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Reinforcement Learning for Dynamic Mutation Process Control in Multi-Objective Differential Evolution

IFAC-PapersOnLine 2022年第15期55卷 117-122页

作者： Lue Tao Gongshu Wang Yang Yang Yun Dong Lijie Su Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University) Ministry of Education China National Frontiers Science Center for Industrial Intelligence and Systems Optimization Northeastern University China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Northeastern University China

To improve the search performance of the multi-objective differential evolution algorithm, we use a reinforcement learning agent to control the dynamic mutation process. First, a novel multi-objective optimization framework with new mutation operators is developed. Then, a Q-learning algorithm is introduced to select mutation operators with different characteristics adaptively. Specifically, we design three feature functions to describe the state of the population observed by the agent. Based on the observed state, the agent dynamically selects the mutation operator in each generation, which strongly improved the searching ability. We compare the performance of the proposed method with two state-of-art algorithms on benchmark functions and find that the proposed algorithm has a better performance in multiple indicators. At the same time, the component validity analysis also shows the effectiveness of the Q-learning and the framework introduced in this paper. Finally, the learning process shows that the agent can achieve asymptotic convergence.

关键词： Reinforcement Learning Evolutionary Algorithm Multi-Objective Deferential Evolution Mutation Process Control Operator Selection

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IoT Device Connectivity Selection Using a Hybrid Multi-Criteria Group Decision-Making Approach

IoT Device Connectivity Selection Using a Hybrid Multi-Crite...

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Decision Aid Sciences and Application (DASA), International Conference on

作者： Mouna Regaieg Cherif Hela Moalla Frikha Research Laboratory “Modeling and Optimization for Decisional Industrial and Logistic Systems” Faculty of Economic Sciences and Management of Sfax University of Sfax Sfax Tunisia Research Laboratory “Optimisation Logistique et Informatique Decisionnelle” University of Sfax Higher Institute of Industrial Management Sfax Tunisia

The Internet-of-Things (IoT) systems hold immense promise for transforming various aspects of our lives and industries, driving significant societal and economic advancements. This research paper aims to investigate the significance of IoT systems in various domains, focusing specifically on the industrial application, emphasizing the pivotal role of reliable and efficient device connectivity within such systems. To address the challenges posed by uncertainty and ambiguity in real-life scenarios, we proposed the integration of rough set theory with multi-criteria decision-making approaches to evaluate and classify IoT devices in the industrial domain. The utilization of the proposed hybrid multi-criteria group decision-making approach allows us to effectively model and handle the uncertainty arising from expert assessments. This paper emphasized the computation of parameter weights using a chosen weighting technique to facilitate decision-making processes influenced by subjective information. Finally, an example case shows how the framework may be applied.

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Characterization and evaluation of the treated water quality from the wastewater treatment plant of the Djelfa city

Characterization and evaluation of the treated water quality...

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Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET), International Conference on

作者： Salah Karef Mohamed Azlaoui Abdelhadi Hameurlaine Mokhtar Fodili Laboratory of Modeling Optimization and Simulation of Real Complex Systems University of Djelfa Djelfa Algeria Laboratory of Applied Automation & Industrial Diagnostics University of Djelfa Djelfa Algeria Laboratory of Organic Chemistry and Natural Substances University of Djelfa Djelfa Algeria

ISBN: (数字)9798350346336

ISBN: (纸本)9798350346343

In the framework of the protection of the environment, we proceeded during the year 2016 (12 months), to the follow-up of variation of the wastewater pollution parameters at the inlet and at the outlet of the treatment plant of the Djelfa city, which operates by activated sludge, following the medium load *** physicochemical analyzes were carried out on the following parameters: pH, temperature, eclectic conductivity, turbidity, Total suspended solids, COD, BOD5, NH4+, NO3- and total phosphorus. At the end of these analyses, we obtained good elimination yield of 92% to 91% for TSS and 92% to 91% for BOD5. The COD recorded a reduction of 84% to 83%. Total phosphorus achieved a removal efficiency of 55% to 66%. For nitrogen, Ammonia experienced a 61% to 57% reduction from inlet to outlet of the plant. On the other hand, nitrates recorded an increase of 200% to 236%, due to *** quality of the treated water, for the majority of the parameters, complies with the standards required by Algerian regulations and those of the WHO. We can conclude that the treatment system adopted at the level of the WWTP of Djelfa is effective and justified its design and its objective of realization.

关键词： Ammonia Oxygen Urban areas Phosphorus Water pollution Biochemistry Wastewater

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A Rubber Tyred Gantry Crane Scheduling in Container Terminals in Port of Sfax-Tunisia

A Rubber Tyred Gantry Crane Scheduling in Container Terminal...

