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Optimum design of skeletal structures using imperialist competitive algorithm

COMPUTERS & STRUCTURES 2010年第21-22期88卷 1220-1229页

作者： Kaveh, A. Talatahari, S. Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn Tehran Iran Univ Tabriz Dept Civil Engn Tabriz Iran

A novel optimization method is presented based on a socio-politically motivated strategy, called imperialist competitive algorithm (ICA). ICA is a multi-agent algorithm with each agent being a country, which is either a colony or an imperialist. These countries form some empires in the search space. Movement of the colonies toward their related imperialist, and imperialistic competition among the empires, form the basis of the ICA. During these movements, the powerful imperialists are reinforced and the weak ones are weakened and gradually collapsed, directing the algorithm towards optimum points. Here, the ICA is utilized to optimize the skeletal structures. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： imperialist competitive algorithm Meta-heuristic algorithms Optimum design Truss structures Frame structures

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GICA: imperialist competitive algorithm with globalization mechanism for optimization problems

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TURKISH JOURNAL OF ELECTRICAL ENGINEERING AND COMPUTER SCIENCES 2017年第1期25卷 209-221页

作者： abdi, Yousef lak, Mahmoud Seyfari, Yousef Payame Noor Univ Dept Comp Engn Tabriz Iran Islamic Azad Univ Dept Comp Engn Shabostar Branch Shabestar Iran Univ Tabriz Dept Comp Sci Tabriz Iran

The imperialist competitive algorithm (ICA) is a recent global search strategy developed based on human social evolutionary phenomena in the real world. However, the ICA has the drawback of trapping in local optimum solutions when used for high-dimensional or complex multimodal functions. In order to deal with this situation, in this paper an improved ICA, named GICA, is proposed that can enhance ICA performance by using a new assimilation method and establishing a relationship between countries inspired by the globalization concept in the real world. The proposed algorithm is evaluated using a set of well-known benchmark functions for global optimization. Obtained results show the efficiency and effectiveness of the method and show that this strategy can deal with the local optimum problem.

关键词： imperialist competitive algorithm optimization local optimum globalization segmented assimilation crossover

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Gravity inversion of basement relief using imperialist competitive algorithm with hybrid techniques

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ACTA GEOPHYSICA 2022年第6期70卷 2629-2646页

作者： Joolaei, Amir Arab-Amiri, Alireza Nejati, Ali Shahrood Univ Technol Fac Min Petr & Geophys Shahrood Iran

Classically, local deterministic optimization techniques have been employed to solve such nonlinear gravity inversion problem. Nevertheless, local search methods can also be easily implemented and demonstrate higher rates of convergence;but in highly nonlinear cases such as geophysical problems, they require a reliable initial model which should be adequately close to the true model. Recently, global optimization methods have shown promising results as an alternative to classical inversion methods. Each of the global optimization algorithms has unique benefits and faults;therefore, applying different combinations of them is one of the proposed solutions for overcoming their distinct limitations. In this research, the design and implementation of the hybrid method based on a combination of the imperialist competitive algorithm (ICA) and firefly algorithm (FA) as tools of two-dimensional nonlinear modeling of gravity data and as a substitute for the local optimization methods were investigated. Hybrid of ICA and FA algorithm (known as ICAFA) is a modified form of the ICA algorithm based on the firefly algorithm. This modification results in an increase in the exploratory capability of the algorithm and improvement of its convergence rate. This inversion technique was first successfully tested on a synthetic gravity anomaly originated from a simulated sedimentary basin model both with and without the presence of white Gaussian noise (WGN). At last, the method was applied to the Bouguer anomaly from a real gravity profile in Moghan sedimentary basin (Iran). The results of this modeling were compatible with previously published works which consisted of both seismic analysis and other gravity interpretations. In order to estimate the uncertainty of solutions, several inversion runs were also conducted independently and the results were in line with the final solution.

