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Optimal control of structures under earthquake excitation based on the colonial competitive algorithm

STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS 2014年第7期23卷 500-511页

作者： Amini, Fereidoun Bagheri, Abdollah Iran Univ Sci & Technol Sch Civil Engn Dept Civil Engn Tehran Iran Univ Pittsburgh Dept Civil & Environm Engn Pittsburgh PA 15261 USA

The active control of engineering structures is one of the best methods to reduce structural responses under seismic excitation for the best performance of structures. This study presents an effective approach for the optimal control of structures under strong ground motion using the colonial competitive algorithm. The colonial competitive algorithm was developed over the last few years in an attempt to overcome the inherent limitations of traditional optimize method. The colonial competitive algorithm has been applied due to its ideal performance in optimal control problem. The effectiveness and performance of the proposed method have been investigated through two numerical examples for the response control of earthquake-excited structures. The obtained results have been compared with the Linear Quadratic Regulator (LQR) control algorithm, and the performance of the proposed control approach has been found to be better than the LQR controller. Copyright (c) 2012 John Wiley & Sons, Ltd.

关键词： optimal control optimization structural control colonial competitive algorithm

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New method for the estimation of strong ground motions based on the colonial competitive algorithm

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KSCE JOURNAL OF CIVIL ENGINEERING 2014年第5期18卷 1403-1410页

作者： Bagheri, Abdollah Amiri, Gholamreza Ghodrati Haghdoust, Jamshid Univ Pittsburgh Dept Civil & Environm Engn Pittsburgh PA 15261 USA Iran Univ Sci & Technol Sch Civil Engn Ctr Excellence Fundamental Studies Struct Engn Tehran 16846 Iran Iran Univ Sci & Technol Sch Civil Engn Tehran 16846 Iran

This paper is aimed at presenting a new method on the basis of the colonial competitive algorithm to predict horizontal peak ground acceleration and spectral acceleration. The colonial competitive algorithm was developed over the last few years in an attempt to overcome inherent limitations of traditional optimize method. The proposed method employs the optimization capabilities of the colonial competitive algorithm to determine the coefficients of attenuation relationships of peak ground acceleration and spectral acceleration. This method was applied to an ensemble of earthquake records of two seismic zones, namely Zagros and Alborz-Central Iran. The obtained results clearly reveal that the colonial competitive algorithm can be viewed as a powerful and reliable tool for solving complex optimization problems such as attenuation relationship.

关键词： attenuation relationship colonial competitive algorithm peak ground acceleration spectral acceleration

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Investigating the application of opposition concept to colonial competitive algorithm

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INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 2012年第5期4卷 319-329页

作者： Azad, Hamid Reza Lashgarian Boushehri, Nader Shetab Mollaverdi, Naser Isfahan Univ Technol Dept Ind & Syst Engn Esfahan *** Iran

Evolutionary algorithms (EAs) are well-known optimisation approaches to deal with non-linear and complex problems. However, these population-based algorithms are computationally expensive due to the slow nature of the evolutionary process. This paper presents a novel algorithm to accelerate colonial competitive algorithm (CCA). The proposed opposition-based CCA (OCCA) employs opposition-based learning (OBL) for population initialisation and also for generation jumping. In this work, opposite countries and colonies have been utilised to improve the convergence rate of CCA. A comprehensive set of 15 complex benchmark functions including a wide range of dimensions is employed for experimental verification. The influences of dimensionality and population size are also investigated. Experimental results confirm that the OCCA outperforms the original CCA in terms of convergence speed and robust.

关键词： opposition-based learning OBL colonial competitive algorithm CCA opposite countries opposite colonies

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A modified colonial competitive algorithm for the mixed-model U-line balancing and sequencing problem

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第18期50卷 5117-5131页

作者： Lian, Kunlei Zhang, Chaoyong Gao, Liang Shao, Xinyu Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Hubei Peoples R China

