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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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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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Hybrid NSGA-II for an imperfect production system considering product quality and returns under two warranty policies

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APPLIED SOFT COMPUTING 2019年 75卷 333-348页

作者： Taleizadeh, Ata Allah Khaligh, Pooya Pourrezaie Moon, Ilkyeong Univ Tehran Sch Ind Engn Coll Engn Tehran Iran Seoul Natl Univ Dept Ind Engn Seoul 08826 South Korea

This study presents a new bi-objective mathematical model for an imperfect production system (IPS) that accounts for product returns and quality levels under two different warranty policies. We considered uncertain customer demand as stochastic behavior and product price as a function of return compensation, product quality level, and warranty-period length. We simultaneously looked at the pro rata warranty and free replacement/repair warranty policies and assumed that customers can choose the desired policy. A return policy for an online distributor was also included and two objective functions were used to address the problem. The first objective function maximized the total expected revenue, and the second objective function maximized customer satisfaction. The non-dominated sorting genetic algorithm (NSGA-II) and two others, the basic bee metaheuristic and teaching-learning-based optimization algorithms, were used to generate the initial solution for use in the NSGA-II algorithm. The results from the hybrid algorithms revealed that the proposed method improves the performance of the NSGA-II algorithm. Finally, several specific sensitivity analyses were conducted to determine the effects of the problem parameters. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Metaheuristics non-dominated sorting genetic algorithm Product quality Warranty

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Optimum design of steel frame structures considering construction cost and seismic damage

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SMART STRUCTURES AND SYSTEMS 2015年第1期16卷 1-26页

作者： Kaveh, A. Fahimi-Farzam, M. Kalateh-Ahani, M. Iran Univ Sci & Technol Ctr Excellence Fundamental Studies Struct Engn Tehran 16844 Iran

Minimizing construction cost and reducing seismic damage are two conflicting objectives in the design of any new structure. In the present work, we try to develop a framework in order to solve the optimum performance-based design problem considering the construction cost and the seismic damage of steel moment-frame structures. The Park-Ang damage index is selected as the seismic damage measure because it is one of the most realistic measures of structural damage. The non-dominated sorting genetic algorithm (NSGA-II) is employed as the optimization algorithm to search the Pareto optimal solutions. To improve the time efficiency of the proposed framework, three simplifying strategies are adopted: first, simplified nonlinear modeling investigating minimum level of structural modeling sophistication;second, fitness approximation decreasing the number of fitness function evaluations;third, wavelet decomposition of earthquake record decreasing the number of acceleration points involved in time-history loading. The constraints of the optimization problem are considered in accordance with Federal Emergency Management Agency's (FEMA) recommended seismic design specifications. The results from numerical application of the proposed framework demonstrate the efficiency of the framework in solving the present multi-objective optimization problem.

关键词： performance-based design steel moment-frame structures Park-Ang damage index non-dominated sorting genetic algorithm simplified nonlinear modeling fitness approximation wavelet analysis

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Performance-cost optimization of tuned mass damper under low-moderate seismic actions

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STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS 2016年第18期25卷 1103-1122页

作者： Greco, Rita Marano, Giuseppe Carlo Fiore, Alessandra Tech Univ Bari DICATECH Dept Civil Engn Environm Terr Bldg & Chem Via Orabona 4 I-70125 Bari Italy Tech Univ Bari Dept Civil Engn & Architecture DICAR Via Orabona 4 I-70125 Bari Italy Fuzhou Univ Coll Civil Engn SIBERC 2 Xue Yuan Rd Fuzhou Fujian Peoples R China

In this paper, a multi-objective optimization of a single tuned mass damper is proposed at the aim to control vibrations induced in building structures under low-moderate earthquakes. The optimum design is carried out by considering both economic and performance criteria. The cost of the device is the economic objective that is assumed directly related to its mechanical parameters. At the aim to control the damage level and the behaviour of components and equipment, the ratio between the absolute accelerations of the protected structure and the unprotected one is assumed as the device performance. A multi-objective optimization is then formulated, and Pareto optimum solutions are achieved by the non-dominated sorting genetic algorithm in its second version. Finally, a sensitivity analysis of the optimum solution with respect to some input data is carried out. Copyright (c) 2016 John Wiley & Sons, Ltd.