关键词： Gravity inversion Global optimization imperialist competitive algorithm Firefly algorithm Uncertainty

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Nonlinear rock-physics inversion using artificial neural network optimized by imperialist competitive algorithm

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JOURNAL OF APPLIED GEOPHYSICS 2018年 155卷 138-148页

作者： Mollajan, Amir Memarian, Hossein Quintal, Beatriz Univ Tehran Univ Coll Engn Sch Min Engn Tehran Iran Univ Lausanne Inst Earth Sci Fac Geosci & Environm Lausanne Switzerland

Estimation of petrophysical properties from seismic attributes can be considered as rock-physics inversion problem. In general, rock-physics models are nonlinear and require nonlinear optimization algorithms to solve the inversion problem. Typically, the conventional method of inversion employs the linearized approximation of the forward model and utilizes the linear inversion methods which are usually not accurate enough and prone to be trapped in a local minimum. This paper presents a novel method of nonlinear rock-physics inversion based on artificial neural network optimized by imperialist competitive algorithm. We used Kuster and Toksta inclusion model with spherical geometric factor as forward model to map the model parameters to the observed data. To quantify the performance of the method, we compare it with the Bayesian linearized rock-physics method. The result shows that the presented method can achieve more reliable and accurate inversion of the petrophysical parameters. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Rock-physics inversion Petrophysical parameters imperialist competitive algorithm Kuster and Toksoz inclusion model Bayesian linearized

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Load Balanced Clustering Based on imperialist competitive algorithm in Wireless Sensor Networks

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WIRELESS PERSONAL COMMUNICATIONS 2020年第1期112卷 371-385页

作者： Dehestani, Fahimeh Jabraeil Jamali, Mohammad Ali Islamic Azad Univ Shabestar Branch Dept Comp Engn Shabestar Iran

Energy consumption is one of the most serious issues in designing Wireless Sensor Networks (WSNs) for maximizing its lifetime and stability. Clustering is considered as one of the topology control methods for maintaining the stability of WSNs which can significantly reduce energy consumption in WSNs. However, using different methods for the selection of cluster head is an important challenge in this domain of research. Load balanced clustering is known as an NP-hard problem for a WSN along with unequal load for sensor nodes. The imperialist competitive algorithm (ICA) is regarded as an evolutionary method which can be used for finding a quick and efficient solution to such problems. In this paper, a clustering method with an evolutionary approach is introduced which investigates the issues of load balance and energy consumption of WSNs in the equal and unequal load modes so as to select optimal cluster heads. Simulation of the proposed method, carried out via NS2, indicated that it improves the criteria of energy consumption, the number of active sensor nodes and execution time.

关键词： Wireless sensor network Clustering algorithm imperialist competitive algorithm Load balancing

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imperialist competitive algorithm with Updated Assimilation for the Solution of Real Valued Optimization Problems

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INTERNATIONAL JOURNAL ON ARTIFICIAL INTELLIGENCE TOOLS 2018年第2期27卷 1850005-1850005页

作者： Sherinov, Zhavat Unveren, Ahmet Acan, Adnan Eastern Mediterranean Univ Dept Comp Engn Gazimagusa Turkey

In this paper, an improved imperialistic competitive algorithm is presented for real-valued optimization problems. A new method is introduced for the movement of colonies towards their imperialist, which is called assimilation. The proposed method uses Euclidean distance along with Pearson correlation coefficient as an operator for assimilating colonies with respect to their imperialists. Applications of the proposed algorithm to classical and recently published hard benchmark problems, and statistical analysis associated with the corresponding experimental results illustrated that the achieved success is significantly better than a number of state-of-the art methods.

关键词： Metaheuristics imperialist competitive algorithm global optimization

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imperialist competitive algorithm hybridized with multilayer perceptron to predict the load-settlement of square footing on layered soils

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MEASUREMENT 2021年 172卷 108837-108837页

作者： Moayedi, Hossein Gor, Mesut Foong, Loke Kok Bahiraei, Mehdi Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Duy Tan Univ Fac Civil Engn Da Nan 550000 Vietnam Firat Univ Engn Fac Civil Engn Dept Div Geotech Engn TR-23119 Elazig Turkey Ton Duc Thang Univ Dept Management Sci & Technol Dev Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Civil Engn Ho Chi Minh City Vietnam Razi Univ Fac Engn Kermanshah Iran

To forecast the value of bearing capacity in shallow footings, a total of 2430 finite element modelling WEND simulation is performed. In this regard and to optimize the performance of the artificial neural network (ANN), it is combined with the imperialist competitive algorithm (ICA). The new combined technique is called ICA-MLP (multi-layer perceptron). To develop the ICA-MLP model, the input parameters were the soil type (i.e., having particular soil properties for each of the sandy soil types) installed at the top, the soil type installed at the bottom, the first-layer thickness ratio (h/B) and the applied stress on the footing (kPa), while the output was the vertical settlement (mm) under the square footing. The estimations were compared with a predeveloped ANN model to demonstrate the ability of the ICA-MLP hybrid model. The results showed a high ability of ICA metaheuristic ensembles for understanding the non-linear relationship between the influential factors and the selected target. Meanwhile, a comparison between the used models revealed that the best-combined structure is when the ICA algorithm is followed by the swarm size equal to 350. In this sense, the results from the predeveloped ANN model, based on R-2 values, were 0.83 and 0.89 for the training and testing data sets, respectively, whereas the R-2 and RMSE values for the ICA-MLP model for the training and testing datasets were 0.983, 0.062 and 0.977, 0.070, respectively. Therefore, the ICA-MLP model can be regarded as a new model that is superior to the conventional MLP technique.

