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On the task assignment with group fairness for spatial crowdsourcing

INFORMATION PROCESSING & MANAGEMENT 2023年第2期60卷

作者： Wu, Benwei Han, Kai Zhang, Enpei Univ Sci & Technol China Sch Comp Sci & Technol HuangShan Rd 443 Hefei 230022 Peoples R China Soochow Univ Sch Comp Sci & Technol Shizi Rd 1 Suzhou 215000 Peoples R China

Task assignment, the core problem of Spatial Crowdsourcing (SC), is often modeled as an optimization problem with multiple constraints, and the quality and efficiency of its solution determines how well the SC system works. Fairness is a critical aspect of task assignment that affects worker participation and satisfaction. Although the existing studies on SC have noticed the fairness problem, they mainly focus on fairness at the individual level rather than at the group level. However, differences among groups in certain attributes (e.g. race, gender, age) can easily lead to discrimination in task assignment, which triggers ethical issues and even deteriorates the quality of the SC system. Therefore, we study the problem of task assignment with group fairness for SC. According to the principle of fair budget allocation, we define a well-designed constraint that can be considered in the task assignment problem of SC systems, resulting in assignment with group fairness. We mainly consider the task assignment problem in a common One-to-One SC system (O2-SC), and our goal is to maximize the quality of the task assignment while satisfying group fairness and other constraints such as budget and spatial constraints. Specifically, we first give the formal definition of task assignment with group fairness constraint for O2-SC. Then, we prove that it is essentially an NP-hard combinatorial optimization problem. Next, we provide a novel fast algorithm with theoretical guarantees to solve it. Finally, we conduct extensive experiments using both synthetic and real datasets. The experimental results show that the proposed constraint can significantly improve the group fairness level of algorithms, even for a completely random algorithm. The results also show that our algorithm can efficiently and effectively complete the task assignment of SC systems while ensuring group fairness.

关键词： Spatial crowdsourcing Group fairness Human-centered algorithm optimization algorithm

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Crystal Symmetry-Inspired algorithm for Optimal Design of Contemporary Mono Passivated Emitter and Rear Cell Solar Photovoltaic Modules

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algorithmS 2024年第7期17卷 297页

作者： Vais, Ram Ishwar Sahay, Kuldeep Chiranjeevi, Tirumalasetty Devarapalli, Ramesh Knypinski, Lukasz Rajkiya Engn Coll Sonbhadra Elect Engn Dept Churk 231206 Uttar Pradesh India Inst Engn & Technol Lucknow Elect Engn Dept Lucknow 226021 Uttar Pradesh India Inst Chem Technol Dept Elect Elect & Instrumentat Engn Indianoil Odisha Campus Bhubaneswar 751013 Orissa India Poznan Univ Tech Fac Automat Control Robot & Elect Engn PL-60965 Poznan Poland

A metaheuristic algorithm named the Crystal Structure algorithm (CrSA), which is inspired by the symmetric arrangement of atoms, molecules, or ions in crystalline minerals, has been used for the accurate modeling of Mono Passivated Emitter and Rear Cell (PERC) WSMD-545 and CS7L-590 MS solar photovoltaic (PV) modules. The suggested algorithm is a concise and parameter-free approach that does not need the identification of any intrinsic parameter during the optimization stage. It is based on crystal structure generation by combining the basis and lattice point. The proposed algorithm is adopted to minimize the sum of the squares of the errors at the maximum power point, as well as the short circuit and open circuit points. Several runs are carried out to examine the V-I characteristics of the PV panels under consideration and the nature of the derived parameters. The parameters generated by the proposed technique offer the lowest error over several executions, indicating that it should be implemented in the present scenario. To validate the performance of the proposed approach, convergence curves of Mono PERC WSMD-545 and CS7L-590 MS PV modules obtained using the CrSA are compared with the convergence curves obtained using the recent optimization algorithms (OAs) in the literature. It has been observed that the proposed approach exhibited the fastest rate of convergence on each of the PV panels.

关键词： optimization algorithm crystal symmetry solar photovoltaic single diode model double diode model

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Simulated annealing aided genetic algorithm for gene selection from microarray data

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COMPUTERS IN BIOLOGY AND MEDICINE 2023年第1期158卷 106854-106854页

作者： Marjit, Shyam Bhattacharyya, Trinav Chatterjee, Bitanu Sarkar, Ram Indian Inst Informat Technol Guwahati Dept Comp Sci & Engn Gauhati 781015 Assam India Jadavpur Univ Dept Comp Sci & Engn Kolkata 700032 W Bengal India

