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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： Autuori, Julien Hnaien, Faicel Yalaoui, Farouk Hamzaoui, Abdelaziz Essounbouli, Najib Univ Technol Troyes ICD LOSI UMR STMR CNRS 6279 F-10004 Troyes France

ISBN: (纸本)9781467355476;9781467355490

""In this paper, we present a new metric to evaluate the meta-heuristics by studying their exploration of the solution space. We propose an efficient representation of the solution space by a one-dimensional map. To evaluate the exploration of space, relative and absolute metrics have been proposed. For the tests, we used the NSGA2 and SPEA2 on Flexible Job Shop Problem (FJSP) with the objectives to reduce the makespan (Cmax) and to produce the jobs just in time (¦²Ni=1 Zi, with Zi = Ti + Ei, T is the tardiness and E is the earliness). The results show that the NSGA2 explore more 6.78 % solutions on average than SPEA2.""

关键词： multi-objectives optimization Flexible Job Shop Problem Evolutionary algorithms Solution space

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multi-objective PI controller tuning using NSGA-II with preferability 40

Multi-objective PI controller tuning using NSGA-II with pref...

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40th Chinese Control Conference (CCC)

作者： Zhang, Tao Yin, Xiaokang Univ Sheffield Dept Automat Control & Syst Engn Sheffield S1 3JD S Yorkshire England

ISBN: (纸本)9789881563804

This paper introduces a modified nondominated sorting genetic algorithm-II (NSGA-II) to deal with nine objectives for a PI controller tuning problem. With the preferability operator which consists of goals and priorities, the optimal solutions are determined according to the setting preferability rather than conventional weak dominance. In addition, pre-clustering analysis is also utilized in the optimization process to reduce computational cost. The final results show that all objectives are satisfied with better performances comparing with the conventional NSGA-II, which proves the feasibility and effectiveness of this modified method.

关键词： multi-objectives optimization NSGA-II PI controller preferability

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A stochastic programming model to solve job-shop scheduling problem under uncertain information environment

A stochastic programming model to solve job-shop scheduling ...

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International Conference on Management Science and Engineering Management

作者： Zhu, Haiping Wu, Jun Wang, Zhonghao Huazhong Univ Sci & Technol Dept Ind & Mfg Syst Engn Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9781846260018

On the basis of describing the uncertain information existing in the actual job-shops with several stochastic variables, a stochastic multi-objectives and multi-priorities programming model for job-shop scheduling is built, in which time, cost and equilibrium serve as the three basic objectives for scheduling of production orders. The confidence level of the delivery time of different types of work pieces serve as the scheduling constraints. In order to obtain the approximate optimum solution, a hybrid intelligent algorithm which combines Stochastic Simulation, Neural Network with Genetic Algorithm is proposed, and the main solving steps are discussed. Finally, a case study is given to illustrate the feasibility of this model and the solving approach.

关键词： job-shop scheduling stochastic programming multi-objectives optimization

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Application of Spotted Hyena Optimizer in Cogeneration Power Plant on Single and multiple-Objective 11

Application of Spotted Hyena Optimizer in Cogeneration Power...

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IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Sukpancharoen, Somboon Rajamangala Univ Technol Thanyaburi Div Mechatron & Robot Engn Pathum Thani Thailand

ISBN: (数字)9781665414906

ISBN: (纸本)9781665414906

In this paper, a Spotted Hyena Optimizer (SHO) is employed in the context of addressing a constrained optimization problem to solve a cogeneration power plant (CGPP) problem through a classical approach. The paper examines the CGPP system through consideration of the 3E aspects (energy, exergy, and economy) through thermodynamic analysis. The equipment used in the system included a condenser, a turbo-generators, and a boiler. Two design optimization approaches were used: single objective optimization (SOO) and multi-objective optimization (MOO), with a comparison conducted using the SHO algorithm. On the basis of the findings, one optimal solution was returned by SOO-SHO from a single run, while a set of optimal solutions was discovered using MOO-SHO. The use of a SOO-SHO model requires the researcher to determine the preferred settings prior to starting the run, whereas the MOO-SHO does not require such decisions to be taken until after the run is complete. Typically, the SOO approach generates the optimal solution when considering a particular objective, while the MOO uses a broader array of information to reach richer solutions that consider the broader perspective.

关键词： Spotted Hyena Optimizer Cogeneration power plant Single objective optimization multi-objectives optimization Meta-heuristics

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Design optimization of Full Vehicle Suspension Based on Ride and Handling Performance

Design Optimization of Full Vehicle Suspension Based on Ride...

