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ant colony optimisation algorithm for detection and tracking of non-structured roads

ELECTRONICS LETTERS 2008年第12期44卷 725-726页

作者： Arnay, R. Acosta, L. Sigut, M. Toledo, J. Univ La Laguna Dept Syst Engn & Automat San Cristobal la Laguna 38204 Santa Cruz Tene Spain

An ant colony optimisation approach is proposed to address the problem of non-structured roads real-time detection and tracking by a self-guided electrical vehicle. The solution adopted tries to find some properties describing the probability that a pixel belongs to the boundaries of the road, and then formalises the road detection problem as an optimisation one.

关键词： electric vehicles image processing optimisation road vehicles tracking ant colony optimisation algorithm electrical vehicle nonstructured road detection nonstructured road tracking probability road detection problem tracking Optimization algorithms Land transportation road vehicles Road Electric vehicles Image processing ants ant algorithm

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A new approach for rebalancing of U-lines with stochastic task times using ant colony optimisation algorithm

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2014年第24期52卷 7262-7275页

作者： Celik, Erkan Kara, Yakup Atasagun, Yakup Yildiz Tech Univ Dept Ind Engn Mech Fac Istanbul Turkey Selcuk Univ Dept Ind Engn Fac Engn Konya Turkey

In real world, line balancing involves existing lines in existing factories and the line typically needs to be rebalanced rather than balanced. Rebalancing of a U-line can be defined as a changeover process from its initial configuration to a new configuration for a while due to the reasons such as demand variations, changes in product design and changes in task times, etc. This study defines U-line rebalancing problem with stochastic task times and proposes a solution procedure based on ant colony optimisation. The objective of the proposed algorithm is to minimise total cost of rebalancing which is the sum of task transposition costs, workstation opening/closing costs and operating costs of workstations for a particular planning horizon. A comprehensive experiment is conducted to generate problem instances and to compare rebalancing costs of U-lines by means of several factors. A total of 6600 rebalancing solutions are obtained and several comparisons are performed.

关键词： ant colony optimisation algorithm U-lines stochastic task times rebalancing

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A hybrid ant colony optimisation algorithm for job shop problems and its convergence analysis

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2015年第3期23卷 230-237页

作者： Cao, Yang Shi, Haibo Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Peoples R China Chinese Acad Sci Shenyang Inst Automat Dept Digital Factory Shenyang 110016 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Chinese Acad Sci Key Lab Networked Control Shenyang 110016 Peoples R China Shenyang Jianzhu Univ Fac Informat & Control Engn Shenyang 110168 Peoples R China

This paper presents a hybrid ant colony optimisation (HACO) algorithm for solving job shop problems. The criterion considered is the maximum completion time, the so-called makespan. The HACO algorithm improves the performance of intelligence optimisation algorithm, which adopts ant colony optimisation (ACO) algorithm to search in the global solution space, and tabu search (TS) algorithm is utilised as the local algorithm in each generation. The global asymptotic convergence of the hybrid algorithm is proved by Markov chain theory in the paper. By testing 13 hard benchmarks instance, the results demonstrate that the HACO algorithm is effective.

关键词： ant colony optimisation algorithm tabu search algorithm convergence analysis job shop problems JSP

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Free-form surface inspection path planning using improved ant colony optimisation algorithm

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ENGINEERING RESEARCH EXPRESS 2022年第3期4卷 035039-035039页

作者： Chen, Yueping Tan, Bo Guangxi Univ Sci & Technol Sch Mech & Automot Engn Liuzhou Peoples R China

To improve the inspection efficiency of free-form surfaces using coordinate measuring machines (CMMs), this paper proposes a free-form CMM inspection path optimization method based on an improved ant colony optimisation algorithm. The inspection path composition and its mathematical model are first analysed, and then the improved ant colony optimisation algorithm is applied to minimize the objective function. To address the problem that the ant colony optimisation algorithm has difficulty jumping out of local optimal solutions, this paper introduces a negative feedback mechanism in the pheromone update rule to improve the probability of the ant colony optimisation algorithm jumping out of the local optimal solution, so as to obtain the global optimal solution with a higher probability. Experiments showed that the inspection path length optimised by the improved ant colony optimisation algorithm was at least 5.2% and 8.6% shorter than those of the traditional ant colony optimisation and simulated annealing algorithms, respectively.

