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VLSI Placement Problem Based on Ant Colony Optimization algorithm 1

5th Computer Science On-line Conference (CSOC)

作者： Zaruba, Daria Zaporozhets, Dmitry Kureichik, Vladimir Southern Fed Univ Rostov Na Donu Russia

ISBN: (数字)9783319336251

ISBN: (纸本)9783319336251;9783319336237

The paper discusses a modified algorithm based on the ants 'behavior in nature. We suggest to apply this algorithm for solving the element placement problem - one of the most difficult problem in the VLSI design. This problem belongs to the NP-class problem that is there are no precise methods to solve this problem. Also we formulate the placement problem and choose an optimization criterion. The developed ant colony optimization (aco) algorithm obtains optimal and quasi-optimal solutions during polynomial time. The distinguish feature of the algorithm is that alternative solution are represented as an undirected graph with weighted edges. Besides, at each generation the algorithm creates a taboo-list to eliminate the quantity of agent (ant) which is wrong from the point of view the using of Reverse Polish notation. To compare obtained results with known analogous algorithms we developed software which allows to carry out experiments on the basis of IBM benchmarks. Conducted experiments shown that the aco algorithm is better than the other algorithms an average of 9 %.

关键词： VLSI Placement problem aco algorithm Taboo-list Reverse polish notation

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A Roadbed Earthwork Allocation Model Based on aco algorithm

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International Conference on Frontiers of Manufacturing and Design Science (ICFMD2010)

作者： Miao, Kun Sun, Xing Li, Liang Cent S Univ Sch Civil Engn & Architecture Changsha 410075 Hunan Peoples R China

ISBN: (纸本)9783037850046

A new optimized highway earthwork allocation model from mass-haul diagram idea is built in this study. A mass-haul diagram is a kind of traditional manual method, but it is visualized and convenient for earthwork allocation. With it, the earth moving operations can be represented as discrete events systems, and an ant colony optimization (aco) algorithm is developed as a system to be equipped with the model. It was shown that the model developed in this study was effective and could increase earthwork allocation efficiency. The model can compute cut and fill quantities and generate the optimal earthmoving plan automatically.

关键词： aco algorithm Highway Earthwork allocation model

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Ant colony optimisation of decision tree and contingency table models for the discovery of gene-gene interactions

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IET SYSTEMS BIOLOGY 2015年第6期9卷 218-225页

作者： Sapin, Emmanuel Keedwell, Ed Frayling, Tim Univ Exeter Coll Engn Math & Phys Sci Exeter EX4 4QJ Devon England Univ Exeter Exeter Med Sch Exeter EX4 4QJ Devon England

In this study, ant colony optimisation (aco) algorithm is used to derive near-optimal interactions between a number of single nucleotide polymorphisms (SNPs). This approach is used to discover small numbers of SNPs that are combined into a decision tree or contingency table model. The aco algorithm is shown to be very robust as it is proven to be able to find results that are discriminatory from a statistical perspective with logical interactions, decision tree and contingency table models for various numbers of SNPs considered in the interaction. A large number of the SNPs discovered here have been already identified in large genome-wide association studies to be related to type II diabetes in the literature, lending additional confidence to the results.

关键词： genetics genomics DNA polymorphism molecular biophysics molecular configurations ant colony optimisation decision trees bioinformatics diseases ant colony optimisation decision tree contingency table models gene-gene interactions aco algorithm near-optimal interactions single nucleotide polymorphisms SNP genome-wide association studies type II diabetes

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Solution of the two-dimensional inverse problem of the binary alloy solidification by applying the Ant Colony Optimization algorithm

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INTERNATIONAL COMMUNICATIONS IN HEAT AND MASS TRANSFER 2015年 67卷 39-45页

作者： Hetmaniok, Edyta Silesian Tech Univ Inst Math PL-44100 Gliwice Poland

In the paper a procedure for solving the two-dimensional inverse problem of the binary alloy solidification is presented. In considered problem the heat transfer coefficient is identified on the basis of measured values of temperature in selected points of the region. Direct problem, associated with the inverse one, is solved by using the generalized alternating phase truncation method. Functional expressing of the error of approximate solution is minimized with the aid of Ant Colony Optimization algorithm. The model also includes the macrosegregation, influencing the solidification, described by means of the lever aim model. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Solidification Binary alloy Lever arm model Swarm intelligence aco algorithm