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The FISITA 2012 World Automotive Congress--Volume 7:Vehicle Design and Testing(Ⅰ)

作者： Tey Jing Yuen Ramli Rahizar Zainul Abidin Mohd Azman Alias Anuar Dzakaria Afandi Advanced Computational and Applied Mechanics (ACAM) Research Group Department of Mechanical EngineeringFaculty of Engineering Universiti MalayaKuala LumpurMalaysia Faculty of Mechanical Engineering Universiti Teknologi Malaysia Kuala LumpurMalaysia

In this paper,a new methodology is proposed to optimize a passive suspension system of a full vehicle system based on ride and *** passive suspension design,the conflicting design objectives are the ride comfort and handling *** ride comfort is defined as the level of comfort experienced by the passenger in a form of numerical values *** root mean square(RMS) of acceleration(ISO 2631).The acceleration is measured when the car travels on a Class C random road profile adopted from ISO8606:1995 ***,handling performance is defined by quality of handling,which relate to subjective feeling of human driver and also objective measurement of the vehicle *** steers maneuver(ISO7401) is employed to measure the required objectives defining handling performance,which included the RMS roll gain,phase angle of yaw rate at 0.2 and at 0.6 *** angle of lateral acceleration at 1 Hz and ratio of yaw rate gain at resonant frequency against the static yaw rate *** objectives will be minimized through multi-objective optimization methodology,which involves sampling technique,and regularity model based on multi-objective estimation of distribution algorithm(RM-MHDA) to solve more than 100 dimensional spaces of design *** methodology showed promising results in optimizing full vehicle suspension design compared to the conventional workflow of suspension tuning.

关键词： multi-objectives optimization Passive suspension Suspension tuning Suspension optimization

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Bridge Maintenance Planning Framework Using Machine Learning, multi-Criteria Decision Analysis and Evolutionary optimization Models (vol 141, 104460, 2022)

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AUTOMATION IN CONSTRUCTION 2022年 143卷

作者： Jaafaru, Hussaini Agbelie, Bismark Catholic Univ Amer Dept Civil Engn 620 Michigan Washington DC 20064 USA Catholic Univ Amer 620 Michigan Washington DC 20064 USA

Although various tools and procedures have been developed to help transportation engineers to objectively evaluate bridge maintenance needs, selecting and scoping projects still relies on engineering judgment. The present paper intends to help engineers evaluate and maintain bridges by developing a comprehensive bridge maintenance planning framework (BMPF) within financial and performance constraints. The aims of this study are to maximize the performance condition level of a bridge network and decrease maintenance costs by planning maintenance treatments appropriately. The framework includes bridge performance impact assessment, machine learning models, multi-criteria decision analysis model and genetic algorithm optimization model. The study analyzed 95 bridges in a network with an 84% accuracy machine learning model prediction. Decision-makers' preferences were considered to rank all bridges using multi-attribute utility Theory. 19 bridges were then chosen for maintenance based on budget and performance using a genetic algorithm model. The BMPF was observed to improve project productivity, reduce down time, and improve bridge inventory condition. Future research can explore the use of other optimization approaches and also include traffic flow and construction cost analysis for a better maintenance cost estimation. The machine learning model for performance prediction can be enhanced by utilizing different techniques.

关键词： Bridges Maintenance planning Machine learning multi-attribute criteria decision analysis multi-objectives optimization Genetic algorithms

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Optimized scheduling of integrated community energy stations based on improved NSGA-III algorithm

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JOURNAL OF ENERGY STORAGE 2024年 99卷

作者： Fang, Na Ma, Senyuan Liao, Xiang Ding, Huiqing Yu, Jiahao Hubei Univ Technol Hubei Key Lab High Efficiency Utilizat Solar Energ Wuhan 430068 Peoples R China Hubei Univ Technol Hubei Engn Res Ctr Safety Monitoring New Energy & Wuhan 430068 Peoples R China

To cope with the problem of building and using a large number of fast electric vehicle stations (FEVS), adding FEVS to the integrated community energy system (ICES) provides new ideas for solving the problems of interaction with the grid, overall system stability, revenue benefits, and environmental pollution. To this end, this paper designs an ICES model with FEVS (ICES-FEVS). This model considers economy, stability, and sustainability to achieve all-around consideration. To further solve the complex multi-objective problem, the multi-objective improvement strategy NSGA-III algorithm (IS-NSGA-III), combined with fuzzy comprehensive evaluation (FCE), is used to solve the model. In the solution phase, the advantages of the IS-NSGA-III algorithm are first verified by the benchmark function, and the validity of the ICES-FEVS model is verified by comparing different models. In the optimization results, daily revenue was increased by 6.3 %, daily battery life loss was increased by 26.03 %, and pollution emissions were reduced by 46.9 %. The analysis of the results shows that introducing Electric Vehicle (EV) fast charging stations in an integrated community energy system ensures economic improvement, sustainable development, and more favorable regulation of the energy storage system. The simulation results show that compared with other algorithms, the HV metrics of IS-NSGA-III are lower by about 6.8 %, Spread metrics are better by about 1.35 %, and the proposed IS-NSGA-III is better in terms of convergence and distributivity.

