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Evolutionary Algorithmic Deployment of Radio Beacons for Indoor Positioning

Evolutionary Algorithmic Deployment of Radio Beacons for Ind...

IEEE Congress on Evolutionary Computation (CEC) held as part of IEEE World Congress on Computational Intelligence (IEEE WCCI)

作者： Ye, Sipan Chen, Yuanzhu Hu, Ting Mem Univ Newfoundland Dept Comp Sci St John NF A1B 3X5 Canada

ISBN: (纸本)9781509006229

In mobile computing, the location awareness of a mobile device and its user enables numerous personalized and social services such as recommendation of products and sharing current locations on social networks. Extending positioning services to indoor environments augments the value of the mobile communication market vastly. Due to serious signal attenuation, navigation satellites are incapable, and a common approach is to use or deploy small-scale radio frequency transmitters. When deploying these radio beacons, it is crucial to use a small number of them to provide high-quality positioning services. Such a deployment task is a challenging optimization problem, and the system administrators would benefit from having a spectrum of solutions with varying balance between cost and quality. In this study, we propose an Evolutionary Algorithm (EA) to tackle the problem. Using a cost-quality adjustment parameter, our EA framework is able to provide a set of solution options to meet varying requirements balancing cost and quality. This property is a result of the parallel population-based search of EAs, and can be very useful in real-world engineering applications.

关键词： Mobile computing Evolutionary computation Location-aware service Indoor positioning Radio beacons Genetic algorithm multiple-objective optimization

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Task Value Calculus: Multi-objective Trade off Analysis using multiple-Valued Decision Diagrams 49

Task Value Calculus: Multi-objective Trade off Analysis usin...

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49th IEEE International Symposium on multiple-Valued Logic (ISMVL)

作者： Giallanza, Tyler Gabrielsen, Erik Taylor, Michael A. Larson, Eric C. Thornton, Mitchell A. Southern Methodist Univ Darwin Deason Inst Cybersecur Dallas TX 75275 USA

ISBN: (纸本)9781728100920

Most multiple-objective optimization algorithms utilize continuous input variables. Given that many decision variables in common use-cases are discrete rather than continuous, we develop a multiple-objective optimization framework over discrete variables known as task value calculus (TVC). The underlying mathematical models in TVC utilize a multiple valued algebraic framework where both the objective functions and the system or process structure models are represented as multiple-valued functions. TVC allows for fast multiple-objective optimization through the use of the multiple-valued decision diagram (MDD) data structure. The algorithms and structures internal to TVC are described and experimental results are provided. TVC is implemented with a simple graphical user interface making it suitable for use by both laypersons and domain experts.

关键词： multiple-valued logic multiple-objective optimization multiple-valued decision diagram

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Mergers and Acquisitions: An Efficiency Evaluation

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Applied Mathematics 2013年第11期4卷 1583-1589页

作者： Paulo Rotela Junior Edson de Oliveira Pamplona Aneirson Francisco da Silva Institute of Production Engineering and Management Federal University of ItajubaItajubaBrazil Departament of Production Sao Paulo State UniversityGuaratinguetaBrazil

This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing efficiency and obtaining business synergy. Prior literature suggests that synergies could arise due to taxes, market power or efficiency improvements. This study evaluates the efficiency of M&A in Brazil among publicly-traded companies. We used models with multiple objectives from Goal Programming and Data Envelopment Analysis (GPDEA), employing accounting indicators as input and output variables, and thus evaluated the emergence of synergy gains. These models allow us to analyze and classify the M&A according to the efficiency obtained in such processes. Some of the M&A cases analyzed were mistakenly considered efficient when used traditional models. And, as expected, the GPDEA was proved to be superior to classical models;however it was noticed that few of the cases investigated were proved to be effective. We presented a new application for multi-objective approach that can be used to assess mergers and acquisitions. The dualapplication of GPDEA provided a greater understanding of efficiency generation in synergy creation by means of M&A.

