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On how Pachycondyla apicalis ants suggest a new search algorithm

FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2000年第8期16卷 937-946页

作者： Monmarché, N Venturini, G Slimane, M Univ Tours Ecole Ingenieurs Informat Ind Lab Informat F-37200 Tours France

In this paper we present a new optimization algorithm based on a model of the foraging behavior of a population of primitive ants (Pachycondyla apicalis). These ants are characterized by a relatively simple but efficient strategy for prey search in which individuals hunt alone and try to cover a given area around their nest. The ant colony search behavior consists of a set of parallel local searches on hunting sites with a sensitivity to successful sites. Also, their nest is periodically moved. Accordingly, the proposed algorithm performs parallel random searches in the neighborhood of points called hunting sites. Hunting sites are created in the neighborhood of a point called nest. At constant intervals of time the nest is moved, which corresponds to a restart operator which re-initializes the parallel searches. We have applied this algorithm, called API, to numerical optimization problems with encouraging results. (C) 2000 Elsevier Science B.V.

关键词： pachycondyla apicalis ants foraging behavior numerical optimization ant algorithms

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ACO-Initialized Wavelet Neural Network for Vibration Fault Diagnosis of Hydroturbine Generating Unit

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MATHEMATICAL PROBLEMS IN ENGINEERING 2015年第1期2015卷 1-7页

作者： Xiao, Zhihuai He, Xinying Fu, Xiangqian Malik, O. P. Wuhan Univ Sch Power & Mech Engn Wuhan 430072 Hubei Peoples R China Univ Calgary Dept Elect & Comp Engn Calgary AB T2N 1N4 Canada

Considering the drawbacks of traditional wavelet neural network, such as low convergence speed and high sensitivity to initial parameters, an ant colony optimization- (ACO-) initialized wavelet neural network is proposed in this paper for vibration fault diagnosis of a hydroturbine generating unit. In this method, parameters of the wavelet neural network are initialized by the ACO algorithm, and then the wavelet neural network is trained by the gradient descent algorithm. Amplitudes of the frequency components of the hydroturbine generating unit vibration signals are used as feature vectors for wavelet neural network training to realize mapping relationship from vibration features to fault types. A real vibration fault diagnosis case result of a hydroturbine generating unit shows that the proposed method has faster convergence speed and stronger generalization ability than the traditional wavelet neural network and ACO wavelet neural network. Thus it can provide an effective solution for online vibration fault diagnosis of a hydroturbine generating unit.

关键词： TURBINE generators ant algorithms WAVELETS (Mathematics) NEURAL networks (Computer science) DEBUGGING in computer science

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Particle Swarm and Bacterial Foraging Inspired Hybrid Artificial Bee Colony Algorithm for Numerical Function Optimization

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-10页

作者： Mao, Li Mao, Yu Zhou, Changxi Li, Chaofeng Wei, Xiao Yang, Hong Jiangnan Univ Sch Internet Things Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Jiangsu Peoples R China Univ Chinese Acad Sci Lab Computat Geodynam Beijing 100049 Peoples R China Chinese Acad Fishery Sci Freshwater Fisheries Res Ctr Wuxi 214081 Jiangsu Peoples R China

Artificial bee colony (ABC) algorithm has good performance in discovering the optimal solutions to difficult optimization problems, but it has weak local search ability and easily plunges into local optimum. In this paper, we introduce the chemotactic behavior of Bacterial Foraging Optimization into employed bees and adopt the principle of moving the particles toward the best solutions in the particle swarm optimization to improve the global search ability of onlooker bees and gain a hybrid artificial bee colony (HABC) algorithm. To obtain a global optimal solution efficiently, we make HABC algorithm converge rapidly in the early stages of the search process, and the search range contracts dynamically during the late stages. Our experimental results on 16 benchmark functions of CEC 2014 show that HABC achieves significant improvement at accuracy and convergence rate, compared with the standard ABC, best-so-far ABC, directed ABC, Gaussian ABC, improved ABC, and memetic ABC algorithms.