关键词： free-form surface path optimisation ant colony optimisation algorithm negative feedback mechanism

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Application of ant-colony-Optimization algorithm for improved management of first flush effects in urban wastewater systems

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SCIENCE OF THE TOTAL ENVIRONMENT 2014年第1期485卷 143-152页

作者： Verdaguer, M. Clara, N. Gutierrez, O. Poch, M. Univ Girona Dept Chem Engn Girona 17071 Spain Univ Girona Dept Comp Sci Appl Math & Stat Girona 17071 Spain Catalan Inst Water Res ICRA Girona 17003 Spain Univ Girona Inst Environm Lab Chem & Environm Engn LEQUIA Girona 17071 Spain

The first flush effect in combined sewer systems during storm events often causes overflows and overloads of the sewage treatment, which reduces the efficiency of the sewage treatment and decreases the quality of the receiving waters due to the pollutants that are contributed. The use of retention tanks constitutes a widely used way to mitigate this effect. However, the management of the pollutant loads encounters difficulties when the retention tanks are emptied. A new approach is proposed to solve this problem by fulfilling the treatment requirements in real time, focussing on the characteristics of the wastewater. The method is based on the execution of an ant colony optimisation algorithm to obtain a satisfactory sequence for the discharge of the retention tanks. The discharge sequence considers the volume of stormwater and its concentration of pollutants including Suspended Solids, Biological Oxygen Demand and Chemical Oxygen Demand, Total Nitrogen and Total Phosphorus. The ant colony optimisation algorithm was applied successfully to a case study with overall reduction of pollutant loads stored in retention tanks. The algorithm can be adapted in a simple way to the different scenarios, infrastructures and controllers of sewer systems. (C) 2014 Elsevier B.V. All rights reserved.

关键词： First flush Wastewater management Combined sewer system Urban wastewater system MAX-MIN ant System ant colony optimisation algorithm

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Electric Vehicle Power Consumption Modelling Method Based on Improved ant colony Optimization-Support Vector Regression

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ENERGIES 2024年第17期17卷 4339页

作者： Zhang, Jiaan Liu, Wenxin Wang, Zhenzhen Fan, Ruiqing Hebei Univ Technol State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300130 Peoples R China Hebei Univ Technol Sch Elect Engn Tianjin 300401 Peoples R China State Grid Tianjin Wuqing Elect Power Supply Co Tianjin 301700 Peoples R China

Accurate forecasting of electric vehicle (EV) power consumption per unit mileage serves as the cornerstone for determining diurnal variations in EV charging loads. To enhance the prediction accuracy of EV power consumption per unit mileage, this paper proposes a modelling method grounded in an improved ant colony Optimization-Support Vector Regression (ACO-SVR) framework. This method integrates the effects of both temperature and speed on the power consumption per unit mileage of EVs. Initially, we analyze the influence mechanism of driving speed and ambient temperature on EV power consumption, elucidating the relationship between power consumption per unit mileage and these factors. Subsequently, we construct an ACO-SVR model utilizing an improved ant colony optimization algorithm, fitting the relationship between power consumption, speed, and temperature to derive the EV power consumption per unit mileage model. Finally, leveraging operational data from EVs in Guangdong, Hong Kong, and Macao as a case study, we validate the energy consumption model of EVs by considering factors such as ambient temperature and driving speed. The results demonstrate that the model proposed in this paper is both accurate and effective.

关键词： electric vehicle power consumption per unit mile statistical methods ant colony optimisation algorithm support vector regression

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ant colony optimisation with elitist ant for sequencing problem in a mixed model assembly line

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2011年第15期49卷 4605-4626页

作者： Zhu, Qiong Zhang, Jie Shanghai Jiao Tong Univ Inst Comp Integrated Mfg Sch Mech Engn Shanghai 200240 Peoples R China

Optimised sequencing in the Mixed Model Assembly Line (MMAL) is a major factor to effectively balance the rate at which raw materials are used for production. In this paper we present an ant colony optimisation with Elitist ant (ACOEA) algorithm on the basis of the basic ant colony optimisation (ACO) algorithm. An ACOEA algorithm with the taboo search and elitist strategy is proposed to form an optimal sequence of multi-product models which can minimise deviation between the ideal material usage rate and the practical material usage rate. In this paper we compare applications of the ACOEA, ACO, and two other commonly applied algorithms (Genetic algorithm and Goal Chasing algorithm) to benchmark, stochastic problems and practical problems, and demonstrate that the use of the ACOEA algorithm minimised the deviation between the ideal material consumption rate and the practical material consumption rate under various critical parameters about multi-product models. We also demonstrate that the convergence rate for the ACOEA algorithm is significantly more than that for all the others considered.

关键词： mixed model assembly line sequencing ant colony optimisation algorithm elitist strategy

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An Artificial Bee colony algorithm for Minimum Weight Dominating Set

An Artificial Bee Colony Algorithm for Minimum Weight Domina...

