problem (CFP). The proposed approach first converts the CFP problems into Travel Salesman Problem (TSP), then to seek the solution by utilizing Ant Colony System. A system called ANT-CFP has been developed to implement the approach. Finally, a comparative study was conducted with 25 cases from published literatures and the results are compared with them generated by two better known algorithms (ZODIAC and GA algorithm). From the result of the computational experiments, the proposed appro

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"Ant colony optimization based clustering for data partitioning." 2005. http://library.cuhk.edu.hk/record=b5892704.

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Woo Kwan Ho.<br>Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.<br>Includes bibliographical references (leaves 148-155).<br>Abstracts in English and Chinese.<br>Contents --- p.ii<br>Abstract --- p.iv<br>Acknowledgements --- p.vii<br>List of Figures --- p.viii<br>List of Tables --- p.x<br>Chapter Chapter 1 --- Introduction --- p.1<br>Chapter Chapter 2 --- Literature Reviews --- p.7<br>Chapter 2.1 --- Block Clustering --- p.7<br>Chapter 2.2 --- Clustering XML by structure --- p.10<br>Chapter 2.2.1 --- Definition of XML schematic information --- p.10<br>Chapter 2.2.2 --- Identi

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Lee, Yi-chan, and 李宜展. "Ant Colony Optimization for Task Matching and Scheduling." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/91492864391274825616.

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碩士<br>國立中山大學<br>資訊工程學系研究所<br>93<br>To realize efficient parallel processing, which is one of effective methods that deal with computing intensive applications, the technology of solving the problems of task matching and scheduling becomes extremely important. In this thesis, an Ant Colony Optimization (ACO) approach is employed for allocating task graphs onto a heterogeneous computing system. The approach uses a new state transition rule to reduce the time needed for finding a satisfactory solution. And a local search procedure is designed to improve the obtained solution. Furthermore, by appl

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Tu, Yi-Jung, and 杜宜蓉. "Evolving Ant Colony Optimization Using the Genetic Algorithm." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/92480337140980150298.

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碩士<br>立德管理學院<br>應用資訊研究所<br>95<br>Genetic algorithm (GA) and ant colony optimization (ACO) are the two of heuristic algorithms. The ACO is inspired from the biological behavior of real ants. It was developed as a viable approach with high performance for achieving stochastic combinatorial optimizations. Although the ACO is effective in solving the global optimization problems, there are many parameters, both explicit and implicit, affect the performance of the algorithms since the search processes of the two algorithms are nonlinear and complex. Therefore, the ACO with well-selected parameter s

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Chen, Chien-Hsun, and 陳建勛. "Ant Colony Optimization Based Extended Job Shop Scheduler." Thesis, 2003. http://ndltd.ncl.edu.tw/handle/28549130147343945674.

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碩士<br>國立臺灣大學<br>工業工程學研究所<br>91<br>Ant Colony Optimization（ACO）is the method to solve optimization problem by imitating the real ants’ behavior that find out the way from the starting point to the destination. Each ant drops the pheromone behind on the way, and then the successors follow the way with the most pheromone. The characteristic of ACO is that each test will keep the good solution previously and try to find the better one. This research tried to solve the job shop scheduling problem using ACO. There are a lot of kinds of type in job shop scheduling problem. The classical jo

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Merkle, Daniel, Martin Middendorf, and Hartmut Schmeck. "Ant colony optimization for resource-constrained project scheduling." 2002. https://ul.qucosa.de/id/qucosa%3A32033.

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An ant colony optimization (ACO) approach for the resource-constrained project scheduling problem (RCPSP) is presented. Several new features that are interesting for ACO in general are proposed and evaluated. In particular, the use of a combination of two pheromone evaluation methods by the ants to find new solutions, a change of the influence of the heuristic on the decisions of the ants during the run of the algorithm, and the option that an elitist ant forgets the best-found solution are studied. We tested the ACO algorithm on a set of large benchmark problems from the Project Scheduling Li

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Chan, Chuang-Lung, and 詹莊龍. "Ant Colony Optimization for On-line Scheduling Problem." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/31181890130826786138.