关键词： PARTICLE swarm optimization ant algorithms NUMERICAL functions MATHEMATICAL optimization STOCHASTIC convergence

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Revisiting wavefront construction with collective agents: an approach to foraging

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SWARM INTELLIGENCE 2014年第2期8卷 113-138页

作者： Simonin, Olivier Charpillet, Francois Thierry, Eric INSA Lyon CITI Inria Lab Villeurbanne France Maia Team LORIA Lab Inria Nancy Grand Est Nancy France ENS Lyon Lyon France

We consider the problem of coordinating a team of agents that have to collect disseminated resources in an unknown environment. We are interested in approaches in which agents collectively explore the environment and build paths between home and resources. The originality of our approach is to simultaneously build an artificial potential field (APF) around the agents' home while foraging. We propose a multi-agent model defining a distributed and asynchronous version of Barraquand et al. Wavefront algorithm. Agents need only to mark and read integers locally on a grid, that is, their environment. We prove that the construction converges to the optimal APF. This allows the definition of a complete parameter-free foraging algorithm, called c-marking agents. The algorithm is evaluated by simulation, while varying the foraging settings. Then we compare our approach to a pheromone-based algorithm. Finally, we discuss requirements for implementation in robotics.

关键词： Swarm algorithm Foraging task Artificial potential field ant algorithms

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Real-Time Gate Reassignment Based on Flight Delay Feature in Hub Airport

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-10页

作者： Wang, Huawei Luo, Yuxiao Shi, Zhijian Nanjing Univ Aeronaut & Astronaut Coll Civil Aviat Nanjing 210016 Jiangsu Peoples R China

Appropriate gate reassignment is crucially important in efficiency improvement on airport sources and service quality of travelers. The paper divides delay flight into certain delay time flight and uncertain delay time flight based on flight delay feature. The main objective functions of model are to minimize the disturbance led by gate reassignment in the case of certain delay time flight and uncertain delay time flight, respectively. Another objective function of model is to build penalty function when the gate reassignment of certain delay time flight influences uncertain delay time flight. ant colony algorithm (ACO) is presented to simulate and verify the effectiveness of the model. The comparison between simulation result and artificial assignment shows that the result coming from ACO is obvious prior to the result coming from artificial assignment. The maximum disturbance of gate assignment is decreased by 13.64%, and the operation time of ACO is 118 s. The results show that the strategy of gate reassignment is feasible and effective.

关键词： REAL-time control FLIGHT delays & cancellations (Airlines) ant algorithms TIME delay systems SIMULATION methods & models QUALITY of service

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An Integrated Multiechelon Logistics Model with Uncertain Delivery Lead Time and Quality Unreliability

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MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-13页

作者： Yang, Ming-Feng Lin, Yi Ho, Li Hsing Kao, Wei Feng Natl Taiwan Ocean Univ Dept Transportat Sci 2 Beining Rd Keelung 202 Taiwan Natl Taipei Univ Technol Grad Inst Ind & Business Management 1Sect 3Zhongxiao E Rd Taipei 106 Taiwan Chung Hua Univ Dept Technol Management 707Sect 2Wufu Rd Hsinchu 30012 Taiwan Chung Hua Univ Ph D Program Technol Management 707Sect 2Wufu Rd Hsinchu 30012 Taiwan

Nowadays, in order to achieve advantages in supply chain management, how to keep inventory in adequate level and how to enhance customer service level are two critical practices for decision makers. Generally, uncertain lead time and defective products have much to do with inventory and service level. Therefore, this study mainly aims at developing a multiechelon integrated just-in-time inventory model with uncertain lead time and imperfect quality to enhance the benefits of the logistics model. In addition, the ant Colony Algorithm (ACA) is established to determine the optimal solutions. Moreover, based on our proposed model and analysis, the ACA is more efficient than Particle Swarm Optimization (PSO) and Lingo in SMEIJI model. An example is provided in this study to illustrate how production run and defective rate have an effect on system costs. Finally, the results of our research could provide some managerial insights which support decision makers in real-world operations.

