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Application of multi-objective optimization genetic algorithm to design terahertz metamaterials with fano resonances

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PHYSICA SCRIPTA 2024年第6期99卷 065555-065555页

作者： Qin, Binyi Li, Yun Liao, Qitao Qiu, Jie Yang, Ruizhao Zheng, Jincun Zhong, Hesen Yulin Normal Univ Ctr Appl Math Guangxi Yulin 537000 Peoples R China Yulin Normal Univ Guangxi Coll & Univ Key Lab Complex Syst Optimizat & Big Data Proc Yulin 537000 Peoples R China Yulin Normal Univ Res Ctr Intelligent Informat & Commun Technol Sch Phys & Telecommun Engn Yulin 537000 Peoples R China Yulin Normal Univ Sch Chem & Food Sci Yulin 537000 Peoples R China Yulin Normal Univ Sch Phys & Telecommun Engn Yulin 537000 Peoples R China Yulin Normal Univ Sch Comp Sci & Engn Yulin 537000 Peoples R China Yulin Normal Univ Optoelect Informat Res Ctr Sch Phys & Telecommun Engn Yulin 537000 Peoples R China

In the prosperous development of terahertz (THz) metamaterials, Fano resonances have gained attention due to their potential applications in ultrasensitive systems. The performance of Fano resonance is directly influenced by the geometrical parameters of the element structure. However, the traditional design rules for Fano resonances in metamaterials rely on an empirical trial-and-error strategy, necessitating significant effort to achieve optimal results. To address this issue, we propose a design method in this study that utilizes the finite integration technique in time domain (FITD) along with a multi-objective optimization genetic algorithm for the intelligent design of metamaterial structures exhibiting the Fano resonance phenomenon. The FITD method is primarily used to calculate the Fano resonance with different metamaterial geometric structure parameters, while the genetic algorithm efficiently selects the optimal solution. Our method, characterized by high efficiency and complete independence from prior knowledge, could offer a new design technique for metamaterials with specific functions, thereby contributing to the development of THz applications.

关键词： Terahertz metamaterials design fano resonances multi-objective optimization non-dominated sorting genetic algorithm

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Optimal design of multichannel fiber Bragg grating filters using Pareto multi-objective optimization algorithm

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OPTICS COMMUNICATIONS 2016年 358卷 59-64页

作者： Chen, Jing Liu, Tundong Jiang, Hao Xiamen Univ Sch Informat Sci & Engn Xiamen 361005 Peoples R China Fuzhou Univ Coll Elect Engn & Automat Fuzhou 350108 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

A Pareto-based multi-objective optimization approach is proposed to design multichannel FBG filters. Instead of defining a single optimal objective, the proposed method establishes the multi-objective model by taking two design objectives into account, which are minimizing the maximum index modulation and minimizing the mean dispersion error. To address this optimization problem, we develop a two-stage evolutionary computation approach integrating an elitist non-dominated sorting genetic algorithm (NSGA-II) and technique for order preference by similarity to ideal solution (TOPSIS). NSGA-ll is utilized to search for the candidate solutions in terms of both objectives. The obtained results are provided as Paretic) front. Subsequently, the best compromise solution is determined by the TOPSIS method from the Paretic) front according to the decision maker's preference. The design results show that the proposed approach yields a remarkable reduction of the maximum index modulation and the performance of dispersion spectra of the designed filter can be optimized simultaneously. (C) 2015 Elsevier B.V. All rights reserved

关键词： Fiber Bragg grating (FBG) Multichannel filter Multi-objective optimization non-dominated sorting genetic algorithm

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A Memetic Evolutionary Multi-Objective Optimization Method for Environmental Power Unit Commitment

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IEEE TRANSACTIONS ON POWER SYSTEMS 2013年第3期28卷 2660-2669页

作者： Li, Yan-Fu Pedroni, Nicola Zio, Enrico Ecole Cent Paris European Fdn New Energy Elect France Paris France Supelec Paris France Politecn Milan I-20133 Milan Italy

A multi-objective power unit commitment problem is framed to consider simultaneously the objectives of minimizing the operation cost and minimizing the emissions from the generation units. To find the solution of the optimal schedule of the generation units, a memetic evolutionary algorithm is proposed, which combines the non-dominated sorting genetic algorithm-II (NSGA-II) and a local search algorithm. The power dispatch sub-problem is solved by the weighed-sum lambda-iteration approach. The proposed method has been tested on systems composed by 10 and 100 generation units for a 24-hour demand horizon. The Pareto-optimal front obtained contains solutions of different trade off with respect to the two objectives of cost and emission, which are superior to those contained in the Pareto-front obtained by the pure NSGA-II. The solutions of minimum cost are shown to compare well with recent published results obtained by single-objective cost optimization algorithms.

