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Optimal Allocation of STATCOM to Enhance Transient Stability Using imperialist competitive algorithm

Intelligent Automation & Soft Computing 2023年第6期36卷 3425-3446页

作者： Ayman Amer Firas MMakahleh Jafar Ababneh Hani Attar Ahmed Amin Ahmed Solyman Mehrdad Ahmadi Kamarposhti Phatiphat Thounthong Department of Energy Zarqa UniversityZarqa13133Jordan Department of Mechanical Engineering Al-Zaytoonah University of JordanAmman11733Jordan Abdul Aziz Al Ghurair School of Advanced Computing(ASAC) Luminus Technical University CollegeJordan Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitecturesNisantasi UniversityIstanbulTurkey Department of Electrical Engineering Jouybar BranchIslamic Azad UniversityJouybarIran Renewable Energy Research Centre(RERC) Department of Teacher Training in Electrical EngineeringFaculty of Technical EducationKing Mongkut’s University of Technology North Bangkok1518Pracharat 1 RoadBangsueBangkok10800Thailand

With the daily expansion of global energy consumption,developing the power grids is of uttermost ***,building a new trans-mission line is costly and time-consuming,so utilizing the same lines with possible higher transmission capacity is very *** this regard,to increase the capacity of the transmission lines,the flexible alternating current transmission system(FACTS)has been widely used in power grids in recent years by industrialized *** of the essential topics in electrical power systems is the reactive power compensation,and the FACTS plays a significant role in controlling the reactive power current in the power grid and the system voltage oscillations and *** a static synchronous compensator(STATCOM)is embedded in a power system to increase the bus voltage,a supplementary damping controller can be designed to enhance the system oscillation *** the expansion of the grids in the power system,the complexity of their optimization and the extraordinary ability of the imperialist competitive algorithm(ICA)for solving such problems,in this paper,the ICA has been used to determine the optimal position and size of the FACTS devices.

关键词： STATCOM FACTS optimization transient stability imperialist competitive algorithm

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A novel permutation-diffusion technique for image encryption based on the imperialist competitive algorithm

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MULTIMEDIA TOOLS AND APPLICATIONS 2023年第1期82卷 725-746页

作者： Golalipour, Keyvan Islamic Azad Univ Sari Branch Dept Comp Engn Sari Iran

Recently, there has been explosive growth in the sharing of images on social media networks. This has occurred primarily because people are using smart phones with high quality imaging facilities and a mobile Internet connection. Accordingly, digital image security has formed a particular focus of recent research. Image encryption is the most common method used to keep images safe during their transmission over the Internet. There are two main phases in image encryption: permutation and diffusion. In this paper, a hybrid model is proposed, which is a combination of a novel permutation technique in conjunction with a new diffusion method. In the permutation phase of the suggested model, pixels are relocated based on their indices. The resulting permuted image has a high difference (more than 99.3%) in the gray level of pixels compared to the corresponding pixels in a plain image. The proposed diffusion method is based on a combination of an imperialist competitive algorithm (ICA) and adjacent lattices as a chaotic function. To date, the ICA, as an evolutionary algorithm, in combination with adjacent lattices, has never been exploited for image encryption. The result analysis demonstrates that the proposed method has excellent resistance against brute force and statistical attacks, in addition to obtaining a 7.9993 entropy score for the encrypted image.

关键词： Image encryption Permutation Coupled map lattice imperialist competitive algorithm

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An imperialist competitive algorithm for distributed assembly flowshop scheduling with Pm→ 1 layout and transportation

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2023年第1期45卷 269-284页

作者： Lei, Deming Du, Haoyang Tang, Hongtao Wuhan Univ Technol Sch Automat Wuhan Peoples R China

Distributed assembly flow shop scheduling problem (DAFSP) has been extensively considered;however, DAFSP with Pm -> 1 layout, in which m parallel machines are at fabrication stage and one machine is at assembly stage, is seldom handled. In this study, DAFSP with the above layout and transportation time is studied and an imperialist competitive algorithm with cooperation and division (CDICA) is presented to minimize makespan. Feature of the problem is used and a heuristic is applied to produce initial solution. Adaptive assimilation and evolution are executed in the weakest empire and adaptive cooperation is implemented between the winning empire and the weakest empire in imperialist competition process. Empire division is performed when a given condition is met. Many experiments are conducted. The computational results demonstrate that new strategies are effective and CDICA is a very competitive in solving the considered DAFSP.