关键词： imperialist competitive algorithm Square footing Load-settlement response Artificial neural network Multi-layered soil

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Two-phase imperialist competitive algorithm for energy-efficient flexible job shop scheduling

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2021年第6期40卷 12125-12137页

作者： Guo, Jiong Lei, Deming Li, Ming Wuhan Univ Technol Sch Automat Wuhan Peoples R China Anhui Polytech Univ Sch Econ & Management Wuhu 241000 Peoples R China

Energy-efficient flexible job shop scheduling problems (EFJSP) have been investigated fully;however, energy-related objectives often have lower importance than other ones in many real-life situations and this case is hardly considered in the previous works. In this study, EFJSP with sequence-dependent setup times (SDST) is considered, in which total tardiness and makespan are given higher importance than total energy consumption. A two-phase imperialist competitive algorithm (TPICA) is proposed. The importance difference among objectives is implemented by treating all objectives equally in the first phase and making energy consumption not to exceed a diminishing threshold in the second phase. A dynamical differentiating assimilation and a novel imperialist competition with the enforced search are implemented. Extensive experiments are conducted and the computational results show that TPICA is very competitive for EFJSP with SDST.

关键词： Flexible job shop scheduling energy-efficient scheduling imperialist competitive algorithm sequence-dependent setup times

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Optimization of Free Convection Heat Transfer in a Horizontal Cylinder Beneath an Adiabatic Ceiling, Using an imperialist competitive algorithm

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JOURNAL OF CHEMICAL ENGINEERING OF JAPAN 2012年第6期45卷 401-407页

作者： Karami, Alimohammad Rezaei, Ehsan Mahmoudinezhad, Sajjad Yousefi, Tooraj Kermanshah Univ Technol Dept Mech Engn Kermanshah Iran Islamic Azad Univ Gachsaran Branch Dept Mech Engn Gachsaran Iran Razi Univ Dept Mech Engn Kermanshah Iran

The focus of the present paper is the application of a novel optimization algorithm called an imperialist competitive algorithm (ICA). In this algorithm, the cost function, which is a function of the input parameters, has to be optimized. In the present research, our cost function is the average free convection heat transfer from a horizontal isothermal cylinder located underneath an adiabatic ceiling. The input parameters are the ratio of the cylinder spacing from the adiabatic ceiling to its diameter (L/D), varying from 0.1 to 2.4, and the Rayleigh number, varying from 5500 to 40000. After data reduction, the regression equation of the average Nusselt number of the cylinder surface was obtained as a function of the Rayleigh number and the cylinder spacing ratio (L/D). The cost function was then optimized using the ICA. The results show that the proposed algorithm is powerful enough to be used for optimizing the cost function. According to the results obtained, the minimum Nusselt number corresponds to the optimum distance between the adiabatic wall and the cylinder.

关键词： Free Convection Heat Transfer Adiabatic Wall Optimization imperialist competitive algorithm

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A novel imperialist competitive algorithm for bi-criteria scheduling of the assembly flowshop problem

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2011年第11期49卷 3087-3103页

作者： Shokrollahpour, E. Zandieh, M. Dorri, Behrouz Shahid Beheshti Univ Dept Ind Management Management & Accounting Fac GC Tehran Iran

This paper deals with the two-stage assembly flowshop scheduling problem with minimisation of weighted sum of makespan and mean completion time as the objective. The problem is NP-hard, hence we proposed a meta-heuristic named imperialist competitive algorithm (ICA) to solve it. Since appropriate design of the parameters has a significant impact on the algorithm efficiency, we calibrate the parameters of this algorithm using the Taguchi method. In comparison with the best algorithm proposed previously, the ICA indicates an improvement. The results have been confirmed statistically.

关键词： assembly flowshop bi-criteria scheduling makespan mean completion time imperialist competitive algorithm

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