关键词： Integrated community energy system Electric vehicle charging stations multi-objectives optimization multi-objective improved strategies NSGA-III algorithm Electric vehicles

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A two-stage multi-objective second generation biodiesel supply chain design considering social sustainability: A case study

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ENERGY 2021年 233卷

作者： Mohtashami, Zahra Bozorgi-Amiri, Ali Tavakkoli-Moghaddam, Reza Univ Tehran Sch Ind Engn Coll Engn Tehran Iran

Undesirable environmental impacts caused by fossil fuel consumption have motivated governments to focus on biofuels production. Therefore, in our paper, we design a multi-objective biodiesel supply chain from Jatropha, which includes biomass cultivation center, pretreatment, and oil extraction center, biorefinery, and demand zone. In our study, a two-stage approach presented, which first specifies candidate locations for biomass cultivation with a common weight data envelopment analysis (CWDEA) method and then strategic and tactical decisions were made by a mathematical model. The presented multi objective model focuses on cost minimization, besides social benefits and environmental impacts maximization while a life cycle assessment approach is used to model social indicators. The capability of the model is validated by proposing a case study of Iran and the augmented epsilon-constraint method is employed to reach a trade-off between three pillars of sustainability while managerial insights are provided by employing a Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method for the optimal solution selection. Model's results and sensitivity analysis on key parameters, specify the best locations for Jatropha Curcas L. (JCL) cultivation and facility construction as well as an optimal value of supply chain variables, which finally proves that Iran has a high potential for biodiesel production from JCL that leads improving balanced socio-economic development in this country. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Biodiesel supply chain design Jatropha multi-objectives optimization CWDEA TOPSIS Social responsibility

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Non-cooperative stability assessments of groundwater resources management based on the tradeoff between the economy and the environment

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JOURNAL OF HYDROLOGY 2019年 578卷

作者： Nazari, Sara Ahmadi, Azadeh Isfahan Univ Technol Dept Civil Engn Esfahan *** Iran

Groundwater resource exploitations, as one of the most valuable water resources, cause conflicts among beneficiaries due to different priorities in decision-making processes. These conflicts lead beneficiaries to decide non-cooperatively. Consequently, it is essential to consider non-cooperative decision-making in order to manage groundwater resources properly. In this study, non-cooperative game theory was applied to groundwater resource management. This methodology was employed in Bad-Khaledabad study area located in the center of Iran. Also, quantity and quality simulation and optimization models were used to calculate the payoffs of beneficiaries including farmers and government. In order to understand beneficiaries' non-cooperative decision-making, three games were examined called cropping pattern shift, efficiency improvement, and linked game. The stable solution obtained for the linked game was the scenario where farmers choose to change their cropping patterns which will increase the farmers' profit by up to US$3,280,000, and government limits groundwater withdrawals to 66.5 MCM and pays for efficiency improvements which will raise the groundwater table 2m at the end of the fifth year.

关键词： Groundwater management Non-cooperative game theory MODFLOW MT3DMS multi-objectives optimization

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Concurrent Association in Heterogeneous Networks with Underlay D2D Communication 13

Concurrent Association in Heterogeneous Networks with Underl...

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13th International Wireless Communications and Mobile Computing Conference (IWCMC)

作者： Abdellatif, Alaa Awad Mohamed, Amr Chiasserini, Carla-Fabiana Qatar Univ Dept Comp Sci & Engn Doha Qatar Politecn Torino Dept Elect & Telecommun Turin Italy

ISBN: (纸本)9781509043729

Deployment of Device-to-Device (D2D) communication within dense heterogeneous networks is a key solution in order to face the intense demand for high data rates and quality of the service in future 5G networks. However, this imposes challenges to develop innovative network selection mechanisms that account for both energy efficiency and user experience. In this paper, we propose a network association framework for heterogeneous systems where uplink data transfers can leverage direct device-to-infrastructure (D2I) links as well as underlay D2D connections. The proposed methodology is based on a distributed approach that optimizes the users' objectives, while accounting for the interference that underlaying D2D communication may cause, in order to enhance system performance and support reliable connectivity. Furthermore, to fully exploit the potential of D2D communication and prevent selfish behavior, a dynamic pricing strategy maximizing the profits of both source and relay nodes is proposed. Our results show that the proposed scheme provides significant performance gains and high efficiency compared to the centralized approach.

关键词： Heterogeneous wireless environment network association energy efficiency device-to-device communications multi-objectives optimization

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