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Forward and backward predictions of the friction stir welding parameters using fuzzy-artificial bee colony-imperialist competitive algorithm systems

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JOURNAL OF INTELLIGENT MANUFACTURING 2015年第2期26卷 307-319页

作者： Teimouri, Reza Baseri, Hamid Babol Univ Technol Dept Mech Engn Babol Sar Iran

Friction stir welding (FSW) process is an environmentally friendly alternative of welding processes. Due to contribution of too many parameters in this process, generation of predictive models which can estimate the process characteristics is really complex. Thus, in order to develop predictive models in this work the fuzzy approaches were applied to anticipate tensile strength, elongation and hardness of FSWed aluminum joints according to variation of tool rotational speed and welding. Current work consists of two main approaches, in first approach manually fuzzy models were used to correlate relationships between inputs and outputs based on human expertise, then these models have been modified using artificial bee colony algorithm (ABC) by selection of appropriate half width for each membership function which minimizes root mean square error (RMSE). In second approach backward mapping was fulfilled to predict appropriate inputs for specified output by using of imperialistic competitive algorithm (ICA) which minimizes modeling error. Results indicated that the developed fuzzy-ABC system generates more accurate prediction rather than manually fuzzy model according to values of RMSE. Also association of modified fuzzy network with ICA is a suitable tool for reverse mapping of FSW process.

关键词： Fuzzy logic Forward and backward mapping Artificial bee colony algorithm imperialistic competitive algorithm

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EXPLICA: An Explorative Imperialist competitive algorithm based on the notion of Explorers with an expansive retention policy

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APPLIED SOFT COMPUTING 2017年 54卷 74-92页

作者： Ardeh, Mazhar Ansari Menhaj, Mohammad Bagher Esmailian, Ehsan Zandhessami, Hessam Kharazmi Univ Dept Decis Sci & Knowledge Engn Tehran Iran Amirkabir Univ Technol Dept Elect Engn Tehran Iran Amirkabir Univ Technol Dept Maritime Engn Tehran Iran Islamic Azad Univ Qazvin Branch Dept Management Qazvin Iran

Meta-heuristic algorithms are of considerable importance in solving optimization problems. This importance is more highlighted when the problems to be optimized are too complicated to achieve a solution using conventional methods or, the traditional methods are somehow not applicable for solving them. Imperial competitive algorithm has been proved to be an efficient and effective meta-heuristic optimization algorithm and it has been successfully applied in many scientific and engineering problems. By introducing the concept of explorers and retention policy, the original algorithm is enhanced with a dynamic population mechanism in this paper and hence, the performance of the Imperial competitive algorithm is improved. Performance of the proposed modification is tested with experiments of optimizing real-values functions and results are compared with results obtained with the original imperialistic competitive algorithm, Genetic algorithm, Particle Swarm Optimization and Simulated Annealing. Also, the applicability of the proposed improvement is verified by optimizing a ship propeller design problem. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Meta-heuristic optimization imperialistic competitive algorithm Real-valued function optimization Ship propeller design

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An Enhanced Imperialist competitive algorithm for optimum design of skeletal structures

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SWARM AND EVOLUTIONARY COMPUTATION 2018年 40卷 24-36页

作者： Maheri, Mahmoud R. Talezadeh, M. Shiraz Univ Dept Civil Engn Shiraz Iran

An Enhanced Imperialist competitive algorithm (EICA) is proposed aimed at enabling the ICA algorithm to escape from local optima faster, thus enabling faster convergence of the basic ICA algorithm. To this end, the imperialistic competition phase of the algorithm is enhanced by giving added value to a slightly unfeasible solution, based on its distance from the relative imperialist. The performance of the proposed EICA algorithm is investigated through design optimizations of four benchmark side-sway frames. Results indicate that, in terms of both the design quality and the solution speed, EICA compares significantly favourable with a number of other meta heuristic optimizers, including the basic ICA.