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International Conference on Control, Decision and Information Technologies (CoDIT)

作者： S. Ben Zina A. Elloumi A. Quilliot Laboratory of Modeling and Optimization for Decisional Industrial and Logistic Systems (MODILS) University of Sfax. (FSEGS) Sfax Tunisia Université Clermont Auvergne LIMOS UMR CNRS 6158 Aubière Cedex France

This paper explores the Gantry Cranes Scheduling Problem (GCSP), specifically focusing on determining the optimal slot unloading/loading sequences for gantry cranes assigned to containers in a block of stacking. The gantry crane scheduling proposed in this paper, which is mathematically modeled by a mixed integer programming model is proposed. using the terminal operating system used in the port studied provides a new (MILP). Finally, the paper compares the results obtained from the proposed model with those of the terminal port for real instances.

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A Novel Black Box Process Quality optimization Approach based on Hit Rate

arXiv

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arXiv 2023年

作者： Yang, Yang Wu, Jian Song, Xiangman Wu, Derun Su, Lijie Tang, Lixin Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Shenyang110819 China Liaoning Key Laboratory of Manufacturing System and Logistics Optimization Shenyang110819 China Manufacturing Department of Shanghai Meishan Iron & Steel Co. LTD. Jiangsu Nanjing210039 China Frontier Science Center for Industrial Intelligence and Systems Optimization

Hit rate is a key performance metric in predicting process product quality in integrated industrial processes. It represents the percentage of products accepted by downstream processes within a controlled range of quality. However, optimizing hit rate is a non-convex and challenging problem. To address this issue, we propose a data-driven quasi-convex approach that combines factorial hidden Markov models, multitask elastic net, and quasi-convex optimization. Our approach converts the original non-convex problem into a set of convex feasible problems, achieving an optimal hit rate. We verify the convex optimization property and quasi-convex frontier through Monte Carlo simulations and real-world experiments in steel production. Results demonstrate that our approach outperforms classical models, improving hit rates by at least 41.11% and 31.01% on two real datasets. Furthermore, the quasi-convex frontier provides a reference explanation and visualization for the deterioration of solutions obtained by conventional models. Copyright © 2023, The Authors. All rights reserved.

关键词： Convex optimization

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A Novel Correlation-optimized Deep Learning Method for Wind Speed Forecast

arXiv

引用

arXiv 2023年

作者： Yang, Yang Lang, Jin Wu, Jian Zhang, Yanyan Zhao, Xiang Key Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Ministry of Education 110819 China Liaoning Engineering Laboratory of Data Analytics and Optimization for Smart Industry Northeastern University Shenyang110819 China Liaoning Key Laboratory of Manufacturing System and Logistics Northeastern University Shenyang110819 China Institute of Industrial & Systems Engineering Northeastern University Shenyang110819 China

The increasing installation rate of wind power poses great challenges to the global power system. In order to ensure the reliable operation of the power system, it is necessary to accurately forecast the wind speed and power of the wind turbines. At present, deep learning is progressively applied to the wind speed prediction. Nevertheless, the recent deep learning methods still reflect the embarrassment for practical applications due to model interpretability and hardware limitation. To this end, a novel deep knowledge-based learning method is proposed in this paper. The proposed method hybridizes pre-training method and auto-encoder structure to improve data representation and modeling of the deep knowledge-based learning framework. In order to form knowledge and corresponding absorbers, the original data is preprocessed by an optimization model based on correlation to construct multi-layer networks (knowledge) which are absorbed by sequence to sequence (Seq2Seq) models. Specifically, new cognition and memory units (CMU) are designed to reinforce traditional deep learning framework. Finally, the effectiveness of the proposed method is verified by three wind prediction cases from a wind farm in Liaoning, China. Experimental results show that the proposed method increases the stability and training efficiency compared to the traditional LSTM method and LSTM/GRU-based Seq2Seq method for applications of wind speed forecasting. Copyright © 2023, The Authors. All rights reserved.

关键词： Wind power

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Numerical Investigation of the Effect of Storage Tank Orientation on the Melting of Phase Change Material in a Square-Shaped Tank

Numerical Investigation of the Effect of Storage Tank Orient...

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International Renewable Energy Congress

作者： Fatiha Chebli Farid Mechighel Ridha Djebali Energy Systems Technology Laboratory National Higher School of Technology and Engineering Annaba Algeria Department of Mechanical Engineering Research laboratory in mechanics of materials and industrial maintenance (LR3MI) Faculty of Technology Badji Mokhtar - Annaba University Annaba Algeria UR: Modeling Optimization and Augmented Engineering ISLAIB University of Jendouba Béja Tunisia

ISBN: (数字)9798331516772

ISBN: (纸本)9798331516789

The storage capacity of surplus energy produced by renewable and conventional power plants makes latent heat storage units (LHSUs) using phase change materials (PCMs) relevant. The phase change processes are affected by the geometric shape of the PCM tank and the operating conditions to which it is subjected. This study explores the behavior of the melting process of paraffin (a PCM) in a square-shaped tank oriented in various orientations 0°, 30°, 60° and 90°. The results show that initially, the melting is dominated by thermal conduction, but as it progresses, natural convection takes over. Furthermore, the melting rate increases with the inclination angle. The total energy stored in a PCM during melting remains constant, although the time needed to store that energy can be considerably influenced by the orientation of the cavity.

