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Simultaneous multi-objective optimization method for trading indicators

RESULTS IN CONTROL AND OPTIMIZATION 2024年 17卷

作者： Nguyen, Nhat M. Tran, Minh Ho Chi Minh City Univ Banking 36 Ton That Dam StNguyen Thai Binh WardDist 1 Ho Chi Minh City 700000 Vietnam

This paper proposes a novel framework for optimizing trading indicators using a multi-objective Particle Swarm Optimization approach. By simultaneously optimizing multiple technical indicators, the method overcomes the limitations of single-objective optimization and complex strategies, resulting in a more robust trading approach. Experiments on VN30-Index daily data demonstrate that the optimized strategy outperforms benchmark and buy-and-hold strategies in terms of returns and Sharpe ratios. Our findings prove that the multi-objective Particle Swarm Optimization method efficiently balances the complexity to combine various technical indicators in a way that keeps the logic of the strategy simple. The technique not only reduces the risks of relying on one indicator but also reduces behavioral influences in the stock selection process. Furthermore, our study adds to the literature a simple and effective method that helps traders identify profitable investment opportunities in different market scenarios.

关键词： multi-objective function Particle swarm optimization Bollinger Bands Moving average convergence divergence Trading strategy optimization

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Optimization of Material Distribution Route Based on Green Logistics and Ant Colony Algorithm 6

Optimization of Material Distribution Route Based on Green L...

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6th International Symposium on Computer Science and Intelligent Control (ISCSIC)

作者： Xu, TianTian Chen, TianMei Zhang, Ying Yu, ChenXi State Grid Zhejiang Producement Co Enterprise Supply Chain Operat Ctr 378 Fengqi Ave Hangzhou 310003 Zhejiang Peoples R China

ISBN: (纸本)9781665454889

Aiming at the problem of slow development of electric logistics due to the low efficiency of traditional electric materials distribution, an optimization method of material distribution route based on ant colony algorithm was proposed. First of all, the multi-objective function was constructed based on customer satisfaction and the shortest distribution distance. Then, combined with the disadvantages of the traditional ant colony algorithm, the pheromone, volatile factor and heuristic factor of the ant colony algorithm were improved to solve the multi-objective function. Finally, the effectiveness of the algorithm was verified by simulation test. Simulation results showed that compared with traditional ant colony algorithm, when the number of terminal distribution points is 20, the shortest distribution distance obtained by the optimized ant colony algorithm is reduced by 1.7%, and the convergence speed of the algorithm is improved by 34.5%. Therefore, the optimized ant colony algorithm is better than the traditional ant colony algorithm, which can improve the distribution efficiency of electric power material.

关键词： ant colony algorithm multi-objective function route optimization green logistics

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A GA-Based Method for Computing MOF-Weighting Coefficients Along with Optimal Location and Sizing of DG Sources in Distribution Systems 21

A GA-Based Method for Computing MOF-Weighting Coefficients A...

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21st International Middle East Power Systems Conference (MEPCON)

作者： Abdel-Salam, Mazen El-Mohandes, Mohamed Th Yousef, Ali M. Abdel-Hakim, Alaa E. Ramadan, Reham Assiut Univ Dept Elec Engn Assiut Egypt

ISBN: (纸本)9781728152899

Minimization of a weighted-sum multi-objective-objective function (MOF) is aimed at obtaining the optimal locations and sizes of multi DG sources in distribution networks. The indices of the MOF are related to the characteristics of the distribution network including active power loss, deviation of bus voltage from nominal value and reactive power loss. In the literature, the weighting coefficients were assumed arbitrarily or determined according to the preferences of the decision maker. To the authors' knowledge, this paper presents -for the first time- a Genetic Algorithm (GA) based method for computing the weighting coefficients while minimizing the MOF of the distribution network. The GA optimization is applied for the MOF after being penalty-formulated to avoid violation of distribution-network constraints. The index priority of the MOF is always given to the deviation of bus voltage from nominal value in conformity to power quality features as no sag or swell of bus voltage is allowed. The computed optimal locations and sizes of the DG sources agreed reasonably with those obtained using PSO, the particle swarm optimization, for a well-recognized distribution network.

关键词： GA technique single-objective function multi-objective function sag swell weighting coefficients

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Application of multi-objective genetic algorithm for optimal design of SSSC based robust damping controllers to improve small signal stability

Application of multi-objective genetic algorithm for optimal...