关键词： Assembly scheduling problem distributed scheduling imperialist competitive algorithm cooperation

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Improvement of Microgrids Operation Considering Demand Response Using imperialist competitive algorithm 12

Improvement of Microgrids Operation Considering Demand Respo...

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12th International Conference on Smart Energy Grid Engineering

作者： Ghaffari, Mahdi Aly, Hamed H. Dalhousie Univ Elect & Comp Engn Dept Smart Grid & Green Power Res Lab Halifax NS Canada

ISBN: (纸本)9798350377385;9798350377378

In recent years, with the restructuring and privatization of power networks, special attention has been paid to the role of customers in network operation. Therefore, demand response programs have played an important role in power network studies and many researchers have been working in this area. Microgrids are a collection of loads and generating units that can supply their own power independently. In this article, the problem of demand response of loads in a microgrid has been studied. For this purpose, the customers in a microgrid announce their proposed prices for participating in the demand response program to the network operator for different hours of the day. This demand response program will be executed when the network operation constraints are violated. Therefore, there is no need to run it in the hours when the network is operating properly. The network operator will run the demand response program with the aim of removing the constraints imposed on the network. For this purpose, the imperialist competitive algorithm (ICA) has been used to find the best possible solution. After running the proposed method, it will be determined how much power each load should reduce in each hour. The proposed method has been implemented on a sample network and its results have been evaluated and analyzed for different scenarios. The problem modeling has been done using MATLAB software. The results proved the effectiveness of the proposed model.

关键词： Demand Response Microgrid imperialist competitive algorithm

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Intelligent Manufacturing Systems Problem with AGV transportation consideration based on Hybrid imperialist competitive algorithm 4

Intelligent Manufacturing Systems Problem with AGV transport...

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4th International Conference on Computer Communication and Artificial Intelligence (CCAI)

作者： Dong, Yuan Rui, Zhou Li, Xiaohui Zhao, Yi ChangAn Univ Sch Elect & Control Engn Xian Peoples R China

ISBN: (纸本)9798350362770;9798350362763

This paper delves into the problem of scheduling manufacturing workshop operations with multiple Automated Guided Vehicles (AGVs), aiming to minimize the maximum completion time. To tackle this issue, a novel approach based on the imperialist competitive algorithm is proposed with the integration of a disjunctive graph-based critical path method and a variable neighborhood descent method. Furthermore, the variable neighborhood descent. This enhances the algorithm's optimization capability prevents it from getting trapped in local optimal. Through comprehensive experiments on the test datasets, the effectiveness and stability of the proposed algorithm are validated.

关键词： Intelligent Manufacturing Systems imperialist competitive algorithm Neighborhood Structure Critical Path

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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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An improved multi-objective imperialist competitive algorithm for surgical case scheduling problem with switching and preparation times

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CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2022年第5期25卷 3591-3616页

作者： Yu, Hui Li, Jun-qing Chen, Xiao-long Niu, Wei Sang, Hong-yan Shandong Normal Univ Sch Informat Sci & Engn Jinan 250000 Peoples R China Liaocheng Univ Sch Informat Liaocheng 252059 Shandong Peoples R China

Surgical case scheduling is a key issue in the field of medician, which is a challenging work because of the difficulty in assigning resources to patients. This study regards the surgical case scheduling problem as a flexible job shop scheduling problem (FJSP). Considering the switching and preparation time of patients in different stage, an improved multi-objective imperialist competitive algorithm (IMOICA), which adopts the non-dominant sorting method, is proposed to optimize the whole scheduling. First, the social hierarchy strategy is developed to initialize the empire. Then, to enhance the global search ability of the algorithm, the concept of attraction and repulsion (AR) is introduced into the assimilation strategy. Moreover, to increase the diversity of the population, the revolution strategy is utilized. Finally, the variable neighborhood search (VNS) strategy is embedded to improve its exploitation capacity further. Experiments show that scheduling in advance saves time and cost, and IMOICA can solve the surgical case scheduling problem studied efficiently.

关键词： Surgical case scheduling imperialist competitive algorithm Variable neighborhood search strategy

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An imperialist competitive algorithm with adaptive cooperation for resource-constrained unrelated parallel machines scheduling with setup time 35

An imperialist competitive algorithm with adaptive cooperati...