In recent times, microarray gene expression datasets have gained significant popularity due to their usefulness to identify different types of cancer directly through bio-markers. These datasets possess a high gene-to-sample ratio and high dimensionality, with only a few genes functioning as bio-markers. Consequently, a significant amount of data is redundant, and it is essential to filter out important genes carefully. In this paper, we propose the Simulated Annealing aided Genetic algorithm (SAGA), a meta-heuristic approach to identify informative genes from high-dimensional datasets. SAGA utilizes a two-way mutation-based Simulated Annealing (SA) as well as Genetic algorithm (GA) to ensure a good trade-off between exploitation and exploration of the search space, respectively. The naive version of GA often gets stuck in a local optimum and depends on the initial population, leading to premature convergence. To address this, we have blended a clustering-based population generation with SA to distribute the initial population of GA over the entire feature space. To further enhance the performance, we reduce the initial search space by a score-based filter approach called the Mutually Informed Correlation Coefficient (MICC). The proposed method is evaluated on 6 microarray and 6 omics datasets. Comparison of SAGA with contemporary algorithms has shown that SAGA performs much better than its peers. Our code is available at https://***/shyammarjit/SAGA.

关键词： Feature selection Genetic algorithm Simulated annealing optimization algorithm Gene expression Microarray dataset

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Intelligent fractional-order integral sliding mode control for PMSM based on an improved cascade observer

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Frontiers of Information Technology & Electronic Engineering 2022年第2期23卷 328-338页

作者： Lingfei XIAO Leiming MA Xinhao HUANG College of Energy and Power Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310027China College of Automation Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China

In this paper,an intelligent fractional-order integral sliding mode control(FOISMC)strategy based on an improved cascade observer is ***,an FOISMC strategy is designed to control a permanent magnet synchronous *** has good tracking performance,is strongly robust,and can effectively reduce *** proposed FOISMC strategy associates strong points of the integral action(which can eliminate steady-state tracking errors)and the fractional calculus(which is flexible).Second,an improved cascade observer is proposed to detect the rotor information with a smaller observation *** proposed observer combines an adaptive sliding mode observer and an extended high-gain *** addition,an improved variable-speed grey wolf optimization algorithm is designed to enhance controller *** effectiveness of the strategy is tested using simulations and an experiment involving model uncertainty and external disturbance.

关键词： Permanent magnet synchronous motor Fractional-order integral sliding mode optimization algorithm Sensorless control Observer

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An improved model-free adaptive control for nonlinear systems: An LMI approach

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APPLIED MATHEMATICS AND COMPUTATION 2023年第1期447卷

作者： Jin, Xiao-Zheng Ma, Yong-Sheng Che, Wei -Wei Qilu Univ Technol Shandong Acad Sci Sch Comp Sci & Technol Jinan 250353 Peoples R China Qingdao Univ Dept Automat Shandong Key Lab Ind Control Technol Qingdao 266071 Peoples R China

This paper proposes two model-free adaptive control (MFAC) schemes by using the linear matrix inequality (LMI) approach for the single-input single-output (SISO) and multi-input multi-output nonlinear (MIMO) systems, respectively. For each control scheme, with the aid of the dynamic linearization technique, the nonlinear system is transformed into an equivalent linear data model. In such a transformation, the nonlinear characteristic of systems is compressed into a time-varying parameter. Then, with the help of the introduction of the observer method, the tracking control problem can be converted into an optimization problem and the controller parameters can be obtained by using the LMI technique. This conversion cannot only reduce the complexity of the stability analysis but also find the appropriate controller parameters, especially for the MIMO case. Finally, three examples with comparisons are provided to illustrate the validity of the devised MFAC schemes. (c) 2023 Published by Elsevier Inc.

关键词： Model -free adaptive control Linear matrix inequality Nonlinear systems optimization algorithm

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Jaya-ICSM: A rapid inverse method driven by monitoring data for concrete-faced rockfill dams static displacement simulation

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ADVANCED ENGINEERING INFORMATICS 2023年第1期57卷

作者： Li, Yichuan Pang, Rui Xu, Bin Zhou, Yang Dalian Univ Technol Fac Infrastructure Engn Sch Hydraul Engn Dalian 116024 Peoples R China Dalian Univ Technol State Key Lab Coastal & Offshore Engn Dalian 116024 Peoples R China Dalian Univ Technol DUT Sch Civil Engn 2 Linggong RdHigh Tech Zone Dalian 116024 Peoples R China Dalian Univ Technol DUT State Key Lab Coastal & Offshore Engn 2 Linggong RdHigh Tech Zone Dalian 116024 Peoples R China