关键词： Merger and Acquisition multiple-objective optimization Goal Programming Data Envelopment Analysis Synergy

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An Optimal ZigBee Wireless Sensor Network Design for Energy Storage System 29

An Optimal ZigBee Wireless Sensor Network Design for Energy ...

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IEEE 29th International Symposium on Industrial Electronics (ISIE)

作者： Liu, Yucheng Wei, Yang Wang, Hao Tsang, Kim Fung Zhu, Hongxu Chow, Yuk Tak City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

ISBN: (纸本)9781728156354

Energy Storage System (ESS) has become a vital development for smart buildings and smart grids. Centralized intelligent ESS controller requires intelligent sensing with accurate real-time sensing data, which demands high latency and packet abnormal rate (PAR) performance of the communications between sensors and the control centralizer. Large scale indoor public spaces (IPS), generally characterized by large volumes, require robust connections among deployed sensors for ESS management. Wireless sensor network (WSN) has been proven to be one of the best candidates for data transmission in large scale ESS systems. ZigBee, attributed to its excellent performance on scalability, low power consumption and relatively sufficient data rate, is a crucial wireless protocol for WSNs in building applications. In this paper, a ZigBee based optimal WSN for ESS is proposed. The design considers multiple parameters for ESS which includes power efficiency, throughput, and robustness (i.e. packet loss, packet error). The parameters are optimized by designing a multi-objective optimization formulation on ESS. The optimization achieves a low latency and a low packet abnormal rate (PAR) and yet provides a real-time accurate data transmission. Experimental results reveal that the proposed system achieves a low PAR of 0.08%. The optimal design provides generic guidance for large scale WSNs design for ESS using ZigBee.

关键词： Large-scale Energy Storage System multiple-objective optimization Wireless Sensor Networks

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multiple-objective Power Control Algorithm Based on Successive Interference Cancellation Algorithm 11

Multiple-Objective Power Control Algorithm Based on Successi...

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11th IEEE International Conference on Software Engineering and Service Science (IEEE ICSESS)

作者： Jin, Jian Wang, Aiping Univ Anhui Dept Comp Sci & Technol Hefei Anhui Peoples R China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165790

Successive Interference Cancellation(SIC) is a multiuser detection algorithm, which can effectively combat multiple access interference in wireless networks. In wireless network system, the network throughput can be improved by using serial interference elimination algorithm and the transmitting power of control nodes. However, in practical applications, pursuing network throughput should also consider saving system energy consumption. In response to this situation, a multiple-objective power control model based on a successive interference cancellation is established with two optimization objectives, minimize the total system transmit power and maximize the average network throughput of the system nodes. An improved NSGA-II algorithm is used to optimize the model globally. A clustering distance-based elimination strategy is designed to maintain the population distribution. The effects of the improved NSGA-II algorithm on the problem are analyzed through simulation experiments. The results of 20 groups of contrastive experiments show that the Pareto solution obtained by the proposed algorithm is superior to the PESA-II algorithm and the MOPSO algorithm.

关键词： Wireless Network Power Control Successive Interference Cancellation multiple-objective optimization

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Generalized Convexity and Characterization of (Weak) Pareto-Optimality in Nonsmooth Multiobjective optimization Problems

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INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2015年第4期14卷 877-899页

作者： Soleimani-Damaneh, Majid Univ Tehran Coll Sci Sch Math Stat & Comp Sci Tehran Iran

