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multi-criterion optimization of integrated photovoltaic facade with inter-building effects in diverse neighborhood densities

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JOURNAL OF CLEANER PRODUCTION 2020年 248卷 119269-000页

作者： Chen, Xi Huang, Junchao Yang, Hongxing Hong Kong Polytech Univ RERG Dept Bldg Serv Engn Kowloon Hong Kong Peoples R China Open Univ Hong Kong Sch Sci & Technol Kowloon Hong Kong Peoples R China

Inter-building effects have been proved to have significant impacts on the energy and indoor environmental performance of adjacent building developments in densified urban environment. Therefore, this study presents a multi-criterion design optimization and decision-making approach for an integrated PV facade design considering miscellaneous inter-building factors as well as corresponding criteria specification in major green building assessment schemes. The impact of the surface reflectance and facade geometry is quantified for the lighting energy demand, HVAC energy demand, photovoltaic (PV) energy supply and indoor visual discomfort time respectively with a robust global sensitivity approach in diverse urban density scenarios. Wall reflection is determined to be the most important urban design factor contributing to 34%-66% variation of different performance indicators as per the availability of solar radiation on different building surfaces. multi-dimension parametric analyses and design optimizations of PV envelope design parameters are then conducted for different neighborhood densities with fixed surface properties of peripheral building facades. Sensitivity indices of window and shading design parameters are subject to significant variation when considering surface properties of peripheral buildings. Furthermore, the performance of two different decision-making strategies (i.e. Technique for Order of Preference by Similarity to Ideal Solution and Minimum Distance to the Utopia Point methods) is compared based on criteria weightings from green building assessment schemes. The final optimum solution closest to the ideal is then determined by two-dimensional charts of objective functions. The integrated design optimization considering peripheral reflection can change the estimated net energy demand by up to 8.84% (mainly in PV supply and lighting demand). These research findings can promote the integration of synergetic energy and indoor environment design stra

关键词： Photovoltaic envelope Energy demand Visual discomfort multi-criterion optimization Decision-making

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multi-criterion optimization for genetic network modeling

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SIGNAL PROCESSING 2003年第4期83卷 763-775页

作者： van Someren, EP Wessels, LFA Backer, E Reinders, MJT Delft Univ Technol Fac Informat Technol & Syst Dept Mediamet Informat & Commun Theory Grp NL-2628 CD Delft Netherlands

A major problem associated with the reverse engineering of genetic networks from micro-array data is how to reliably find genetic interactions when faced with a relatively small number of arrays compared to the number of genes. To cope with this dimensionality problem, it is imperative to employ additional (biological) knowledge about real genetic networks, such as limited connectivity, redundancy, stability and robustness, to sensibly constrain the modeling process. In previous work (Proceedings of the 2001 IEEE-EURASIP Workshop on Nonlinear Signal and Image Processing, Baltimore, MA, June 2001;Proceedings of the Second International Conference on Systems Biology, Pasadena, CA, November 2, pp. 222230), we have shown that by applying single constraints, the inference of genetic interactions under realistic conditions can be significantly improved. Recently (Proceedings of the SPIE, San Jose, CA, January 2002), we have made a preliminary study on how these approaches based on single constraints solve the underlying bi-criterion optimization problem. In this paper, we study the problem of how multiple constraints can be combined by formulating genetic network modeling as a multi-criterion optimization problem. Results are shown on artificial as well as on a real data example. (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： multi-criterion optimization reverse engineering of genetic networks regression small sample size problem

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multi-criterion optimization of a Catalytic Reforming Reactor Unit Using a Genetic Algorithm

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CATALYSIS IN INDUSTRY 2020年第2期12卷 133-140页

作者： Zainullin, R. Z. Zagoruiko, A. N. Koledina, K. F. Gubaidullin, I. M. Faskhutdinova, R. I. Ufa State Petr Technol Univ Ufa 450062 Bashkortostan Russia Russian Acad Sci Boreskov Inst Catalysis Siberian Branch Novosibirsk 630090 Russia Russian Acad Sci Ufa Fed Res Ctr Inst Petrochem & Catalysis Ufa 450098 Bashkortostan Russia

multi-criterion optimization is achieved for the performance of a reactor unit used in reforming oil fractions on the basis of a mathematical model created earlier. The model considers changes in the temperature and molar flow rate of a reaction mixture during chemical reactions, the composition of refined feedstocks, and the quality and ratio of the circulation of hydrogen-rich gas. The criteria for multi-criterion optimization are the octane number, the yield of the target product (reformate), and the combined and individual contents of aromatic hydrocarbons and benzene. optimization is achieved by means of Pareto approximation using a genetic algorithm. The control parameters are the temperatures at the inlet to the reactors. Results from optimization show a reduction of 56 to 45 wt % in the total content of aromatic hydrocarbons, and the research octane number (RON) is lowered from 92.7 to 90.7. Three-objective optimization that ensures a 4 to 3.08 wt % reduction in the content of benzene and a 92.7 to 91.8 drop in the research octane number is also considered. The drop in the octane number is in both cases acceptable, considering the formulated requirements for the ultimate content of benzene and aromatic hydrocarbons in the reformate.