关键词： Environmental/economic dispatch evolutionary algorithm lambda-iteration approach local search memetic algorithm multi-objective optimization non-dominated sorting genetic algorithm power unit commitment

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No_x conversion efficiency optimization based on NSGA-II and state-feedback nonlinear model predictive control of selective catalytic reduction system in diesel engine

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APPLIED ENERGY 2017年 206卷 959-971页

作者： Wei, Li Yan, Fuwu Hu, Jie Xi, Guangwei Liu, Bo Zeng, Jiawei Wuhan Univ Technol Hubei Key Lab Adv Technol Automot Components Wuhan 430070 Hubei Peoples R China Hubei Collaborat Innovat Ctr Automot Components T Wuhan 430070 Hubei Peoples R China

The selective catalytic reduction (SCR) technology is a promising diesel after-treatment technology due to its high NOx reduction potential. A nonlinear model predictive control (NMPC) approach was proposed based on the three-state SCR model here for control and optimization of SCR system to maximize NOx reduction while minimizing NH3 slip and urea consumption;moreover, the ammonia coverage ratio was designed to as a control target, whose desired range was obtained by means of the singular perturbation method, that is to say, the upper limit of ammonia coverage ratio was derived by 10 ppm NH3 slip while the lower limit was calculated by maximum NOx conversion efficiency, which was obtained through a novel model based non-dominated sorting genetic algorithm (NSGA-II) according to an optimum tradeoff between NOx . conversion and NH3 slip at each engine operating point. The state-feedback NMPC algorithm was applied to ensure the estimated ammonia coverage ratio falling in the desired range so that the SCR performance can be optimized over entire engine operating. The standard European steady-state cycle (ESC) was performed for data generation from a diesel engine equipped with a commercial SCR and to verify the effectiveness of the designed control strategy. Simulation results over-the entire ESC indicated that the NOx conversion efficiency may be optimal in various engine operating modes and the NMPC controller ensures the most part of the cycle may conform to the NOx emissions requirements;moreover, the downstream NH3 concentration was less than the limit;especially, the whole mean NH3 slip was 9.7 ppm which is basically close to the given limit (10 ppm);furthermore, the ammonia storage capacity falls rapidly along with growth of the temperature but the NMPC still worked well for prevention of any unacceptably high NH3 slip. The experimental verification was carried out and the results showed that the designed strategy was effective and acceptable compared with the s

关键词： Selective catalytic reduction system Ammonia coverage ratio reference non-dominated sorting genetic algorithm nonlinear model predictive control Diesel emissions control

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Optimisation of process parameters in friction stir welding based on residual stress analysis: a feasibility study

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SCIENCE AND TECHNOLOGY OF WELDING AND JOINING 2010年第5期15卷 369-377页

作者： Tutum, C. C. Hattel, J. H. Tech Univ Denmark Dept Mech Engn Sect Mfg Engn DK-2800 Lyngby Denmark

The present paper considers the optimisation of process parameters in friction stir welding (FSW). More specifically, the choices of rotational speed and traverse welding speed have been investigated using genetic algorithms. The welding process is simulated in a transient, two-dimensional sequentially coupled thermomechanical model in ANSYS. This model is then used in an optimisation case where the two objectives are the minimisation of the peak residual stresses and the maximisation of the welding speed. The results indicate that the objectives for the considered case are conflicting, and this is presented as a Pareto optimal front. Moreover, a higher welding speed for a fixed rotational speed results, in general, in slightly higher stress levels in the tension zone, whereas a higher rotational speed for a fixed welding speed yields somewhat lower peak residual stress, however, a wider tension zone, leading to a substantially higher residual tensile force.