关键词： SUPPLY chain management INVENTORY management systems DELIVERY of goods QUALITY of products DECISION making ant algorithms PARTICLE swarm optimization

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Using the ACS Approach to Solve Continuous Mathematical Problems in Engineering

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-7页

作者： Wu, Min-Thai Hong, Tzung-Pei Lee, Chung-Nan Natl Sun Yat Sen Univ Dept Comp Sci & Engn Kaohsiung 80424 Taiwan Natl Univ Kaohsiung Dept Comp Sci & Informat Engn Kaohsiung 81148 Taiwan

ant colony system (ACS) has been widely applied for solving discrete domain problems in recent years. In particular, they are efficient and effective in finding nearly optimal solutions to discrete search spaces. Because of the restriction of ant-based algorithms, when the solution space of a problem to be solved is continuous, it is not so appropriate to use the original ACS to solve it. However, engineering mathematics in the real applications are always applied in the continuous domain. This paper thus proposes an extended ACS approach based on binary-coding to provide a standard process for solving problems with continuous variables. It first encodes solution space for continuous domain into a discrete binary-coding space (searching map), and a modified ACS can be applied to find the solution. Each selected edge in a complete path represents a part of a candidate solution. Different from the previous ant-based algorithms for continuous domain, the proposed binary coding ACS (BCACS) could retain the original operators and keep the benefits and characteristics of the traditional ACS. Besides, the proposed approach is easy to implement and could be applied in different kinds of problems in addition to mathematical problems. Several constrained functions are also evaluated to demonstrate the performance of the proposed algorithm.

关键词： ant algorithms DISCRETE systems CODING theory PROBLEM solving CONTINUOUS functions

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Pherographs and other hidden landscapes

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INTERNATIONAL JOURNAL OF ARTS AND TECHNOLOGY 2015年第2期8卷 132-166页

作者： Fernandes, Carlos M. Univ Tecn Lisboa Syst & Robot Inst Evolutionary Syst & Biomed Engn Lab Ave Rovisco Pais 1 Lisbon Portugal

Due to some of their traits (non-linearity, emergent behaviour, self-organisation), complex systems raised the interest of artists and theorists and went beyond a scientific framework, entering the realm of visual arts. Art with complex systems is usually referred to as artificial (or generative) art. This paper discusses pherographia, a term that describes the creative use of an artificial intelligence model based on the concepts of stigmergy and cooperation amongst social insects. The system is dynamic, interacts with different types of environment, and reflects properties of insects' societies such as self-organisation, memory and adaptability to changes. Pherographia is addressed from its genesis as a swarm model to its use as an artificial art tool and metaphor for creating a figurative and abstract body-of-work that has been presented to a heterogeneous audience. Motivation and details of the artworks are discussed, as well as their links to artificial art, digital art and photography.

关键词： generative art ant algorithms pherographia arts and technology

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Optimization of UAV Team Routes in the Presence of Alternative and Dynamic Depots

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CYBERNETICS AND SYSTEMS ANALYSIS 2020年第2期56卷 195-203页

作者： Horbulin, V. P. Hulianytskyi, L. F. Sergienko, I. V. Natl Acad Sci Ukraine Kiev Ukraine Natl Acad Sci Ukraine VM Glushkov Inst Cybernet Kiev Ukraine

The paper considers route optimization problems for unmanned aerial vehicles (UAV), which act as a team when inspecting or supporting a given set of objects in the presence of alternative and dynamic depots (starting and/or landing sites) and resource constraints. Problem definition and mathematical models are proposed. Such problems, in particular, include UAV flight planning problems, which use mobile platforms as a depot. The optimization criteria are both the total length of the routes and the number of UAVs involved. algorithms for solving formulated combinatorial optimization problems based on ant colony optimization, tabu search, and exhaustive search have been developed and implemented. The results of the computational experiment are presented.

关键词： route optimization UAV ant algorithms dynamic depot tabu search gremlins

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A fast algorithm for image registration

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COMPTES RENDUS MATHEMATIQUE 2008年第9-10期346卷 593-598页

作者： Fehrenbach, Jerome Masmoudi, Mohamed Univ Toulouse Inst Math F-31062 Toulouse 09 France

An algorithm is presented here to estimate a smooth motion at a high frame rate. It is derived from the non-linear constant brightness assumption. A hierarchical approach reduces the dimension of the space of admissible displacements, hence the number of unknown parameters is small compared to the size of the data. The optimal displacement is estimated by a Gauss-Newton method, and the matrix required at each step is assembled rapidly using a finite-element method.

关键词： algorithms ALGEBRA ARITHMETIC -- Foundations COMPUTER programming ant algorithms

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