关键词： catalytic reforming reactor unit multi-criterion optimization genetic algorithm temperature regime ratio of catalyst distribution

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multi-criterion optimization of a pneumatic vibroinsulation system

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multiBODY SYSTEM DYNAMICS 2005年第1期13卷 39-52页

作者： Bestle, D Wachal, A Brandenburg Univ Technol Cottbus Chair Engn Mech & Vehicle Dynam D-03013 Cottbus Germany

Vibration insulation becomes more important as the importance of nanotechnology increases. Air springs have shown to offer a suitable technical solution with respect to vertical vibration, however, they show only low damping in horizontal direction. The paper introduces physical and mechanical models describing the dynamics of such air springs, where validation and identification is based on multiple types of excitation. Based on the derived model, design optimization is performed for additional air springs acting in horizontal direction. Three criteria are formulated describing both the insulation performance with respect to external excitation and disturbances by initial conditions. A multi-criterion optimization concept is used to account for these multiple design goals simultaneously.

关键词： multi-criterion optimization identification vibration insulation pneumatic insulator air spring

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multi-criterion optimization of a pneumatic vibroinsulation system

Multi-criterion optimization of a pneumatic vibroinsulation ...

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Euromech 442 Colloquium on optimization of Mechanical Systems

作者： Bestle, D Wachal, A Brandenburg Univ Technol Cottbus Chair Engn Mech & Vehicle Dynam D-03013 Cottbus Germany

关键词： multi-criterion optimization identification vibration insulation pneumatic insulator air spring

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Efficient deployment of UAVs for disaster management: A multi-criterion optimization approach

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COMPUTER COMMUNICATIONS 2021年 177卷 185-194页

作者： Masroor, Rooha Naeem, Muhammad Ejaz, Waleed COMSATS Univ Islamabad Dept Elect & Comp Engn Wah Campus Islamabad Pakistan Lakehead Univ Dept Elect Engn Barrie ON L4M 3X9 Canada

Recently different information and communication technologies are investigated to manage disasters. Acknowledging disaster resilience, many efforts are commenced to monitor, forecast, and assess the situation in time. Response time and situational awareness is the key to save lives in disaster situations. These issues motivate the utilization of unmanned aerial vehicles (UAVs) in emergency conditions where a lack of communication and support services are core objectives to control. This paper has addressed UAV-assisted wireless networks' situational awareness deployment in disaster management as a mobile helping unit. In this regard, we have to efficiently place UAVs in emergency situations where infrastructure is devastated and diffused with features of minimum distance, cost, and number of UAVs. To this end, we optimize a multi-objective problem of UAV placement, users-UAV connectivity, distance, and cost. The formulated problem is a integer linear optimization problem (ILP). To solve it, we first propose a high complexity branch and bound (B&B) algorithm to find an optimal solution. Then, we develop a low complexity heuristic to conquer the objectives efficiently. Finally, simulation results show that our proposed approach can maximize the number of users with a minimum number of UAVs efficiently.

关键词： UAVs Deployment multi-criterion optimization

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multi-objective grey wolf optimizer: A novel algorithm for multi-criterion optimization

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EXPERT SYSTEMS WITH APPLICATIONS 2016年 47卷 106-119页

作者： Mirjalili, Seyedali Saremi, Shahrzad Mirjalili, Seyed Mohammad Coelho, Leandro dos S. Griffith Univ Sch Informat & Commun Technol Nathan Campus Brisbane Qld 4111 Australia Griffith Coll Brisbane Qld 4122 Australia Pontifical Catholic Univ Parana PUCPR Ind & Syst Engn Grad Program PPGEPS Curitiba Parana Brazil

Due to the novelty of the Grey Wolf Optimizer (GWO), there is no study in the literature to design a multi objective version of this algorithm. This paper proposes a multi-Objective Grey Wolf Optimizer (MOGWO) in order to optimize problems with multiple objectives for the first time. A fixed-sized external archive is integrated to the GWO for saving and retrieving the Pareto optimal solutions. This archive is then employed to define the social hierarchy and simulate the hunting behavior of grey wolves in multi-objective search spaces. The proposed method is tested on 10 multi-objective benchmark problems and compared with two well-known meta-heuristics: multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) and multi-Objective Particle Swarm optimization (MOPSO). The qualitative and quantitative results show that the proposed algorithm is able to provide very competitive results and outperforms other algorithms. Note that the source codes of MOGWO are publicly available at http://***/***. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： multi-objective optimization Evolutionary algorithm multi-criterion optimization Heuristic algorithm Meta-heuristic Engineering optimization Grey wolf optimizer