Implementation of mixed-model U-shaped assembly lines (MMUL) is emerging and thriving in modern manufacturing systems owing to adaptation to changes in market demand and application of just-in-time production principles. In this study, the line balancing and model sequencing (MS) problems in MMUL are considered simultaneously, which results in the NP-hard mixed-model U-line balancing and sequencing (MMUL/BS) problem. A colonial competitive algorithm (CCA) is developed and modified to solve the MMUL/BS problem. The modified CCA (MCCA) improves performance of original CCA by introducing a third type of country, independent country, to the population of countries maintained by CCA. Implementation details of the proposed CCA and MCCA are elaborated using an illustrative example. Performance of the proposed algorithms is tested on a set of test-bed problems and compared with that of existing algorithms such as co-evolutionary algorithm, endosymbiotic evolutionary algorithm, simulated annealing, and genetic algorithm. Computational results and comparisons show that the proposed algorithms can improve the results obtained by existing algorithms developed for MMUL/BS.

关键词： mixed-model U-line balancing and sequencing colonial competitive algorithm genetic algorithm

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colonial competitive algorithm Assisted Least Squares Support Vector Machines

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International Conference on Civil Engineering and Building Materials (CEBM)

作者： Ren, Yuan Bai, Guangchen Beijing Univ Aeronaut & Astronaut Sch Jet Prop Beijing 100083 Peoples R China

ISBN: (纸本)9783037851395

The use of least squares support vector machine (LSSVM), a novel machine learning method, for classification and function approximation has increased over the past few years especially due to its high generalization performance. However, LSSVM is plagued by the drawback that the hyper-parameters, which largely determine the quality of LSSVM models, have to be defined by the user, and this increases the difficulty of applying LSSVM and limits its use on academic and industrial platforms. In this paper we present a novel method of automatically tuning the hyper-parameters of LSSVM based on colonial competitive algorithm (CCA), a newly developed evolutionary algorithm inspired by imperialistic competition mechanism. To show the efficacy of the CCA assisted LSSVM methodology, we have tested it on several benchmark examples. The study suggests that proposed paradigm can be a competitive and powerful tool for classification and function approximation.

关键词： colonial competitive algorithm parameters tuning machine learning optimization

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A novel solution in the simultaneous deep optimization of RGB-D camera calibration parameters using metaheuristic algorithms

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2018年第2期26卷 743-754页

作者： Safaei, Amir Fazli, Saeid Univ Zanjan Fac Engn Dept Elect Engn Zanjan Iran Univ Zanjan Res Inst Modern Biol Tech Zanjan Iran

This article presents a novel method for estimating 19 parameters of RGB and depth camera calibration simultaneously. The proposed algorithm is based on applying metaheuristic methods for deep optimization and estimating all parameters of intrinsic, extrinsic, and lens distortions of cameras. This paper compares four metaheuristic algorithms, i.e. a genetic algorithm, particle swarm optimization, the colonial competitive algorithm, and the shuffled frog leaping algorithm, with a numerical algorithm called singular value decomposition. The proposed method does not need the initial estimation for optimization and it can avoid being trapped in local minima. By using nondirect estimation, we achieve middle computing matrices such as the homography matrix, which is used in the pinhole camera model. Both versions of Kinect sensors are used for the experimental evaluation. The mean square of the reprojection error criteria is defined as the objective function in the proposed algorithm. The experimental results show that the proposed method is more efficient and accurate than traditional numerical solutions.

关键词： colonial competitive algorithm homography Kinect calibration metaheuristic algorithm radial lens distortion shuffled frog leaping algorithm

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A discrete colonial competitive algorithm for hybrid flowshop scheduling to minimize earliness and quadratic tardiness penalties

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EXPERT SYSTEMS WITH APPLICATIONS 2011年第12期38卷 14490-14498页

作者： Behnamian, J. Zandieh, M. Shahid Beheshti Univ Management & Accounting Fac Dept Ind Management GC Tehran Iran Amirkabir Univ Technol Dept Ind Engn Tehran Iran

Recently introduced colonial competitive algorithm (CCA) has shown its excellent capability on different optimization problems. The aim of this paper is to propose a discrete version of this method to determine a schedule that minimizes sum of the linear earliness and quadratic tardiness in the hybrid flowshops scheduling problem with simultaneously considering effects of sequence-dependent setup times and limited waiting time. In other word we assume that the waiting time for each job between two consecutive stages cannot be greater than a given upper bound. Also for this problem, a mixed integer program is formulated. Computational results are presented to evaluate the performance of the proposed algorithms for problems with different structures. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Hybrid flowshops scheduling Limited waiting time colonial competitive algorithm Mixed integer linear programming Earliness and tardiness penalties

