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A comprehensive survey on enhancements and limitations of the RPL protocol: A focus on the objective function

AD HOC NETWORKS 2020年 96卷 102001-102001页

作者： Lamaazi, Hanane Benamar, Nabil Moulay Ismail Univ Fac Sci Meknes Morocco Moulay Ismail Univ Meknes Sch Technol Meknes Morocco

The RPL routing protocol for low power and lossy networks uses the objective function (OF) to build a Destination Oriented Directed Acyclic Graph (DODAG) based on a set of metrics and constraints. The OF has as the main function to select and specify the best parent or the optimal path to reach the destination. However, proposing an adequate objective function in Low Power and Lossy Networks (LLNs) presents a substantial challenge. In this paper, we propose a survey on existing objective functions in LLNs based on a set of metrics. These metrics can define a node or/and link characteristics. We highlight the advantages and the shortcoming of each studied solution. Furthermore, we propose a classification of the used metrics and the criteria of choice. Then, we present a comparative study of the existing OFs in terms of the required performances of the RPL protocol and we provide a deep statistical analysis of all reviewed papers. Finally, we conclude our contribution by highlighting the different issues and challenges that can be exploited for future works. We believe that this survey will help LLNs researchers' community to easily understand the objective function concept and contributes to improving RPL in this context for further relevant research works. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Internet of things RPL LLNs objective function

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Design of a two-output forward converter with an output voltage objective function

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2011年第12期39卷 1199-1213页

作者： Lo, Yu-Kang Chen, Jun-Ting Song, Tze-Herng Ou, Sheng-Yuan Natl Taiwan Univ Sci & Technol Dept Elect Engn Taipei Taiwan Natl Taipei Univ Technol Dept Elect Engn Taipei Taiwan

A new method is proposed in this paper to distribute the steady-state output voltage errors in a two-output forward converter. The cross regulation between the two output voltages are described in terms of the circuit parameters. An objective function is formed for each of the two outputs to track its reference within the specified error. The legitimate duty cycle range is located through the transfer characteristics between the duty cycle and the load currents. The weighting feedback gains of the two output voltages can be determined by the presented control scheme which optimizes the objective function. The proposed method is suitable for a two-output system without a dominant load. Experiments on a prototype are conducted to show that there exist a duty cycle range and a set of weighted feedback gains minimizing the defined objective function. Copyright (C) 2010 John Wiley & Sons, Ltd.

关键词： two-output forward converter cross regulation weighting feedback gains objective function

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Incorporating objective function Information Into the Feasibility Rule for Constrained Evolutionary Optimization

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IEEE TRANSACTIONS ON CYBERNETICS 2016年第12期46卷 2938-2952页

作者： Wang, Yong Wang, Bing-Chuan Li, Han-Xiong Yen, Gary G. Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China City Univ Hong Kong Dept Syst Engn & Engn Management Hong Kong Hong Kong Peoples R China Cent S Univ State Key Lab High Performance Complex Mfg Changsha 410083 Hunan Peoples R China Oklahoma State Univ Sch Elect & Comp Engn Stillwater OK 74078 USA

When solving constrained optimization problems by evolutionary algorithms, an important issue is how to balance constraints and objective function. This paper presents a new method to address the above issue. In our method, after generating an offspring for each parent in the population by making use of differential evolution (DE), the well-known feasibility rule is used to compare the offspring and its parent. Since the feasibility rule prefers constraints to objective function, the objective function information has been exploited as follows: if the offspring cannot survive into the next generation and if the objective function value of the offspring is better than that of the parent, then the offspring is stored into a predefined archive. Subsequently, the individuals in the archive are used to replace some individuals in the population according to a replacement mechanism. Moreover, a mutation strategy is proposed to help the population jump out of a local optimum in the infeasible region. Note that, in the replacement mechanism and the mutation strategy, the comparison of individuals is based on objective function. In addition, the information of objective function has also been utilized to generate offspring in DE. By the above processes, this paper achieves an effective balance between constraints and objective function in constrained evolutionary optimization. The performance of our method has been tested on two sets of benchmark test functions, namely, 24 test functions at IEEE CEC2006 and 18 test functions with 10-D and 30-D at IEEE CEC2010. The experimental results have demonstrated that our method shows better or at least competitive performance against other state-of-the-art methods. Furthermore, the advantage of our method increases with the increase of the number of decision variables.