关键词： imperialistic competitive algorithm Design optimization Metaheuristic optimization algorithms Steel frames

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A novel hybrid ICA-ANFIS model for prediction of manufacturing processes performance

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING 2017年第2期231卷 181-190页

作者： Baseri, Hamid Belali-Owsia, Moosa Amirkabir Univ Technol Dept Mech Engn Tehran Iran Babol Univ Technol Dept Mech Engn Babol Sar Iran

In order to reduce the manufacturing process variability and improve the production yield, it is important to predict the performance of manufacturing process. The adaptive neuro-fuzzy inference system (ANFIS) is a powerful network which can predict the output parameters of manufacturing process. However, design of ANFIS needs trial and errors to select the best structure. In this study, an imperialistic competitive algorithm has been used to determine the ANFIS architecture to reach minimum values of the prediction error. In order to evaluate the performance of this combined method, two illustrative examples of manufacturing processes have been used. Results indicated that the combined method has superiority in prediction of output, rather than previous developed ANFIS models and so it can be applied for modeling of the other manufacturing processes.

关键词： Combined algorithm imperialistic competitive algorithm adaptive neuro-fuzzy inference system optimization

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Designing the Robust Fuzzy PI and Fuzzy Type-2 PI Controllers by Metaheuristic Optimizing algorithms for AVR System

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IETE JOURNAL OF RESEARCH 2022年第5期68卷 3540-3554页

作者： Modabbernia, Mohammadreza Alizadeh, Behnam Sahab, Alireza Mirhosseini Moghaddam, Maziar Islamic Azad Univ Dept Elect Engn Lahijan Branch Lahijan Iran

In this paper, two robust controllers have been designed to automatically regulate the synchronous generator voltage for an extensive domain of the system parameters in a single-machine infinite bus (SMIB) framework. These two controllers are based on the fuzzy set, and the type-2 fuzzy logic plus the proportional-integral (PI) operation, respectively. The Fuzzy and Type-2 fuzzy logic decisions are independent of the system parameters which increase the system robustness against the uncertainties and disturbances, and the PI controller can eliminate the terminal voltage steady-state error. The performance of the controllers has been optimized by adjustment of the four coefficients of each controller through Artificial Bee Colony, imperialistic competitive algorithm, and Particle Swarm Optimization (PSO). Five scenarios with four different patterns for reference input and disturbances have been considered to show the competency of the designed controllers. The simulations which have been done by PSO optimization results show the higher robustness of these controlling combination against the load fluctuations, the sequence of the input voltage, and changes in the system parameters, such as the gains and time constants of the amplifier, exciter, and generator in contrast to optimized PID with metaheuristic algorithms.

关键词： Artificial bee colony Automatic voltage regulator Fuzzy controller imperialistic competitive algorithm Particle swarm optimization Type-2 fuzzy logic controller

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A step beyond susceptibility: an adaptation of risk framework for monetary risk estimation of gully erosion

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NATURAL HAZARDS 2022年第2期111卷 1661-1684页

作者： Nalivan, Omid Asadi Badehian, Ziaedin Sadeghinia, Majid Soltani, Adel Islami, Iman Boustan, Ali Gorgan Univ Agr Sci & Nat Resources GUASNR Dept Watershed Management Gorgan Golestan Iran Lorestan Univ Coll Agr & Nat Resources Khorramabad Iran Ardakan Univ Fac Agr & Nat Resources Dept Nat Engn Ardakan Iran Payame Noor Univ Dept Agr Technol & Engn Tehran Iran Tarbiat Modares Univ Fac Nat Resources & Marine Sci Dept Rangeland Management Noor Iran Islamic Azad Univ Civil Engn Dept Kerman Branch Kerman Iran