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Deployment of the meta heuristic colonial competitive algorithm in synthesis of unequally spaced linear antenna array

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IEICE ELECTRONICS EXPRESS 2011年第24期8卷 2048-2053页

作者： Kazemi, Somayeh Ghorbani, Ayaz Hashemi, Seyed Naser Amir Kabir Univ Technol Dept Elect Engn Tehran Iran Amir Kabir Univ Technol Dept Math & Comp Sci Tehran Iran

In this paper we re-call a recently developed meta heuristic optimization algorithm based on socio-political process of imperialistic competition. This colonial competitive algorithm (CCA) has shown its efficient capability in comparison to convenient optimization algorithms like GA, PSO. In this study we investigate the synthesis problem of unequally linear space antenna using CCA and show the efficient convergence to obtain a pattern with acceptable Side Lobe Level.

关键词： unequally-spaced antenna colonial competitive algorithm genetic algorithm legendre method pseudo least mean square method

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Optimization approach for increasing revenue of perishable product supply chain with the Internet of Things

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INDUSTRIAL MANAGEMENT & DATA SYSTEMS 2017年第4期117卷 729-741页

作者： Yan, Rui Univ Calif San Diego Dept Math San Diego CA 92103 USA

Purpose - The purpose of this paper is to optimize a two-level perishable product supply chain by increasing its revenue with the Internet of Things (IoT). It particularly investigates how radio-frequency identification (RFID) technology impacts the revenue of the supply chain. Design/methodology/approach - In this paper, two revenue models were built to calculate the revenue of perishable product supply chain before and after the application of IoT to analyze the influences of IoT on perishable product supply chain. In the case study, particular data of an aquatic product supply chain were analyzed through these models which were later solved by a computer simulation method based on colonial competitive algorithm, a new heuristic algorithm inspired by imperialistic competition in human society. Findings - Using these revenue models to compare the revenues of supply chain before and after the application of IoT, this paper concludes that the application of IoT can efficiently optimize a perishable product supply chain by balancing its wholesale profits and its total costs including logistics costs, therefore, increasing its overall revenue. However, this conclusion is only applicable for large enterprises, while small enterprises are not supposed to introduce IoT due to its high cost. Originality/value - The revenue models built in this paper can be used to evaluate the profits of supply chain and help enterprises determine how to maximize their profits and whether they should introduce IoT in a perishable product supply chain. In addition, through the analysis of case study, this paper gives several valuable suggestions to help enterprises reduce their logistics costs and increase their overall revenue.

关键词： Optimization Internet of Things colonial competitive algorithm Perishable product supply chain Revenue model

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Modeling and solving a capacitated stochastic location-allocation problem using sub-sources

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SOFT COMPUTING 2016年第6期20卷 2261-2280页

作者： Alizadeh, Morteza Mahdavi-Amiri, Nezam Shiripour, Saber Mazandaran Univ Sci & Technol Dept Ind Engn Babol Sar Iran Sharif Univ Technol Fac Math Sci Tehran Iran

We study a capacitated multi-facility location-allocation problem in which the customers have stochastic demands based on Bernoulli distribution function. We consider the capacitated sub-sources of facilities to satisfy demands of customers. In the discrete stochastic problem, the goal is to find optimal locations of facilities among candidate locations and optimal allocations of existing customers to operating facilities so that the total sum of fixed costs of operating facilities, allocation cost of the customers, expected values of servicing and outsourcing costs is minimized. The model is formulated as a mixed-integer nonlinear programming problem. Since finding an optimal solution may require an excessive amount of time depending on nonlinear constraints, we transform the nonlinear constraints of the problem to linear ones to arrive at a simple formulation of the model. Numerical results show that the LINGO 9.0 software is capable of solving small size problems. For medium and large-size problems, we propose two meta-heuristic algorithms, namely a genetic algorithm and a discrete version of colonial competitive algorithm. Computational results show that the proposed algorithms efficiently obtain effective solutions.

关键词： Capacitated location-allocation problem Outsourcing function Linearization Genetic algorithm colonial competitive algorithm

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