Efforts to characterize optimality in nonsmooth and/or nonconvex optimization problems have made rapid progress in the past four decades. Nonsmooth analysis, which refers to differential analysis in the absence of differentiability, has grown rapidly in recent years, and plays a vital role in functional analysis, information technology, optimization, mechanics, differential equations, decision making, etc. Furthermore, convexity has been increasingly important nowadays in the study of many pure and applied mathematical problems. In this paper, some new connections between three major fields, nonsmooth analysis, convex analysis, and optimization, are provided that will help to make these fields accessible to a wider audience. In this paper, at first, we address some newly reported and interesting applications of multiobjective optimization in Management Science and Biology. Afterwards, some sufficient conditions for characterizing the feasible and improving directions of nonsmooth multiobjective optimization problems are given, and using these results a necessary optimality condition is proved. The sufficient optimality conditions are given utilizing a generalized convexity notion. Establishing necessary and sufficient optimality conditions for nonsmooth fractional programming problems is the next aim of the paper. We follow the paper by studying (strictly) prequasiinvexity and pseudoinvexity. Finally, some connections between these notions as well as some applications of these concepts in optimization are given.

关键词： (Weak) Pareto-optimality multiple-objective optimization decision making invexity functional analysis Clarke's gradient

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Comparative study of hybrid architectures integrated with dual-fuel intelligent charge compression ignition engine: A commercial powertrain solution towards carbon neutrality

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ENERGY CONVERSION AND MANAGEMENT 2023年第1期292卷

作者： Zhang, Yaoyuan Wu, Haoqing Mi, Shijie Zhao, Wenbin He, Zhuoyao Qian, Yong Lu, Xingcai Shanghai Jiao Tong Univ Key Lab Power Machinery & Engn MOE Shanghai 200240 Peoples R China

The dual-fuel intelligent charge compression ignition (ICCI) engine, equipped with double direct injection systems, can simultaneously improve fuel consumption and gaseous emissions by substituting low-carbon fuels for conventional fuels. This work investigates the optimal application of the ICCI engine on hybrid powertrains under various standard driving conditions. The purpose is to evaluate the profit of combining the advantages of hybrid powertrains with the advanced engine. Dynamic programming (DP) is applied to the energy management control, realizing the global optimization in the design phase. Three typical hybrid configurations are compared, including series (SHEV), parallel (PHEV), and power-split (PSHEV) hybrid electric vehicles. Except for the charging sustaining stage, the optimal state of charge trajectories are also researched to verify the reasonable parameters in the charging stage. Considering multiple objectives, a non-dominated sorting genetic algorithm (NSGA-II) is coupled to optimize fuel consumption, gaseous emissions, and battery cost. The ICCI engine is mapped by the test bench results, while the involved hybrid configurations are modeled in Matlab/Simulink. The results illustrate that PSHEV achieves the best fuel economy and emission purification among the involved structures. With the ideal solution provided by DP, fuel consumption and gaseous emissions for PSHEV are reduced by 10% and 50%, and the low-carbon fuel utilization ratio has tripled, contributing to carbon neutrality. The engine was operated in several working conditions for SHEV, achieving the cleanest gaseous emissions. For PHEV, the engine performance was rarely improved compared with the engine without the assistance of hybrid systems. The optimization provided by NSGA-II indicates that the minimum values of multiple objectives cannot be reached simultaneously. A further 50% reduction in emissions would cause fuel consumption to double the original.

关键词： Low-temperature combustion engine Hybrid electric vehicle Dynamic programming multiple-objective optimization

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Rigid-Elastic Combined Metamaterial Beam With Tunable Band Gaps for Broadband Vibration Suppression

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JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME 2024年第2期146卷 021004-021004页

作者： Zhang, Jiazhen Peng, Xuzhang Yu, Dewen Hu, Guobiao Yang, Yaowen Nanyang Technol Univ Sch Civil & Environm Engn Nanyang Ave Singapore 639798 Singapore Hong Kong Univ Sci & Technol Guangzhou Internet Things Thrust Guangzhou 511400 Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Key Lab Educ Minist Modern Design & Rotor Bearing Xian 710049 Peoples R China