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35th Chinese Control and Decision Conference (CCDC)

作者： Dai, Fengteng Lei, Deming Wuhan Univ Technol Sch Automat Wuhan Peoples R China

ISBN: (纸本)9798350334722

Resource-constrained unrelated parallel machine scheduling problem (RLIPMSP) has been extensively considered;however, RUPMSP with setup time is seldom studied. In this study, RUPNISP with sequence-dependent setup time (SDST) is investigated and an imperialist competitive algoirthrn with adaptive cooperation (AYIICA) is presented to minimize total tardiness. for two strongest empires, two cooperation methods between them are given, adaptive selection based on the ratio of their normalized total cost is implemented to choose a cooperation way, the weakest empire support is executed by using their good solutions, and a new imperialit competition is presented. A number of experiments are conducted on 70 instances from the literature. The computational results demonstrate that the new strategies are effective and ACICA can provide better results than the algorithms from the literature.

关键词： Parallel machines scheduling imperialist competitive algorithm additional resource adaptive cooperation

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An efficient hybrid approach based on Harris Hawks optimization and imperialist competitive algorithm for structural optimization

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ENGINEERING WITH COMPUTERS 2022年第SUPPL 2期38卷 1555-1583页

作者： Kaveh, A. Rahmani, P. Eslamlou, A. Dadras Iran Univ Sci & Technol Sch Civil Engn POB 16846-13114 Tehran 16 Narmak Iran

In this paper, a new hybrid algorithm is introduced, combining two Harris Hawks Optimizer (HHO) and the imperialist competitive algorithm (ICA) to achieve a better search strategy. HHO is a new population-based, nature-inspired optimization algorithm that mimics Harris Hawks cooperative behavior and chasing style in nature called surprise pounce HHO. It is a robust algorithm in exploitation, but has an unfavorable performance in exploring the search space, while ICA has a better performance in exploration;thus, combining these two algorithms produces an effective hybrid algorithm. The hybrid algorithm is called imperialist competitive Harris Hawks Optimization (ICHHO). The proposed hybrid algorithm's effectiveness is examined by comparing other nature-inspired techniques, 23 mathematical benchmark problems, and several well-known structural engineering problems. The results successfully indicate the proposed hybrid algorithm's competitive performance compared to HHO, ICA, and some other well-established algorithms.

关键词： Hybrid algorithm Harris Hawks optimization imperialist competitive algorithm Benchmark functions Truss structures

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Sentiment Classification Using Two Effective Optimization Methods Derived From The Artificial Bee Colony Optimization And imperialist competitive algorithm

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COMPUTER JOURNAL 2022年第1期65卷 18-66页

作者： Osmani, Amjad Mohasefi, Jamshid Bagherzadeh Gharehchopogh, Farhad Soleimanian Islamic Azad Univ Dept Comp Engn Urmia Branch Orumiyeh Iran Urmia Univ Dept Comp Engn Orumiyeh Iran

Artificial bee colony (ABC) optimization and imperialist competitive algorithm (ICA) are two famous metaheuristic methods. In ABC, exploration is good because each bee moves toward random neighbors in the first and second phases. In ABC, exploitation is poor because it does not try to examine a promising region of search space carefully to see if it contains a good local minimum. In this study, ICA is considered to improve ABC exploitation, and two novel swarm-based hybrid methods called ABC-ICA and ABC-ICA1 are proposed, which combine the characteristics of ABC and ICA. The proposed methods improve the evaluations results in both continuous and discrete environments compared to the baseline methods. The second method improves the first optimization method as well. Feature selection can be considered to be an optimization problem because selecting the appropriate feature subset is very important and the action of appropriate feature selection has a great influence on the efficiency of classifier algorithms in supervised methods. Therefore, to focus on feature selection is a key issue and is very important. In this study, different discrete versions of the proposed methods have been introduced that can be used in feature selection and feature scoring problems, which have been successful in evaluations. In this study, a problem called cold start is introduced, and a solution is presented that has a great impact on the efficiency of the proposed methods in feature scoring problem. A total of 16 UCI data sets and 2 Amazon data sets have been used for the evaluation of the proposed methods in feature selection problem. The parameters that have been compared are classification accuracy and the number of features required for classification. Also, the proposed methods can be used to create a proper sentiment dictionary. Evaluation results confirm the better performance of the proposed methods in most experiments.

关键词： optimization methods sentiment classification imperialist competitive algorithm artificial bee colony feature selection

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