关键词： Friction stir welding Thermal pseudomechanical model Residual stress Constrained multiobjective optimisation non-dominated sorting genetic algorithm

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Agent-Based Modeling for Evaluation of Crop Pattern and Water Management Policies

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WATER RESOURCES MANAGEMENT 2019年第11期33卷 3707-3720页

作者： Nouri, Alireza Saghafian, Bahram Delavar, Majid Bazargan-Lari, Mohammad Reza Islamic Azad Univ Dept Civil Engn Sci & Res Branch Tehran Iran Tarbiat Modares Univ Dept Water Resources Engn Tehran Iran Islamic Azad Univ East Tehran Branch Dept Civil Engn Tehran Iran

The objective of the present paper is to propose a framework for development of an optimal cropping pattern aimed at ground water recovery using an agent based approach. In the proposed agent-based model (ABM), the agents' learning from each other as well as their self-learning from their own behavioral feedback was studied through simulation of the behavior of agricultural agents using fuzzy inference system (FIS). Moreover, the agents' behavior were determined using linear programming in order to maximize the farmers' income. The governmental agent regulated the interactions between agricultural and environmental agents by imposing its policies in the form of scenarios. The efficiency of the presented methodology was evaluated using hydrological data of Najaf Abad region, located in Iran's central plain, on the basis of three hydrological scenarios (wet, normal, and dry) subject to governmental policy of aquifer recovery. The results showed that in a normal scenario with current groundwater withdrawal, the water level reduced by an average of 0.18 m per year. In contrast, the water level increased by an average of 0.48 m under aquifer recovery scenario. Furthermore, despite 17% reduction in water rights of agricultural agents in the study area, the total long-term agricultural income declined only by less than 4%, and in the planning horizon, their average annual income associated with these two management scenarios were estimated at 123.5 and 119 million US dollars, respectively.

关键词： Agent Based Model Fuzzy Inference System Behavioral Constraints Ground Water Recovery non-dominated sorting genetic algorithm

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A fine-grained parallel approach for the registration areas optimization

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LOGIC JOURNAL OF THE IGPL 2017年第6期25卷 862-876页

作者： Berrocal-Plaza, Victor Vega-Rodriguez, Miguel A. Sanchez-Perez, Juan M. Univ Extremadura Dept Comp & Commun Technol Escuela Politecn Campus Univ S-N Caceres Spain

Mobility management is one of the most important operations in any public land mobile network. For idle terminals, most of mobility management strategies consist of two main procedures: subscriber's location update and paging. These two procedures define a multiobjective optimization problem in which the challenge is to find the network configurations that minimize the number of location updates and the number of paging messages. In this optimization process, the use of accurate information is very important to find the network configurations that best match the subscribers' activity in a mobile network. A mobile activity trace is a very accurate way for representing the subscribers' activity in a mobile network in form of a chronological list of events related to the subscribers' movements and the incoming and outgoing calls. This kind of representation can be used to study the performance of any mobility management strategy at the expense of considerably increasing the time needed to evaluate the objective functions. In fact, we show that more than 99% of the optimizer runtime is used to evaluate the objective functions. With the aim of facing this problem, we propose a fine-grained parallel approach focused on parallelizing the objective functions exclusively. Results show that the efficiency of our approach is always higher than 50% and that the optimizer runtime is drastically reduced.

关键词： OpenMP non-dominated sorting genetic algorithm mobile location management registration areas

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An Integrated Approach Based on MADM and MODM for Order Picking System Considering Human Factors

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2024年第5期23卷 2017-2064页

作者： Nikkhoo, Fatemeh Kashan, Ali Husseinzadeh Ostadi, Bakhtiar Nikbakhsh, Ehsan Tarbiat Modares Univ Fac Ind & Syst Engn Tehran Iran

Optimizing order-picking systems (OPSs) while considering human factors and integrating key decisions is a major challenge for warehouse managers. This study presents a two-stage framework based on multi-attribute decision-making (MADM) and multi-objective decision-making (MODM) models to integrate decisions on picker selection, order batching, batch assignment, picker routing, and scheduling. In the first stage, the human factors affecting picker selection are considered as the problem's criteria and the available pickers are treated as alternatives. The fuzzy entropy method and fuzzy COmplex PRoportional ASsessment (COPRAS) are used to weight the factors and rank the pickers, respectively. In the second stage, a three-objective mathematical model is formulated to minimize makespan and the operating costs of picking while maximizing the total scores of the selected pickers. The improved augmented epsilon constraint method (AUGMECON2) and the non-dominated sorting genetic algorithm II (NSGA-II) are applied to solve the proposed model. The performance of the two methods is tested on well-known benchmark instances and a real-world case study. The NSGA-II algorithm can generate optimal results using only about 6.58% of the CPU time required by AUGMECON2 to solve the problem. Our computational experiments show that increasing the number of pickers from 2 to 8 and doubling their capacity reduces the makespan by 2.61% and 2.74%, respectively.