This paper presents a rapid static parameter inverse method for concrete-faced rockfill dams based on displacement data using an improved cloud surrogate model and the Jaya optimization algorithm. The improved cloud surrogate model (ICSM), which evolved from the uncertainty cloud theory, is used rapidly to establish a nonlinear relationship between static parameters and displacement. The Jaya optimization algorithm, which is proficient in recognizing the extreme value of the objective function, is selected for parameter identification. To verify the performance of the proposed method, an inverse analysis of two numerical models and a real engineering project is considered, and a comparative study with the BP neural network as the surrogate model is conducted. Study results demonstrate that ICSM has an extremely high prediction accuracy, with a mean relative error that is always under 1 %. The prediction accuracy does not increase too much even under complex nonlinear conditions or when dealing with sparse training data. Moreover, Jaya-ICSM maintains high computational efficiency throughout the entire inverse analysis, saving more than 98 % of the time compared to another inverse method and proving to be much better than direct inversion based on the finite element method. This enables real-time inverse analysis and state feedback of complex engineering. The results also illustrate that the Jaya-ICSM is promising in parameter recognition and superior in supporting the displacement evaluation of earth-rock dams. Therefore, the proposed method can be an effective tool for engineers to evaluate the safety of earth-rockfill dams and ensure their long-term stability.

关键词： Inverse analysis Concrete -faced rockfill dam Cloud surrogate model optimization algorithm Displacement simulation

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Optimizing the Electricity Consumption with a High Degree of Flexibility Using a Dynamic Tariff and Stackelberg Game

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JOURNAL OF optimization THEORY AND APPLICATIONS 2021年第1期190卷 151-182页

作者： Oprea, Simona-Vasilica Bara, Adela Ifrim, George Adrian Bucharest Univ Econ Studies Dept Econ Informat & Cybernet 6 Piata Romana Bucharest Romania Univ Galatzi Dept Automat Control & Elect Engn 47 Domneasca Galati Romania

Recent advancements in the sensor industry, smart metering systems and communication technology have led to interesting electricity consumption optimization opportunities that contribute to both peak reduction and bill savings and better integration of flexible appliances (including e-mobility). In combination with advanced tariffs, there has been a promising demand side management strategy devised from different perspectives: consumers interested in cost minimization, retailers and grid operators interested in peak minimization or hybrid solutions which reduce the costs to the extent of a certain peak level. In this paper, we propose an optimization algorithm that is significantly enhanced by a Stackelberg-type dynamic nonzero-sum game in which the consumers optimize and send their 24-h consumption schedules to the electricity retailer and receive the hourly tariff rates until their savings and the Flattening Index are maximized. Thus, it has been demonstrated that the one-iteration optimization is not as rewarding as the proposed game-optimization algorithm and that the results are heavily influenced by the degree of flexibility of the appliances. The algorithm is tested and validated using a large real input dataset, recorded at 15-min interval for a period of one year from a small residential community that consists of 11 modern houses with more than 300 appliances and high flexibility in terms of shifting, and the results highlight the consumers' gain, FI and peak to average ratio indicators.

关键词： optimization algorithm Game theory Smart meters Advanced tariff

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Optimizing relative root-zone water depletion thresholds to maximize yield and water productivity of winter wheat using AquaCrop

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AGRICULTURAL WATER MANAGEMENT 2023年第1期286卷

作者： Zhang, Ting Zuo, Qiang Ma, Ning Shi, Jianchu Fan, Yuchuan Wu, Xun Wang, Lichun Xue, Xuzhang Ben -Gal, Alon Minist Educ Key Lab Plant Soil Interact Beijing 100193 Peoples R China Minist Agr Key Lab Arable Land Conservat North China Beijing 100193 Peoples R China China Agr Univ Coll Land Sci & Technol Minist Educ Beijing 100193 Peoples R China Pingliang Acad Agr Sci Pingliang Gansu Peoples R China Univ Florida Everglades Res & Educ Ctr 3200 Canal St S Belle Glade FL 33430 USA Natl Res Ctr Intelligent Equipment Agr Beijing 100097 Peoples R China Gilat Res Ctr Agr Res Org Volcani Inst Soil Water & Environm Sci Mobile Post Negev IL-85280 Ramat Gan Israel China Agr Univ Coll Land Sci & Technol Beijing 100193 Peoples R China