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A multi-criterion optimization technique for energy efficient cluster formation in wireless sensor networks

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INFORMATION FUSION 2011年第3期12卷 202-212页

作者： Aslam, Nauman Phillips, William Robertson, William Sivakumar, Shyamala Dalhousie Univ Dept Engn Math & Internetworking Halifax NS B3J 2X4 Canada St Marys Univ Sobeys Sch Business Halifax NS B3H 3C3 Canada

Clustering techniques have emerged as a popular choice for achieving energy efficiency and scalable performance in large scale sensor networks. Cluster formation is a process whereby sensor nodes decide which cluster head they should associate with among multiple choices. Typically this cluster head selection decision involves a metric based on parameters including residual energy and distance to the cluster head. This decision is a critical embarkation point as a poor choice can lead to increased energy consumption, thus compromising network lifetime. In this paper we present a novel energy efficient cluster formation algorithm based on a multi-criterion optimization technique. Our technique is capable of using multiple individual metrics in the cluster head selection process as input while simultaneously optimizing on the energy efficiency of the individual sensor nodes as well as the overall system. The proposed technique is implemented as a distributed protocol in which each node makes its decision based on local information only. The feasibility of the proposed technique is demonstrated with simulation results. It is shown that the proposed technique outperforms all other well known protocols including LEACH, EECS and HEED resulting in a significant increase in network life. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Clustering Energy efficient multi-criterion optimization Wireless sensor networks

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Neural network based multi-criterion optimization image reconstruction technique for imaging two- and three-phase flow systems using electrical capacitance tomography

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MEASUREMENT SCIENCE AND TECHNOLOGY 2001年第12期12卷 2198-2210页

作者： Warsito, W Fan, LS Ohio State Univ Dept Chem Engn Koffolt Labs Columbus OH 43210 USA

In this work a new image reconstruction technique for imaging two- and three-phase flows using electrical capacitance tomography (ECT) has been developed. A brief review on reconstruction techniques developed recently for ECT is also given. The reconstruction technique proposed here is based on multi-criterion optimization using an analogue neural network. hereafter referred to as neural network multi-criteria optimization image reconstruction (NN-MOIRT). The reconstruction technique is a combination between a multi-criterion optimization image reconstruction technique for linear tomography, and the so-called linear back projection (LBP) technique commonly used for capacitance tomography. The multi-criterion optimization image reconstruction problem is solved using Hopfield model dynamic neural network Computing. For three-component imaging, the single-step sigmoid function in the Hopfield networks is replaced by a double-step sigmoid function. allowing the neural computation to converge to three distinct stable regions in the output space corresponding to the three components. enabling differentiation among the single phases. The technique has been tested on a capacitance data set obtained from simulated measurement as well as experiment using a 12-clectrode sensor. The performance of the technique has been compared with other commonly used iterative techniques, i.e. iterative linear back projection technique (ILBP) and the simultaneous image reconstruction technique (SIRT) for two-phase system imaging, and has shown great improvements in the accuracy and the consistency as compared with those techniques. The technique has also shown the capability of three-phase image reconstruction with high accuracy.

关键词： electrical capacitance tomography multiphase flow diagnostics image reconstruction neural network multi-criterion optimization

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multi-criterion optimization of a biologically-produced nanofluid flow inside tubes fitted with coaxial twisted tape based on first and second law viewpoints

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POWDER TECHNOLOGY 2022年 412卷

作者： Khanmohammadi, Shoaib Mazaheri, Nima Bahiraei, Mehdi Kermanshah Univ Technol Dept Mech Engn Kermanshah Iran Univ Calgary Schulich Sch Engn Dept Mech & Mfg Engn 2500 Univ Dr NW Calgary AB T2N 1N4 Canada Razi Univ Fac Engn Kermanshah Iran

The current study deals with a numerical simulation of heat transfer inside enhanced tubes having the coaxial double-twisted tape in the presence of an eco-friendly nanofluid containing graphene nanoplatelets (GNPs). The results unveil that when the particle concentration (cp) escalates, the thermal entropy generation rate ( Sh) tends to decline, whereas the heat transfer coefficient enhances. It was found that around 21.6% reduction in the Sh is attained by a decrease of the twisted ratio (w) from 3.5 to 2.5 at the concentration of 0.075% and Reynolds number of 10,000. Adding more GNPs to the water yields an increment in either the pressure drop or the frictional entropy generation. The findings refer to this issue that a multi-criterion optimization to find the best optimum state is required. A genetic algorithm-based optimization with the entropy generation rate, heat transfer, and pressure loss results in the optimum values at Re = 16,995.4, cp = 0.093%, and w = 3.41.

关键词： Entropy generation Coaxial twisted tape multi-criterion optimization Heat transfer Environmentally friendly nanofluid

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