关键词： tuned mass damper random vibrations cost of protection system multi-objective optimization non-dominated sorting genetic algorithm

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Multi objective optimization of rotorcraft compact spinning system using fuzzy-genetic model

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JOURNAL OF THE TEXTILE INSTITUTE 2017年第12期108卷 2166-2172页

作者： Vadood, Morteza Barzoki, Parvaneh Kheirkhah Johari, Majid Safar Yazd Univ Dept Text Engn Yazd Iran Amirkabir Univ Technol Dept Text Engn Tehran Iran

In this paper, the mechanical and physical properties of rotorcraft compact spinning yarns were evaluated. For this aim, the filament pre-tension, yarn count and type of sheath fibers were selected as the controllable factors, and the effect of them on the elongation and hairiness was investigated statistically and the obtained results indicated that controllable factors have significant effect on the measured properties. In the next step, the relation between factors and measured properties was modeled by fuzzy interface system and genetic algorithm was used to optimize the number of membership function and its kind. It was observed that the accuracy of obtained models for both elongation and hairiness is acceptable (correlation coefficient for both models was: 0.99). Finally, to find a set of controllable factors to produce a yarn with high elongation and low hairiness, multi objective optimization was applied by means of non-dominated sorting genetic algorithm and a set of trade off solutions obtained so that each solution can be accepted as a response.

关键词： Multi objective optimization rotorcraft compact spinning fuzzy interface system genetic algorithm non-dominated sorting genetic algorithm

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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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Multi-objective optimisation of a 2D backward-sfacing step channel with porous baffles

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JOURNAL OF THERMAL ANALYSIS AND CALORIMETRY 2024年第10期149卷 4755-4770页

作者： Costa, Sergio Cavaleiro Janeiro, Fernando M. Malico, Isabel Univ Evora IDMEC Escola Ciencias & Tecnol R Romao Ramalho 59 P-7000671 Evora Portugal Univ Evora Escola Ciencias & Tecnol R Romao Ramalho 59 P-7000671 Evora Portugal Inst Super Tecn Inst Telecomunicacoes Ave Rovisco Pais P-1049001 Lisbon Portugal

Porous baffles can be used to enhance heat transfer in various engineering applications, including electronic cooling, gas turbine blades, and chemical reactors. Also, the backward-facing step is a widely used configuration in fluid dynamics studies due to its simplicity and relevance to real-world geometries. This study examines heat transfer and flow characteristics in a backward-facing step channel featuring a heated bottom wall and two porous baffles. A computational fluid dynamics model, validated against prior research, is used to investigate flow and temperature fields. The innovation of this work lies in the application of multi-objective optimisation to search for a set of solutions that establish a trade-off between the average Nusselt number and the pressure drop. The optimisation specifically considers various parameters of the porous baffles, including height, width, distance from the step, and Darcy number, to identify optimal design configurations. Results show that porous baffles significantly improve heat transfer compared to a backward-facing step channel without them, despite an increase in pressure drop due to their presence. This work offers valuable insights into the trade-off between heat transfer performance and pressure drop, crucial for designing efficient heat transfer systems. By exploring the Pareto-Frontier, which represents various optimal design solutions, the study provides practical guidance when seeking to optimise heat transfer in backward-facing step channels with porous baffles. The findings contribute to advancing the understanding of heat transfer enhancement, highlighting the potential of porous baffles as a viable solution for improving thermal management in engineering systems.

关键词： Computational fluid dynamics Backward-facing step Multi-objective optimisation Porous media non-dominated sorting genetic algorithm

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Integrative numerical modeling and thermodynamic optimal design of counter-flow plate-fin heat exchanger applying neural networks

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INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER 2020年 159卷 120097-120097页

作者： Richter do Nascimento, Carlos Augusto Mariani, Viviana Cocco Coelho, Leandro dos Santos Pontificia Univ Catolica Parana Dept Mech Engn Curitiba Parana Brazil Univ Fed Parana Dept Elect Engn Curitiba Parana Brazil Pontificia Univ Catolica Parana Ind & Syst Engn Grad Program Curitiba Parana Brazil

In this study, an optimization technique combined with a Random Vector Functional Link (RVFL) network in the form of a surrogate-assisted approach was carried out for the optimal design of counter-flow plate-fin compact heat exchanger (PFHE) with offset-strip fins considering different mass flow rates. Computational Fluid Dynamics (CFD) simulations generated dataset for training and testing by RVFL network, reducing processing time and assuring PFHE accuracy when applied in many-objective optimization based on non-dominated sorting genetic algorithm III (NSGA-III). Next, the NSGA-III was designed to achieve the maximum effectiveness, minimum volume, and pressure drop at the hot and cold sides in PFHE design. For experimental validation the Shear Stress Transport (SST) k-omega turbulence model was used to simulate the flow and heat transfer in PFHE showing 4.36% and 3.27% of error, respectively, to pressure drop and convective heat transfer coefficient measurements. The optimized results by NSGA-III indicated that the volume and effectiveness values are in agreement with the literature, decreasing approximately 55.4% and 72.3% of pressure drop at the hot and cold sides, respectively, which showed that the convective heat transfer was enhanced and the flow resistance was also significantly reduced. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Plate-fin heat exchanger Offset-strip fin Many-objective optimization non-dominated sorting genetic algorithm Random vector functional link network Effectiveness

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