关键词： Constrained optimization problems (COPs) constraints evolutionary algorithms (EAs) objective function

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A design and analysis of objective function-based unsupervised neural networks for fuzzy clustering

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NEURAL PROCESSING LETTERS 1996年第2期4卷 83-95页

作者： Rhee, HS Oh, KW SOGANG UNIV AI LABDEPT COMMUN SCISEOUL 121742SOUTH KOREA

Fuzzy clustering has played an important role in solving many problems. In this paper, we design an unsupervised neural network model based on a fuzzy objective function, called OFUNN. The learning rule for the OFUNN model is a result of the formal derivation by the gradient descent method of a fuzzy objective function. The performance of the cluster analysis algorithm is often evaluated by counting the number of crisp clustering errors. However, the number of clustering errors alone is not a reliable and consistent measure for the performance of clustering, especially in the case of input data with fuzzy boundaries. We introduce two measures to evaluate the performance of the fuzzy clustering algorithm. The clustering results on three data sets, Iris data and two artificial data sets, are analyzed using the proposed measures. They show that OFUNN is very competitive in terms of speed and accuracy compared to the fuzzy c-means algorithm.

关键词： cluster analysis fuzzy performance measure gradient descent method objective function unsupervised neural networks

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Nonlinear inverse optimization approach for determining the weights of objective function in standing reach tasks

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COMPUTERS & INDUSTRIAL ENGINEERING 2012年第4期63卷 791-801页

作者： Zou, Qiuling Zhang, Qinghong Yang, Jingzhou (James) Cloutier, Aimee Pena-Pitarch, Esteban Texas Tech Univ Dept Mech Engn Human Centr Design Res Lab Lubbock TX 79409 USA No Michigan Univ Marquette MI 49855 USA UPC Manresa 08240 Spain

This paper presents a nonlinear inverse optimization approach to determine the weights for the joint displacement function in standing reach tasks. This inverse optimization problem can be formulated as a bi-level highly nonlinear optimization problem. The design variables are the weights of a cost function. The cost function is the weighted summation of the differences between two sets of joint angles (predicted posture and the actual standing reach posture). Constraints include the normalized weights within limits and an inner optimization problem to solve for joint angles (predicted standing reach posture). The weight linear equality constraints, obtained through observations, are also implemented in the formulation to test the method. A 52 degree-of-freedom (DOF) human whole body model is used to study the formulation and visualize the prediction. An in-house motion capture system is used to obtain the actual standing reach posture. A total of 12 subjects (three subjects for each percentile in stature of 5th percentile female, 50th percentile female, 50th percentile male and 95th percentile male) are selected to run the experiment for 30 tasks. Among these subjects one is Turkish, two are Chinese, and the rest subjects are Americans. Three sets of weights for the general standing reach tasks are obtained for the three zones by averaging all weights in each zone for all subjects and all tasks. Based on the obtained sets of weights, the predicted standing reach postures found using the direct optimization-based approach have good correlation with the experimental results. Sensitivity of the formulation has also been investigated in this study. The presented formulation can be used to determine the weights of cost function within any multi-objective optimization (MOO) problems such as any types of posture prediction and motion prediction. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： objective function Multi-objective optimization Weights Inverse optimization Standing reach tasks

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Parameter Identification Method for Transient Impact Interference of Vortex Sensor Based on Optimal Estimation of objective function

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2022年 71卷 1-10页

作者： Shao, Chun-Li Yang, Shuang-Long Xu, Ke-Jun Zhu, Qian-Long Anhui Univ Sch Elect Engn & Automat Hefei 230601 Peoples R China Hefei Univ Technol Sch Elect & Automat Engn Hefei 230009 Peoples R China

The application occasion of vortex flowmeter is complex and changeable, and it is easily interfered by various transient impacts, which may cause the flowmeter to fail to measure correctly. In order to find a reliable solution, it is the key to find a method to identify the parameters of transient impact interference output by vortex sensor effectively. Based on the analysis of the vortex flowmeter piping system, a real number form of the composite Laplace wavelet with unilateral attenuation is used to describe each main mode of transient impact interference output by the vortex sensor. Considering that the transient impact interference has multi-modal characteristics, including dense modes, the objective function is constructed, a genetic algorithm combined with BFGS quasi-Newton method is used to search for the optimal estimation of the objective function, and a parameter identification method of the transient impact interference based on the optimal estimation of the objective function is proposed. The effectiveness and reliability of the parameter identification method for the transient impact interference output by vortex sensor are verified by simulation experiments and transient impact interference platform experiments.