关键词： Phase change materials Heating systems Renewable energy sources Shape Morphology Numerical simulation Convection Power generation

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Discrete Event Simulation to Evaluate Different Treatments of Diabetic Retinopathy Disease

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American Journal of Operations Research 2022年第6期12卷 250-260页

作者： Salma Kanoun Badreddine Jerbi Hichem Kamoun Laboratory of Modeling and Optimization for Decisional Industrial and Logistic Systems College of Economic Sciences and Management University of Sfax Sfax Tunisia Higher Institute of Management Gabes Tunisia Detached to Quassim University College of Business and Economics Saudi Arabia

modeling approach using discrete event simulation has been proven to work well in modeling in health care. The aim of our paper is to propose a simulation approach which shows realistic models presenting different possible treatments in different stages of diabetic retinopathy. We have presented three models in order to choose the best treatment for diabetic retinopathy patients. The first model describes the flow of a patient through stages without any medical treatments. It takes 13 years to reach blindness. The second model which includes the laser photocoagulation treatments leads to blindness after 46 years. Then, the third model illustrates the involvement of vitrectomy operation and delays blindness by 23 years. To construct the models, data were taken from experienced doctors and professors of the ophthalmology department in the University hospital Habib Bourguiba and the endocrinology department in the University hospital Hedi Chaker in Sfax, Tunisia. Our objective is to delay reaching the blindness stage as late as possible. Three models were developed, verified and validated through many iterative implementations with ARENA simulation software.

关键词： Diabetic Retinopathy modeling Discrete Event Simulation Health Care ARENA Simulation Software

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Reliability Assessment of LCC-HVDC links Using Protection Devices

Reliability Assessment of LCC-HVDC links Using Protection De...

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Renewable Solutions for Ecosystems: Towards a Sustainable Energy Transition (ICRSEtoSET), International Conference on

作者： Abdelhadi Hameurlaine Larbi Boukezzi Salah Karef Haouari Sayah Laboratory of Applied Automation & Industrial Diagnostics University of Djelfa Djelfa Algeria Materials Science and Informatics Laboratory MSIL University of Djelfa Djelfa Algeria Com Laboratory of Modeling Optimization and Simulation of Real Complex Systems University of Djelfa Djelfa Algeria Intelligent Control and Electrical Power System Laboratory University of SidiBel-Abbes SidiBel-Abbes Algeria

ISBN: (数字)9798350346336

ISBN: (纸本)9798350346343

the DC/AC interaction and the presence of the high nonlinearity in the HVDC links, these problems needs to examine the behavior of the system in steady-state and transient conditions in order to define the great role of protection functions and control parameters. Furthermore, Control and protection systems are a vital part of an HVDC system to guarantee the safety, reliability, and stability of its operation. This research aim is to provide the solutions for control and protection problems that can occur in HVDC link. In this paper, we study how we mitigate this serious malfunction of commutation failure process in the operation of HVDC converters. Indeed some protection functions like the commutation failure prevention. Furthermore, HVDC transmission systems are vulnerable to DC faults and its protection becomes ever more important with the fast growth in the number of installations. Finally, the dynamics of the studied power system including the HVDC link is thoroughly investigated through various simulation scenarios.

关键词： Performance evaluation HVDC transmission Power system dynamics Power system stability Stability analysis Power system reliability Steady-state

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Use of Electric Vehicles in Home-Health Care Routing Problems: Analysis of a Multi-objective Approach under Uncertainty

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IFAC-PapersOnLine 2021年第2期54卷 127-132页

作者： Oumayma Bahri El-Ghazali Talbi Lionel Amodeo Laboratory of Logistics and Optimization of industrial Systems University of Troyes 12 rue Marie Curie 10004 Troyes FRANCE Laboratory INRIA LILLE NORD EUROPE 172 Avenue de Bretagne 59000 Lille FRANCE

Our aim in this study is to propose a novel approach for optimizing a variant of the home health care routing problem, in which the health-care workers perform a requested number of visits to patients by using electric vehicles. Our approach on the one hand uses multi-objective optimization methods to find optimal planning routes of EVs and on the other hand deals with uncertainty in some major problem constraints. The goal is to help decision makers choosing appropriate routes; while minimising the cost of electric vehicular displacements in terms of: the total travel cost for all home-health workers and the waiting time for all patients. Moreover, we consider in our problem the fuzzy nature of some major constraints.

关键词： Electric Vehicles Home health care sector Routing problems Multi-objective optimization Metaheuristics Uncertainty aspect Fuzziness

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