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IEEE Symposium on Swarm Intelligence (SIS)

作者： Nitash, C. G. Singh, Alok Univ Hyderabad Sch Comp & Informat Sci Hyderabad 500046 Telangana India

ISBN: (纸本)9781479944583

The minimum weight dominating set (MWDS) problem is a classic NP-Hard optimisation problem with a wide range of practical applications. As a result, many algorithms have been proposed for this problem. Several greedy and approximation algorithms exist which provide good results for unit disk graphs with smooth weights. However, these algorithms do not perform well when applied to general graphs. There are a few metaheuristics in the literature such as genetic algorithms and ant colony optimisation algorithm, which also work for general graphs. In this paper, a swarm intelligence algorithm called artificial bee colony (ABC) algorithm is presented for the MWDS problem. The proposed ABC algorithm is compared with other metaheuristics in the literature and shown to perform better than any of these metaheuristics, both in terms of solution quality and time taken.

关键词： genetic algorithms graph theory set theory swarm intelligence ABC algorithm MWDS problem NP-hard optimisation problem ant colony optimisation algorithm artificial bee colony algorithm general graphs metaheuristics minimum weight dominating set swarm intelligence algorithm undirected graph algorithm design and analysis Approximation algorithms Genetic algorithms Maintenance engineering Optimization Sociology Statistics

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Selective Maintenance on a Multi-State Transportation System Considering Maintenance Sequence Arrangement

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IEEE ACCESS 2021年 9卷 70048-70060页

作者： Sun, Yao Sun, Zhili Northeastern Univ Sch Mech Engn & Automat Shenyang 110819 Peoples R China

The mission for a type of transportation system is to complete a certain transportation volume within a predetermined period, during which maintenance is also performed. In such a system, any unit selected to be maintained is often connected to the system to participate in the system operation immediately after its maintenance, and its participation in the system operation at different moments has different effects. Based on this consideration, this paper proposes a new selective maintenance model for a multi-state system wherein the maintenance sequence arrangement is considered. In this selective maintenance problem, to maximise the system reliability, a sub-set of all desired maintenance activities is selected, and the sequence of the selected maintenance activities to be performed is arranged, with the transportation volume requirement and the limited budget considered. An ant colony optimisation algorithm is tailored for the resulting optimisation problem. Two example analyses are presented to illustrate the effectiveness of the tailored ant colony optimisation algorithm and the effect of the proposed selective maintenance. The results show that the tailored ant colony optimisation algorithm is effective for the proposed selective maintenance model. This selective maintenance can significantly improve the system reliability when the predetermined period is relatively short, and this maintenance effect of improving the system reliability gradually weakens as the predetermined period becomes longer. Increasing the budget and decreasing the transportation volume requirement can slow this weakening of the maintenance effect.

关键词： Maintenance engineering Transportation Systems operation Optimization Load modeling Sun Markov processes ant colony optimisation algorithm maintenance sequence arrangement multi-state system selective maintenance

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Design of thinned fractal antenna arrays for adaptive beam forming and sidelobe reduction

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IET MICROWAVES antENNAS & PROPAGATION 2018年第3期12卷 435-441页

作者： El-Khamy, Said E. Eltrass, Ahmed S. El-Sayed, Huda F. Alexandria Univ Dept Elect Engn Alexandria 21544 Egypt Pharos Univ Dept Basic Sci Alexandria Egypt

This study introduces, for the first time, a new design methodology that combines the unique multi-band features of thinned fractal antenna arrays with the adaptive beamforming requirements. The major challenges of fractal array design are the high sidelobe level (SLL), the huge number of elements at higher-growth stages, and the radiation pattern synthesis. In this study, the ant colony optimisation algorithm is utilised for thinning fractal arrays by estimating the optimum combination of on' and off' elements corresponding to lowest possible SLL, while the least mean square algorithm is investigated as an adaptive beamforming method in the proposed design. The capability of the proposed design is demonstrated by investigating hexagonal and pentagonal fractal antenna arrays under various parameter regimes. The results show that the proposed design is much superior in terms of multi-band frequency operation, array element reduction, and beamforming accuracy. This reveals the effectiveness of the proposed technique as a promising design in smart antenna technology.

关键词： fractal antennas array signal processing antenna radiation patterns ant colony optimisation least mean squares methods adaptive antenna arrays thinned fractal antenna arrays adaptive beam forming method sidelobe reduction multiband features fractal array design high sidelobe level radiation pattern synthesis ant colony optimisation algorithm least mean square algorithm pentagonal fractal antenna arrays hexagonal fractal antenna arrays multiband frequency operation array element reduction smart antenna technology

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