关键词： Transient analysis Interference Flowmeters Vibrations Damping Time-frequency analysis Linear programming objective function optimal estimation parameter identification transient impact vortex flowmeter

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A New Method for Solving objective function of Hybrid Electric Propulsion System for Intelligent Design

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IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION 2024年第2期10卷 3043-3060页

作者： Yan, Zhi-Wei Wang, Biao Ju, Ting Chen, Wei Nanjing Univ Aeronaut & Astronaut Coll Energy & Power Engn Nanjing 210016 Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Peoples R China Chongqing Jiaotong Univ Inst Aeronaut Chongqing 400074 Peoples R China

Using hybrid electric propulsion system (HEPS) is one of the ways to reduce aircraft environmental pollution and help to bring the airlines into the all-electric era. However, the objective function of aircraft HEPS for intelligent search design is relatively simple at present. In this article, a new method for solving the objective function of HEPS intelligent design was proposed, which solves the problem of poor accuracy of power level modeling and improves the ability to explore global optimal results. This article took the fixed-wing unmanned aerial vehicle that mainly performs long-range flight tasks as an example. The load curve solving methods were compared, and the entire calculation structure was optimized for computational efficiency. Also, the results of more than 13% fuel saving rate with high fuel efficiency compared with pure fuel-powered flight were obtained. The combination of energy management strategy (EMS) participation in load curve solving and further dynamic programming (DP) optimization in objective function solving was proved to be optimal.

关键词： Autonomous aerial vehicles Atmospheric modeling Energy management Aircraft Mathematical models Linear programming Batteries Energy management strategy (EMS) hybrid electric propulsion system (HEPS) objective function

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A least third-order cumulants objective function

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NEURAL PROCESSING LETTERS 1996年第2期3卷 91-99页

作者： Leung, CT Chow, TWS Yam, YF CITY UNIV HONG KONG DEPT ELECT ENGNKOWLOONHONG KONG

A novel Least Cumulants Method is proposed to tackle the problem of fitting to underlying function in small data sets with high noise level because higher-order statistics provide an unique feature of suppressing Gaussian noise processes of unknown spectral characteristics. The current backpropagation algorithm is actually the Least Square Method based algorithm which does not perform very well in noisy data set. Instead, the proposed method is more robust to the noise because a complete new objective function based on higher-order statistics is introduced. The proposed objective function was validated by applying to predict benchmark sunspot data and excellent results are obtained. The proposed objective function enables the network to provide a very low training error and excellent generalization property. Our results indicate that the network trained by the proposed objective function can, at most, provide 73% reduction of normalized test error in the benchmark test.

关键词： Least Cumulants Method third-order cumulants objective function least cumulants based backpropagation

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Appropriate formulation of the objective function for the history matching of seismic attributes

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COMPUTERS & GEOSCIENCES 2013年 51卷 64-73页

作者： Tillier, E. Da Veiga, S. Derfoul, R. IFP Energies Nouvelles F-92852 Rueil Malmaison France

The purpose of history matching is to find one or several reservoir models which can reproduce as best as possible all the available data. The available data are traditionally some production data, but today seismic data are often integrated in the history matching process. The way of measuring the misfit between real data and simulated responses has a significant impact on the optimization process and hence on the final optimal model obtained. The classical formulation of the misfit is the least square one, which was used with success for production data. This formulation was naturally extended for seismic data. However, it yields an objective function term which is difficult to reduce. Indeed, seismic data are different from production data since they are defined by millions of points and are generally very noisy. When matching seismic data, the goal is then to capture the main features. As a result, computing a point to point error is not adapted and the resulting objective function is not representative of the quality expected for the match. We propose in this paper to define a more appropriate formulation. The idea is to use some image analysis tools to define a formulation focusing on the main features of seismic images. More precisely, it is based on image segmentation and on a modified Hausdorff metric. We illustrate the success of this formulation on a simple history matching case. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： objective function History matching Seismic attributes Local dissimilarity map

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Estimation of an optimal solution of a LP problem with unknown objective function - A stochastic approximation approach based on the simplex method

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MATHEMATICAL PROGRAMMING 2004年第3期101卷 463-478页

作者： Prieto-Rumeau, T Univ Nacl Educ Distancia Dept Econ Aplicada Cuantitat 2 Madrid Spain

We consider a linear programming problem with unknown objective function. Random observations related to the unknown objective function are sequentially available. We define a stochastic algorithm, based on the simplex method, that estimates an optimal solution of the linear programming problem. It is shown that this algorithm converges with probability one to the set of optimal solutions and that its failure probability is of order inversely proportional to the sample size. We also introduce stopping criteria for the algorithm. The asymptotic normality of some suitably defined residuals is also analyzed. The proposed estimation algorithm is motivated by the stochastic approximation algorithms but it introduces a generalization of these techniques when the linear programming problem has several optimal solutions. The proposed algorithm is also close to the stochastic quasi-gradient procedures, though their usual assumptions are weakened.

关键词： objective function Mathematical Method Approximation Algorithm Programming Problem Failure Probability

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