In an effort to improve the previous gully susceptibility assessments in Iran, we attempted to conglomerate the notions of susceptibility, vulnerability, and exposure associated with gully occurrence across the northeast of the Golestan province in Iran to test the feasibility of the provided risk framework. The adaptive neuro-fuzzy inference system (ANFIS) and its ensemble with the imperialist competitive algorithm (ANFIS-ICA) were adopted to assess gully susceptibility. Based on various performance metrics, including Pierce's skill score, Heidke's skill score, Gilbert's skill score, and the area under the receiver operating characteristic curve, the ANFIS-ICA model with the respective values of 0.64, 0.637, 0.47, and 0.887 evidently outperformed the solitarily used ANFIS model due to being fused to a robust optimization algorithm. The results of susceptibility assessment revealed that about 24% of the study area falls within the highly susceptible zone to gully occurrences which stems from the interactive role of such factors as the red relief image map (RRIM), valley depth, average annual rainfall, distance from roads, and distance from streams. Moreover, the RRIM factor provided promising multi-featured morphological information that boosted the pattern recognition power of the susceptibility model. Gully risk assessment results indicated that approximately 6% of the area falls within the high-risk zone. The highest average values of the monetary risk mainly pertain to residential areas, moderately dense forests, orchards, dense forests, and roads, which would impose a sizable risk to the region in case of crisis. Superimposition of the susceptibility map over the monetary risk map showed that their shared areal coverage only accounts for 17.7%, and there is an 82.3% difference which, in turn, indicated that considering the risk map as an alternative to the previous susceptibility maps would considerably change the spatial allocation of the mitigation measures.

关键词： ANFIS imperialistic competitive algorithm Vulnerability Exposure Monetary risk

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Dynamic facility layout problem under competitive environment: a new formulation and some meta-heuristic solution methods

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PRODUCTION ENGINEERING-RESEARCH AND DEVELOPMENT 2016年第6期10卷 615-632页

作者： Kheirkhah, AmirSaman Bidgoli, Masume Messi Bu Ali Sina Univ Dept Ind Engn Hamadan Iran

Dynamic facility layout problem (DFLP) considers flow over multiple time periods in an environment where material flow between departments changes over time. These changes render the current facility layout inefficient and could increase material handling costs, which results in a need for dynamic layout models. But a key factor ignored for simplicity in the DFLP literature, is considering the effects of non-cooperating internal and external competitions on the mentioned changes in facility layout over time that sometimes results in main conflict of objectives/goals for these distinct decision makers. To the best our knowledge, the existing special literature did not cover this important assumption. Ignoring this main assumption resulted in the existing monopolistic models for DFLP that cannot satisfy the new needs in the nowadays competitive environments. Therefore, in this paper, a duopoly Bertrand non-cooperative game model is presented to consider the impacts of all conflicting factors on a DFLP for each period and three meta-heuristic algorithms are proposed to obtain Nash equilibrium for this model. The results obtained from solving some numerical examples with these algorithms show that the proposed simulated annealing algorithm is more effective than the others for the competitive dynamic facility layout problem.

关键词： Dynamic facility layout design Material handling system design Game theory Simulated algorithm imperialistic competitive algorithm

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Economic Emission Dispatch by Modified imperialistic Competition algorithm Considering Carbon Capture Power Plants

Economic Emission Dispatch by Modified Imperialistic Competi...

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International Conference on Circuit, Power and Computing Technologies (ICCPCT)

作者： Kuanr, Biswa Ranjan Das, Sudipta Das, Saborni Shekhar, Himanshu Lata, Madhavi Jadavpur Univ Power Engn Dept Kolkata India

ISBN: (纸本)9781479970759

With the advent of carbon capture and storage technology (CCS), carbon capture power plant (CCPP) has become a vital part of modern day power systems. However, introduction of CCPPs in power systems has a significant impact on dispatch strategies as CCS consumes energy for their operation though they reduce emission. In this work a Modified imperialistic Competition algorithm (MICA) based solution procedure is proposed for solving multi-objective Economic Emission Dispatch problem (EED) in a power system with CCPP. A fuzzy set theory based selection method is adopted for selecting the best compromise solution out of a set of non-dominated Pareto solutions of EED problem. Proposed approach is implemented on a 6-generator test system. Results demonstrate the effects of CCPP on economy and emission of the system and effectiveness of MICA in handling multi-objective non-linear optimization problems.