Determination of relative root-zone water depletion (RRWD) thresholds to trigger irrigation is crucial to create optimal irrigation schedules targeting maximum yield and/or water productivity with limited water supply for a crop. In this study, a numerical procedure to determine RRWD thresholds was developed through coupling AquaCrop software with genetic-simplex algorithms. Using a two-year field lysimetric experiment for winter wheat conducted in the North China Plain (NCP), AquaCrop adequately simulated canopy cover, final above-ground biomass, grain yield, seasonal evapotranspiration, and soil water storage, with the normalized root mean squared error (NRMSE) smaller than 15 % and determination coefficient (R2) larger than 0.84. The global op-timum range of RRWD thresholds was preliminarily determined using the genetic algorithm, and subsequently final RRWD thresholds were optimized by fine tuning using the simplex algorithm. The RRWD threshold com-binations (composed of the RRWD thresholds to trigger different sequential irrigation events) for varying number of irrigation events (i.e.1-4) were optimized based on 39 years of historical meteorological data, and the effects of climate change on the optimal crop yield (Ya, opt), water productivity (WPopt), and the combinations of optimized RRWD threshold (RRWDopt) were investigated. The results indicated that both Ya , opt and WPopt generally increased with time showing a tendency of gradually elevated annual CO2 concentration and seasonal average effective temperature. Irrespective of the number of irrigation events during the winter wheat growing season, the differences of RRWDopt for different combinations of irrigation sequence and event in the same kind of hydrological year were relatively small, with a coefficient of variation consistently less than 23 % and a mean of 8 %. When combinations of mean RRWDopt were applied into AquaCrop to trigger irrigation for winter wheat in various hydrological years, the sim

关键词： Crop model optimization algorithm Irrigation scheduling Evapotranspiration Climate change

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Optimized inversion method for thermal parameters of concrete dam under the insulated condition

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2023年第PartB期126卷

作者： Bo, Chen Qingyi, Wang Weinan, Chen Hao, Gu Hohai Univ Coll Water Conservancy & Hydropower Engn Nanjing 210098 Peoples R China Hohai Univ State Key Lab Hydrol Water Resources & Hydraul En Nanjing 210098 Peoples R China Water Conservancy & Hydroelect Power Co Ltd Zhejiang Design Inst Hangzhou 310000 Peoples R China

It is crucial to study how thermal characteristics of concrete dam change over time, especially in cold regions, in order to guarantee long-term safety of the engineering projects. In this manuscript, an inverse analysis method by coupling the numerical simulation model and dam safety monitoring data, is proposed to solve the problem that true thermal parameters of the whole structure cannot be obtained by laboratory experiments or field tests of single points. Moreover, a numerical equivalence method of the dam and its insulation layer is introduced, in order to overcome the problem that the thickness of the insulation layer is much smaller than that of the concrete dam, resulting in low accuracy of the simulation model. Thirdly, the particle swarm optimization is introduced, in order to solve the ill-posed problems occurring during the solution process of multi-parameter inverse analysis. Considering the problem that the original particle swarm algorithm is easy to fall into local optimum and stuck edge, this study improves particles velocity and inertia weights. Benchmark function tests are applied to show the performance compared to several typical optimized algorithms. Numerical simulation and engineering verifi-cation are used to demonstrate the rationality and feasibility of the proposed method. The cases show that the residual box diagram of two typical measuring points calculated by inversion value is smaller than the median line and mean point calculated by design value. Moreover, the change law of the temperature field of the finite element calculation using the inversion values is closer to the actual measured value than that of the design value. The results indicate that the multi-parameter inverse method is feasible in insulated dam engineering. In addition, the result of the improved PSO optimization converges faster and has a higher fitness value than that of the original algorithm. It suggests that the improved PSO algorithm for thermal parameters i

关键词： Cold region Concrete dam Dam insulation Equivalent heat release coefficient optimization algorithm

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Preliminary Design of Expendable and Reusable Mixed-Staged Launch Vehicles

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JOURNAL OF SPACECRAFT AND ROCKETS 2025年第3期62卷 955-978页

作者： Goldyn, Pawel Marwege, Ansgar Riehmer, Johannes Klevanski, Josef Guelhan, Ali German Aerosp Ctr DLR EV Dept Superson & Hyperson Technol D-51147 Cologne Germany

One of the very first tasks in launch vehicle design is the preliminary sizing. It is necessary for further design choices, but it should deliver a precise estimate of the launch vehicle's mass and geometry as possible. Orbital launch vehicles can be either expendable or partially/fully reusable and can assume various stage configurations. Finding an optimal solution under practical constraints is a challenging task, which gives a wide design space for potential future launch vehicles. Hence, a generalized mathematical model of a launch vehicle design has been developed and implemented as a versatile and easily modifiable programming tool for fast and parametric system characterization and optimization. The model uses several basic parameters useful in describing launch vehicles and introduces some new parameters to account for reusability. Analytical and semi-empirical correlations are used to determine the overall system and mission performance of a launch vehicle for a given reference mission, including mass and geometry, and calculate the optimal launcher staging. The implementation of the model also allows coupling with other tools, which forms a design chain with respect to aerodynamics and trajectory simulation. With this design chain, several launch vehicles have been modeled and validated, proving the applicability of the method.

关键词： Expendable Launch Vehicle Space Launch Systems Aerodynamic Performance Lagrange Multipliers Reusable Launch System Delta-V Budget Rocket Trajectories Mass-Estimating Relations Multistage Launch Vehicle optimization algorithm

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