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Optimum reliable operation of water distribution networks by minimising energy cost and chlorine dosage

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WATER SA 2015年第1期41卷 149-156页

作者： Babaei, Nadia Tabesh, Massoud Nazif, Sara Univ Tehran Coll Engn Sch Civil Engn Tehran Iran

In recent decades much attention has been paid to optimal operation of water distribution networks (WDNs). In this regard, the system operation costs, including energy and disinfection chemicals, as well as system reliability should be simultaneously considered in system performance optimisation, to provide the minimum required level of performance in failure condition and to manage economic limitations. In this study, multi-objective optimisation of water distribution network performance in 3 different scenarios was considered. In these scenarios the effects of time-dependent chlorine injection and pump speed, as well as different combinations of objective functions for minimising energy and disinfection costs and for maximising hydraulic reliability and quality-based reliability are incorporated. As the optimisation method, a multi-objective ant colony optimisation (aco) algorithm was used because of its high efficiency. For better managing the hydraulic behaviour and water quality in the WDN, considering temporal variations of demand, it is suggested to use variable speed pumps (VSP) as well as to inject chlorine at a variable rate. Application of VSP and time-dependent chlorine injection results in improvements such as reduction in energy and disinfection costs, and decrease in disinfection costs in application of HDSM (head-driven simulation method). In HDSM simulation of WDN, a decrease in hydraulic reliability because of shortages in water supply can be mitigated through extra chlorine injection and increase in quality-based reliability. To deal with this challenge, it is recommended to satisfy the hydraulic reliability first and then to evaluate the quality reliability. Furthermore it is necessary to modify the hydraulic reliability relationship to incorporate different components of the WDN other than pumps. This will provide more reliable results for evaluation of the system performance.

关键词： multi-objective optimisation aco algorithm energy cost disinfection costs hydraulic reliability quality reliability

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Fuzzy identification and control of a piezoelectric actuator 3

Fuzzy identification and control of a piezoelectric actuator

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INTERNATIONAL CONFERENCE ON CONTROL ENGINEERING & INFORMATION TECHNOLOGY (CEIT)

作者： Rebai, Aissa Guesmi, Kamel Hemici, Boualem Natl Polytech Sch ENP Algiers Proc Control Lab LCP Algiers Algeria IUT Troyes CReSTIC 09 Rue Quebec F-10026 Troyes France

ISBN: (纸本)9781479982134

Due to the special characteristics of piezoelectric actuators, the modelling and control task of these devices has been one of the most important research topic in the last decade. In the first part of this paper, a T-S fuzzy model is proposed to represent the behavior of this type of actuators and the recursive least squares (RLS) algorithm is used to optimize the parameters of this model. In the second part, based on an analytical model, a fuzzy PID controller for the piezoelectric actuator plant is presented. An ant colony optimization (aco) algorithm is used to find the parameters of the proposed controller. The proposed approaches are validated through simulation along with their satisfactory performances.

关键词： Piezoelectric actuator Dynamic hysteresis model T-S fuzzy system Inverse model Fuzzy PID controller aco algorithm

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Ant Colony Input Parameters Optimization for Multiuser Detection in DS/CDMA Systems

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IEEE LATIN AMERICA TRANSACTIONS 2014年第8期12卷 1355-1364页

作者： Marinello Filho, J. C. de Souza, R. N. Abrao, T. Univ Estadual Londrina Epartment Elect Engn Londrina Brazil Univ Estadual Londrina Dept Elect Engn Commun Grp Londrina Brazil

In this work a simple and efficient methodology for tuning the input parameters applied to the ant colony optimization multiuser detection (aco-MuD) in direct sequence code division multiple access (DS-CDMA) is proposed. The motivation in using a heuristic approach is due to the nature of the NP complexity posed by the wireless multiuser detection optimization problem. The challenge is to obtain suitable data detection performance in solving the associated hard complexity problem in a polynomial time. Previous results indicated that the application of heuristic search algorithms in several wireless optimization problems have been achieved excellent performance-complexity tradeoffs. Regarding different system operation and channels scenarios, a complete input parameters optimization procedure for the aco-MuD is provided herein, which represents the major contribution of this work. Furthermore, the performance of the aco-MuD is analyzed via Monte-Carlo simulations. Simulation results show that, after convergence, the performance reached by the aco-MuD is much better than the conventional detector, and somewhat closer to the single user bound (SuB). Rayleigh flat channel is initially considered, but the results are straightforwardly extended to selective fading channels, as well as diversity (time and spatial) wireless channels.