关键词： Economic Emission Dispatch Carbon capture and storage imperialistic competitive algorithm Multi-objective optimization

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imperialistic Competition Based Short-term Economic Emission Dispatch of Hydrothermal Power System with Cascaded Reservoirs

Imperialistic Competition Based Short-term Economic Emission...

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IEEE Power, Communication and Information Technology Conference (PCITC)

作者： Kuanr, Biswa Ranjan Shekhar, Himanshu Chakraborty, Niladri Jadavpur Univ Power Engn Dept Kolkata India

ISBN: (纸本)9781479974559

In this paper an imperialistic competition algorithm (ICA) based optimization technique is presented for solving the short-term economic emission dispatch (EED) problem in a hydrothermal system with cascaded reservoirs. Various operating constraints of the hydro system such as flow rate limit, reservoir storage volume limit, dynamic water balance, power generation limit and transportation delay between cascaded reservoirs are taken into account while for thermal units valve point effects and generation limits are considered in problem formulation. The bi-objective EED problem is converted to a single objective problem by price penalty factor approach. The proposed approach is successfully implemented on a test system comprising of three thermal units and four cascaded hydro units. A comparison of the result obtained by the proposed approach with those provided by other population based meta-heuristic techniques established proposed technique's superiority both in terms of result quality and computation time.

关键词： Economic emission dispatch Hydrothermal scheduling imperialistic competitive algorithm Multi-objective optimization

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An imperialistic Strategy Approach to Continuous Global Optimization Problem 16

An Imperialistic Strategy Approach to Continuous Global Opti...

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16th International Symposium on Symbolic and Numeric algorithms for Scientific Computing (SYNASC)

作者： Anescu, George Univ Politehn Bucuresti Power Plant Engn Fac Bucharest 060042 Romania

ISBN: (纸本)9781479984480

The paper is introducing the principles of a new global optimization strategy, imperialistic Strategy (IS), applied to the Continuous Global Optimization Problem (CGOP). Inspired from existing multi-population strategies, like the Island Model (IM) approaches to parallel Evolutionary algorithms (EA) and the imperialistic competitive algorithm (ICA), the proposed IS method is considered an optimization strategy for the reason that it can integrate other well-known optimization methods, which in the context are regarded as sub-methods (although in other contexts they are prominent global optimization methods). Four optimization methods were implemented and tested in the roles of sub-methods: Genetic algorithm (GA) (a floating-point representation variant), Differential Evolution (DE), Quantum Particle Swarm Optimization (QPSO) and Artificial Bee Colony (ABC). The optimization performances of the proposed optimization methods were compared on a test bed of 9 known multimodal optimization problems by applying an appropriate testing methodology. The obtained increased success rates of IS multi-population variants compared to the success rates of the optimization sub-methods run separately, combined with the increased computing efficiencies possible to be perceived for parallel and distributed implementations, demonstrated that IS is a promising approach to CGOP.

关键词： genetic algorithms parallel algorithms quantum computing ABC CGOP DE EA GA ICA IM IS multipopulation variants QPSO artificial bee colony continuous global optimization problem differential evolution distributed implementations floating-point representation variant genetic algorithm imperialistic competitive algorithm imperialistic strategy approach island model multimodal optimization problems multipopulation strategies parallel evolutionary algorithms parallel implementations quantum particle swarm optimization Biological cells Genetic algorithms Linear programming Optimization Sociology Statistics Vectors Artificial Bee Colony Continuous Global Optimization Problem Differential Evolution Genetic algorithm IS imperialistic competitive algorithm imperialistic Strategy Island Model Quantum Particle Swarm Optimization Genetic algorithm (GA) MT activity based costing Independent component analysis islet cell antibody Instant messaging Particle swarm optimization Gallium cytology Sociology Parallel algorithms quantum computing Policies and plans bee colonies linear programming

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