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IEEE/PES Power Systems Conference and Exposition

作者： Ladjavardi, M. Masoum, M. A. S. Curtin Univ Technol Dept Elect & Comp Engn Perth WA 6001 Australia

ISBN: (纸本)9781424401772

A new genetic approach is proposed for optimal selection of the Static Synchronous Series Compensator (SSSC) based conventional lead-lag damping controller parameters. The parameters are tuned in order to shift the lightly damped and undamped modes under various loading conditions toward the prescribed stability region. The objective function includes system stability criteria (e.g., damping factor and damping ratio of the eigenvalues for all operating points under consideration) and boundaries of controller parameters (as constraints), enforcing their simultaneous improvement. The robustness is achieved by considering several loading conditions. The work relies on Genetic Algorithm (to capture the near global solution), analysis of mode observability (to select the effective feedback signal for the damping controller) and the theoretical analysis of a Single-Machine Infinite-Bus (SMIB), using its modified linearized Phillips-Heffron model installed with SSSC. It is shown that the results could easily be extended for multi Machine Power Systems. Simulation results are presented to show the fine performance of the proposed SSSC controller in damping the critical modes under different loading conditions without significantly deteriorating damping characteristics of other modes in a SMIB power system.

关键词： SSSC damping controller robust genetic algorithm multi-objective function and small signal stability

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Based on the B-splines to Smooth the Trajectory Planning of Composite Parallel Four-Bar Mechanism

Based on the B-splines to Smooth the Trajectory Planning of ...

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2nd International Conference on Measurement, Instrumentation and Automation (ICMIA 2013)

作者： Zhang, Jianjun Zhang, Zuolong Liu, Qishuai China Univ Petr Coll Mech & Elect Engn Qingdao Peoples R China

ISBN: (纸本)9783037857519

The composite parallel four-bar manipulator multi-objective function simulation by B-splines shows the new method for multi-objective planning trajectory of manipulator is effective. The algorithm minimizes the objective function for optimization. By setting restriction on acceleration, the method has been tested in simulation yielding good results which get the smooth trajectory through the via-points by fourth-order B-splines.

关键词： B-splines Trajectory planning multi-objective function Composite parallel four-bar mechanism

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Detection and prevention of black-hole and wormhole attacks in wireless sensor network using optimized LSTM

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INTERNATIONAL JOURNAL OF PERVASIVE COMPUTING AND COMMUNICATIONS 2023年第1期19卷 124-153页

作者： Pawar, Mohandas V. J., Anuradha VIT Univ Vellore Tamil Nadu India

Purpose This study aims to present a novel system for detection and prevention of black hole and wormhole attacks in wireless sensor network (WSN) based on deep learning model. Here, different phases are included such as assigning the nodes, data collection, detecting black hole and wormhole attacks and preventing black hole and wormhole attacks by optimal path communication. Initially, a set of nodes is assumed for carrying out the communication in WSN. Further, the black hole attacks are detected by the Bait process, and wormhole attacks are detected by the round trip time (RTT) validation process. The data collection procedure is done with the Bait and RTT validation process with attribute information. The gathered data attributes are given for the training in which long short-term memory (LSTM) is used that includes the attack details. This is used for attack detection process. Once they are detected, those attacks are removed from the network using the optimal path selection process. Here, the optimal shortest path is determined by the improvement in the whale optimization algorithm (WOA) that is called as fitness rate-based whale optimization algorithm (FR-WOA). This shortest path communication is carried out based on the multi-objective function using energy, distance, delay and packet delivery ratio as constraints. Design/methodology/approach This paper implements a detection and prevention of attacks model based on FR-WOA algorithm for the prevention of attacks in the WSNs. With this, this paper aims to accomplish the desired optimization of multi-objective functions. Findings From the analysis, it is found that the accuracy of the optimized LSTM is better than conventional LSTM. The energy consumption of the proposed FR-WOA with 35 nodes is 7.14% superior to WOA and FireFly, 5.7% superior to grey wolf optimization and 10.3% superior to particle swarm optimization. Originality/value This paper develops the FR-WOA with optimized LSTM detecting and preventing

关键词： Wireless sensor networks Black hole attacks Wormhole attacks Fitness rate-based whale optimization algorithm Long term short memory Bait process Round trip time Shortest path communication multi-objective function

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Optimization of 6.5 GHz CMOS Low Noise Amplifier Applying multi-objective Firefly Algorithm 5

Optimization of 6.5 GHz CMOS Low Noise Amplifier Applying Mu...

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5th Iranian International Conference on Microelectronics (IICM)

作者： Babasafari, Maryam Yargholi, Mostafa Mostafavi, Mohammad Univ Zanjan Dept Elect Engn Zanjan Iran