关键词： Ant colony intelligence aco algorithm DS-CDMA Multiple access communication network Multiuser detection input parameters optimization computational complexity

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Path Planning of UAVs Formation Based on Improved Ant Colony Optimization algorithm 6

Path Planning of UAVs Formation Based on Improved Ant Colony...

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IEEE Chinese Guidance, Navigation and Control Conference (CGNCC)

作者： Zhao Qiannan Zhen Ziyang Gao Chen Ding Ruyi Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Jiangsu Peoples R China

ISBN: (纸本)9781479946990

Aimed at the problem about the path planning of multiple unmanned aerial vehicles (UAVs) formation in radar-threatening environment, an intelligent method based on improved ant colony optimization (aco) algorithm is presented. To begin with, initialize the mission environment before the mathematically modeling of flight path and environment. Then, a path of a single UAV can be sought by aco algorithm. The following step is the formation of multiple UAVs. Ultimately, a real flyable path comes out on condition that the formation remains unchanged. However, path planning based on the traditional aco may not be the best when it comes to the fact that it may contain some dispensable routes. To solve this problem, the path is trimmed afterwards to make it more straightforward. Simulation results show that the proposed improved intelligent method have better dynamic nature and computing power.

关键词： ant colony optimisation autonomous aerial vehicles path planning position control aco algorithm UAV formation ant colony optimization flight path flyable path intelligent method mission environment radar-threatening environment unmanned aerial vehicles formation algorithm design and analysis Diamonds Educational institutions Fuels Joints Optimization Path planning

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Automated Recognition of Ficus Deltoidea Using Ant Colony Optimization Technique

Automated Recognition of Ficus Deltoidea Using Ant Colony Op...

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8th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Ishak, Asnor Juraiza Soh, Azura Che Marhaban, Mohammad Hamiruce Khamis, Shamsul Ghasab, Mohammad Ali Jan Univ Putra Malaysia Fac Engn Dept Elect & Elect Engn Serdang 43400 Selangor Malaysia Univ Putra Malaysia Inst Biosci Unit Biodivers Serdang 43400 Selangor Malaysia

ISBN: (纸本)9781467363228;9781467363204

Improving in the fields of soft computing and artificial intelligence, the branch study of automated herb recognition among plenty of weeds has become challenging issue due to their applications in medicine, food and industry. This paper presents innovative method to improve the accuracy of classification as well the efficiency, such that irrelevant features that make computational complexity are ignored by feature subset selection that is proposed by means of ant colony optimization algorithm (aco). At first, through image processing specified features are extracted from the Ficus deltoidea leaves such as vein, morphology and texture features and they construct a search space to be chosen for the optimal subset features that is selected by aco algorithm as support vector machine (SVM) classify them. The experimental results have shown that the proposed method not only optimize feature subset, but also has a remarkable positive impact on accuracy.

关键词： feature reduction aco algorithm SVM Ficus deltoidea Herb recognition

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Application of aco algorithm in protein structure prediction

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Journal of Harbin Institute of Technology(New Series) 2009年第1期16卷 111-114页

作者：唐好选曲毅 School of Computer Science and Technology Harbin Institute of Technology

The hydrophobic-polar (HP) lattice model is an important simplified model for studying protein folding. In this paper, we present an improved aco algorithm for the protein structure prediction. In the algorithm, the "lone"ethod is applied to deal with the infeasible structures, and the "oint mutation and reconstruction"ethod is applied in local search phase. The empirical results show that the presented method is feasible and effective to solve the problem of protein structure prediction, and notable improvements in CPU time are obtained.

关键词： protein structure prediction HP lattice model aco algorithm

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