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碩士<br>元智大學<br>工業工程與管理學系<br>96<br>In the modern manufacturing environment, customer-order-driven has become the most popular production type. For those important orders, delay of the final product will lead to the degrading of the customer royalty and the business credibility. Also the early finished product will cost the company to find a warehouse to store the end-product before they are delivered to customers. Therefore it is important to assign appropriate due date to orders and to determine an efficient production scheduling simultaneously. Thus, this research presents a novel ant colony o

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Jyue-Hou and 侯爵. "Optimum Design of Structure by Ant Colony Optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/61487897206147409387.

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碩士<br>淡江大學<br>航空太空工程學系碩士班<br>100<br>The Ant Colony Optimization was applied to optimum structural design in this study. Ant Colony Optimization is to mimic the behavior of ants finding a good path to the food, which is one of the artificial biological algorithms. Therefore, it has the merits of global searching strategy without falling into local optimum. The structural optimization problem can be transformed into mathematical functions then the problem can be solved by using appropriate transition mechanism, and combined the path searching/updating of pheromone system. During the process of s

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Chia-HungLin and 林嘉宏. "Fuzzy Image Filter Design Using Ant Colony Optimization." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/73334362904253576694.

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碩士<br>國立成功大學<br>電機工程學系專班<br>100<br>The digital images are easily affected by the noises; hence the image filters are often regarded as pre-processing of image processing system. If the image has serious damage or high-noise, the traditional image filters are usually unable to handle well. Therefore, this thesis utilizes the advantages of the fuzzy system to improve the traditional median filter, and then use ant colony optimization (ACO) algorithm to adjust the parameters of fuzzy image filter and make the filter to achieve better performance. ACO algorithm is an optimal method that developed

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Yin, Yan-Yue, and 尹燕越. "Ant Colony Optimization System for Mold-Manufacturing Scheduling." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/38312221353824874298.

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碩士<br>中原大學<br>機械工程研究所<br>102<br>Plastics are used in an enormous and expanding range of products, especially consumer electronics, mold development speed will be more and more important. Mold manufacturing schedules are more complex Job-shop Scheduling Problem. Many factories already adopted work stations to increase the overall production capacity. Still use conventional job-shop scheduling system that can be applied well to multi-stage, single machine producing mode is not an effective way to use production resources. Consider parallel-machine producing mode and make appropriate scheduling,

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Wu, Tung-Yeh, and 吳東燁. "The Design and Implementation of Parallel Ant Colony Optimization." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/e2m474.

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碩士<br>銘傳大學<br>資訊工程學系碩士班<br>92<br>The Ant Colony Optimization (ACO) is a new meta-heuristic that is proposed by Dorigo et al. (1991) to solve hard combinatorial optimization problems. It is a population-base, nature-inspired approach and has been applied successfully to variety combinatorial optimization problems. As the structure of the ACO highly suggests a parallel implementation of the algorithm, we would like to explore the parallelism of ACO in this paper. The various alternatives of the parallelism of the computations and communications of ACO within a processor as well as among processo

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Chen, Jou-Chun, and 陳柔君. "Ant Colony Optimization for Identical Parallel Machine Scheduling problem." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/29109563283807139819.

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碩士<br>元智大學<br>工業工程與管理學系<br>93<br>ABSTRACT In PCB industries, the simple single machine scheduling problem has been fully investigated and no longer fulfills the sophisticated demands of production lines. Instead, the parallel machine type of production environment has become more popular nowadays. How to properly arrange the scheduling of jobs on parallel machines has attracted much research attention recently. The parallel machine scheduling problem is proved to be NP-Hard. Therefore, Meta-heuristics such as the focus of this research ant colony optimization has its merit on solving such com

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