关键词： Order picking system human factors multi-attribute decision-making multi-objective optimization problems non-dominated sorting genetic algorithm improved augmented epsilon constraint method

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Optimal allocation of regional water resources in an arid basin: insights from Integrated Water Resources Management

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AQUA-WATER INFRASTRUCTURE ECOSYSTEMS AND SOCIETY 2022年第8期71卷 910-925页

作者： Banadkooki, Fatemeh Barzegari Xiao, Yong Malekinezhad, Hossein Hosseini, Mohammad Mehdi Payam Noor Univ Fac Engn POB 4697-19395 Tehran Iran Southwest Jiaotong Univ Fac Geosci & Environm Engn Chengdu 611756 Peoples R China Yazd Univ Fac Nat Resources POB 741-89195 Yazd Iran Shahid Bahonar Univ Kerman Fac Math & Comp POB 76169-14111 Kerman Iran

Viewing water management as a multifaceted issue is critical to achieving sustainable water management. This paper proposes an integrated optimal allocation model for aquifer sustainability and environmental benefits when managing conjunctive water resources. Optimization techniques such as genetic algorithm (GA) and non-dominated sorting genetic algorithm (NSGA-II) are used to balance economic benefit and demand management based on decision makers' preferences. The findings indicate that less water was allocated to industries with high water demand. The value of the allocated water to these industries is between 34 and 52%. Thus, it concluded that specific industries are unsustainable when environmental damage is considered. From the scenarios examined, scenario 10 (water resource conditions and water demands are determined based on existing conditions, considering domestic water management and aquifer restoration) was found to be the optimal water management scenario. The indicators of Integrated Water Resources Management (IWRM) for this scenario are 0.30, 0.15, 190, 40.9, and 0.55 for relative water stress, aquifer sustainability, aquifer attenuation period, aquifer recovery potential, and agricultural water productivity, respectively. This finding implies that considering demand management, wastewater treatment, and the absence of industrial development in development scenarios, it will be possible to conserve aquifers and meet water demands.

关键词： environmental sustainability genetic algorithm Integrated Water Resources Management non-dominated sorting genetic algorithm optimization

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Multi-project Time-cost Optimization in Critical Chain with Resource Constraints

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KSCE JOURNAL OF CIVIL ENGINEERING 2018年第10期22卷 3738-3752页

作者： Amiri, Mohammad Javad Taheri Haghighi, FarshidReza Eshtehardian, Ehsan Abessi, Ozeair Babol Noshirvani Univ Technol Construct Engn & Management Babol Sar *** Iran Babol Noshirvani Univ Technol Dept Civil Engn Babol Sar *** Iran Tarbiat Modares Univ Dept Project Management Tehran 14115111 Iran

The simultaneous reduction of the project cost and time has paramount importance in today's competitive world;however, it is necessary to balance the project time and cost because of the reduction asymmetry of the two factors in a project. How to balance the cost and time parameters in managing construction projects is also critical and there have always been some attempts made to provide different approaches to control it. Given the immense importance of considering resource constraints for project scheduling problems, and the proximity of the study conditions to the real world, resource constraints were also included. In a project, project managers need to be aware of resource constraints. As resource constraint scheduling problem is considered NP-hard, the meta-heuristic models were developed in this paper in order to obtain results contributing to project managers' decision-making. For this purpose, a non-dominated sorting genetic algorithm method was developed to optimize a time-cost trade-off problem. Furthermore, to solve a multi-project scheduling problem, the critical chain method was used. In order to evaluate the performance of the model, the developed model was first studied in a small scale and then simultaneous projects with 7, 8 and 10 tasks were planned. Because resource availability is essential in such problems, after solving the proposed model, a sensitivity analysis was performed for daily resources and the results were discussed. Results shows the ability of the proposed model and methodology to optimize the time-cost tradeoff considering resource constraints in sample problems. Solutions obtained showed that in some cases of scheduling without this algorithm, resource consumption exceeded above resource availability. After solving the model by proposed algorithm, resource allocation is implemented considering resource constraint. This model determined these resources as crucial and helped managers to control them.

关键词： bi-objective time-cost optimization resource constraints non-dominated sorting genetic algorithm

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