Extensive research efforts have been dedicated to exploring the application of metamaterial beams for vibration suppression. However, most existing designs primarily focused on utilizing the translational motion of local resonators to create band gaps. To address this limitation of employing solo motion to induce a relatively narrow band gap, this study proposes a novel design: a rigid-elastic combined metamaterial beam utilizing both translational and rotational motions of local resonators. Theoretical framework development involves extending the transfer matrix method to incorporate rigid bodies, with analytical results validated through finite element simulations and experimental data. Compared to conventional metamaterial beams, the proposed design exhibits an additional wide band gap in the low-frequency region that can be utilized for broadband vibration suppression. A parametric study elucidates the influences of geometric parameters on band gap formation, followed by an exploration of the tunability of the proposed meta-beam through a graded scheme and optimization strategy. In particular, a multiple-objective optimization approach is employed to enlarge the vibration suppression region and enhance vibration suppression ability. The optimized meta-beam demonstrates a remarkable 45% wider dominant suppression region and a 14% lower average transmittance compared to a uniform model.

关键词： metamaterial tunable band gap multiple-objective optimization vibration suppression structural dynamics and control vibration control vibration isolation

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Optimizing spatial layout of afforestation to realize the maximum benefit of water resources in arid regions: A case study of Alxa, China

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JOURNAL OF CLEANER PRODUCTION 2021年 320卷 128827-128827页

作者： Zhang, Xiaoyu Xu, Duanyang Wang, Ziyu Chinese Acad Sci Inst Geog Sci & Nat Resources Res Key Lab Land Surface Pattern & Simulat Beijing 100101 Peoples R China Beijing Normal Univ Fac Geog Sci Beijing 100088 Peoples R China Beijing Forestry Univ Coll Forestry Beijing 100083 Peoples R China

Water shortage, ecological protection, and economic development are long-standing challenges faced by arid regions. Scientific afforestation project provides an effective way to realize the maximum benefit of water resources in the perspective of ecology and economy "win-win". However, how to plan and shape afforestation to meet different objectives and overcome different obstacles is an essential problem in policy-making. In this study, a method of optimizing the spatial layout of afforestation by considering ecological and economic goals, priority areas, and water resources capacity is developed. A case study of spatial layout planning of afforestation (represented by H. ammodendron) in Alxa, China is proposed. Results show that the scale of afforestation in Alxa would increase from 2019 to 2030 by considering the maximum benefit of water resources in ecology and economy. The priority areas for afforestation are mainly located in the west side of Helan Mountain, the east and south sides of the Badain Jaran Desert, and the central part of Ejin Banner. The spatial heterogeneity of precipitation makes the afforestation density increase from northwest to southeast, and the density would be changed under different climate scenarios. The method and results of this study provide a practical reference for optimizing afforestation and water resources allocation to achieve win-win pattern for ecology and economy in arid regions.

关键词： Ecological restoration Water balance multiple-objective optimization Spatial planning Arid region

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A review on inverse analysis models in steel material design

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Materials Genome Engineering Advances 2024年第4期2卷 26-33页

作者： Yoshitaka Adachi Ta-Te Chen Fei Sun Daichi Maruyama Kengo Sawai Yoshihito Fukatsu Zhi-Lei Wang Nagoya University NagoyaJapanBeijingChina 2JFE Steel CorporationChibaJapanBeijingChina 3University of Science and Technology BeijingBeijingChina

This paper reviews various inverse analysis models used in steel material design,with a focus on integrating process,microstructure,and properties through advanced machine learning *** study underscores the importance of establishing comprehensive models that effectively link these elements for enhanced materials *** models discussed include the convolutional neural network–artificial neural network-coupled model,which employs convolutional neural networks for feature extraction;the Bayesian-optimized generative adversarial network–conditional generative adversarial network model,which generates diverse virtual microstructures;the multi-objective optimization model,which concentrates on process–property relationships;and the microstructure–process parallelization model,which correlates microstructural features with process *** model is assessed for its strengths and limitations,influencing its practical applicability in material *** paper concludes by advocating for continued improvements in model accuracy and versatility,with the ultimate goal of enhancing steel properties and expanding the scope of data-driven material development.

关键词： GAN image regression inverse analysis multiple-objective optimization steel

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