ISBN: (纸本)9798350360196

This paper demonstrates an optimal low-noise amplifier (LNA) design with applying Firefly Algorithm (FA). To optimize the noise figure (NF) and gain (similar to the input and output matching and linearity) the FA is charity, although validating entirely the design constraints. Subsequently, there are five objectives for optimizing;they may treat as multio-bjective optimization. Weighted sum access is accustomed to alter these purposes to a single objective function. The Weights are set consistent through the objective function precedence. The recommended LNA has a cascode manufacture with an inductive source degeneration circuit for usage at 6.5 GHz frequency;it is exploited to implement in ADS software at the UMC 0.18 mu m CMOS technology through a 1.8 V supply voltage. The considered LNA has simulated assessments: Input reflection coefficient (S11) of -21dB, Output reflection coefficient (S22) of -14 dB, Voltage gain (S21) of 19.74 dB, noise figure (NF) of 1.42 dB, and IIP3 of -3 dBm at 6.5 GHz. The optimized LNA parameter assessment utilizing FA, at what time simulated in MATLAB situation, is instituted to be -26.46 dB, -18.41 dB, 20.51 dB, 1.29 dB and 0.325 dBm for S11, S22, S21, NF, and IIP3, respectively. The FA execution in optimizing the LNA parameters is also associated through the execution of comparable fashionable algorithms similar particle swarm optimization (PSO) and cuckoo search algorithm (CSA). The consequences completely verify the FA's superiority ended additional approaches in expressions of its computational consistency and proficiency.

关键词： Firefly Algorithm (FA) Low Noise Amplifier multi-objective function

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Inverse Optimal Controller Design Based on multi-objective Optimization Criteria for Discrete-Time Nonlinear Systems 7

Inverse Optimal Controller Design Based on Multi-Objective O...

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7th IEEE Palestinian International Conference on Electrical and Computer Engineering (PICECE)

作者： Almobaied, Moayed Eksin, Ibrahim Guzelkaya, Mujde Islamic Univ Gaza Elect Engn Dept Gaza Palestine Istanbul Tech Univ Control & Automat Dept Istanbul Turkey

ISBN: (纸本)9781538662915

This paper proposes an inverse optimal controller design method for discrete-time affine nonlinear systems that relies on a multi-objective optimization criterion. Inverse optimal control approach circumvents the tedious task of solving the Hamilton-Jacobi-Bellman equation (HJB) that results from the classical solution of the nonlinear optimal control problem. Here, the inverse optimal controller is based on defining an appropriate quadratic control Lyapunov function (CLF) where the parameters of this candidate CLF were optimized in an off-line manner by using Big Bang-Big Crunch algorithm. The root-mean-square-error (RMSE) of system states with respect to a reference trajectory and the sum-of-squares of control effort are utilized as the multi-objective optimization criterion in the Big Bang-Big Crunch optimizing algorithm. In order to test the performance of the proposed method, a nonlinear example from the literature of inverse optimal control is taken into consideration. The simulation results enlighten the designer in making a choice between the classical inverse optimal control solution and the multi-objective function included case.

关键词： Inverse optimal control Hamilton-Jacobi-Bellman (HJB) Big Bang-Big Crunch algorithm (BB-BC) multi-objective function

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Optimal Allocation of STATCOM using Improved Sine Cosine Optimization Algorithm 8

Optimal Allocation of STATCOM using Improved Sine Cosine Opt...

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8th IEEE India International Conference on Power Electronics (IICPE)

作者： Singh, Pradeep Tiwari, Rajive Malaviya Natl Inst Technol Dept Elect Engn Jaipur Rajasthan India

ISBN: (纸本)9781538649961

As the power system continuously operates under stressed condition due to various constraints, i.e. economic, right of way and regulations etc. FACTS devices are used to provide flexible control of the power systems. STATCOM is used to control the various parameters of the power system either by injecting or absorbing the reactive power but subjected to the cost. Therefore, this paper concerns with the optimal number, location and size of holomorphic embedded load-flow (HELF) model of STATCOM in the multi-bus power systems using improved sine cosine optimization algorithm (ISCA). The IEEE 30-bus test system is considered to validate the algorithm for optimal allocation of HELF model. The results are also compared with the sine-cosine algorithm (SCA) and grey wolf optimization (GWO).

关键词： HELF multi-objective function ISCA Fuzzy logic FACTS devices

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Fuzzy optimal power flow with multi-objective based on artificial bee colony algorithm in power system

Fuzzy optimal power flow with multi-objective based on artif...

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International Conference on Renewable Energy and Environmental Technology (REET 2013)

作者： He, Xuanhu Wang, Wei Wang, Yingnan Kong, Jun Geng, Jing Fan, Shengbin Beijing JiaoTong Univ Sch Elect Engn Beijing Peoples R China

ISBN: (纸本)9783037859124

According to the problem of optimal power flow (OPF), the optimization objectives including minimization of total fuel cost for generating units, minimization of emission for atmospheric pollutants, minimization of active power losses and minimization of voltages deviations are established. The paper uses fuzzy membership functions instead of multi-objective functions to form fuzzy optimal power flow in the optimal power flow calculation process. The novel artificial bee colony (ABC) algorithm is proposed to solve OPF problem with multi-objective. The proposed approach is applied to the OPF problem on IEEE30 test systems. And the simulation results verify the effectiveness of the proposed method.

关键词： Power System Optimal Power Flow Fuzzy Mathematics multi-objective function Artificial Bee Colony Algorithm

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