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International Core Journal of Engineering 2021年第11期7卷 191-196页

作者： Songlin Yin Fei Tan Maohua Yang

Multi-objective optimization problems exist everywhere in life, and solving these problems can bring many benefits to society. Multi-objective optimization is to optimize all the objective functions in the problem, but in general, there is a little conflict between these objective functions, so it is difficult to achieve multi-objective optimization. So far, many experts and scholars have carried out research on multi-objective optimization problems and have achieved a series of results. This article starts from the basic description of multi-objective optimization problems and the research status so far. There are many methods to solve multi-objective optimization problems, such as objective optimization method. Such traditional methods as well as intelligent algorithms such as particle swarm optimization and differential evolution algorithm provide a comprehensive overview of multi-objective optimization problems.

关键词： Multi-objective optimization intelligent algorithm traditional optimization method

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Solving constrained economic electrical energy generation and CO2 emission dispatch using hybrid algorithm

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ENVIRONMENTAL TECHNOLOGY & INNOVATION 2021年 24卷

作者： Jebaseelan, S. D. Sundarsingh Selvan, N. B. Muthu Kumar, C. Kalaimurugan, A. Srujana, A. Ravi, C. N. Sathyabama Inst Sci & Technol Dept EEE Chennai Tamil Nadu India SSN Coll Engn Dept Elect & Elect Engn Chennai Tamil Nadu India M Kumarasamy Coll Engn Dept Elect & Elect Engn Karur 639113 India Agni Coll Technol Dept Elect & Elect Engn Chennai Tamil Nadu India Vidya Jyothi Inst Technol Dept Elect & Elect Engn Hyderabad India

Carbon foot print is latest hot discussion and all the countries are started the initiation to minimize it. One of the main carbon emission industries is thermal electrical power generating company. For the social welfare the emission has to minimize to maximum extend. The electrical power generation company as well needs to minimize the generation cost for the better operation. Minimizing carbon foot print and minimal power generation cost are opposite to each other. When the optimization focused to minimize the generation cost it lead to increase the carbon foot print and vice versa. This paper addresses the constraint the optimization problem which needs the objective of reducing both emission and generation cost. Electrical power generating cost of thermal power plant is nonlinear and non-convex in nature. Likewise the emission produced by the thermal power plant is complex mathematical problem. intelligent algorithms are best suitable to solve these types of practical problems. In this paper hybrid of firefly algorithm and differential evolution technique is adopted to find the constrained emission minimization and cost minimization. Firefly algorithm works based on brightness, attractiveness and movement and there is no mutation process. Differential evolution technique has better mutation process and hence this mutation operation of differential evolution technique is introduced with firefly algorithm for the hybrid operation and to get better result. The research work is aimed to reduce the carbon foot print as well the generation cost of the power system. (C) 2021 The Authors. Published by Elsevier B.V.

关键词： Economic dispatch Emission dispatch intelligent algorithm Hybrid algorithm Firefly algorithm Differential evaluation Constraint optimization

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algorithm Research on Optimizing Ordering and Pricing Policy for Perishable Items

Algorithm Research on Optimizing Ordering and Pricing Policy...

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Chinese intelligent Automation Conference

作者： Yang, Xin Zhao, Yuan Wei, Jin-yu Yu, Yang Tianjin Univ Technol Zhonghuan Informat Coll Tianjin 300380 Peoples R China Hebei Univ Technol Sch Econ & Management Tianjin 300401 Peoples R China Tianjin Hantuo Comp Technol Res Inst Tianjin 300462 Peoples R China Tianjin Univ Technol Sch Management Tianjin 300384 Peoples R China

ISBN: (纸本)9789813290501;9789813290495

In reality, perishable products also contain defective ones before storage due to uncertainties during production process. In order to reduce the loss caused by the defective products, an inspection process is implemented by retailers. In view of the above, a retailer's deteriorating inventory model with defective items is established in this article. Then GA and PSO are used to figure out the model respectively and the usefulness of the intelligent algorithm is confirmed by comparing the outcomes of the two algorithms.

关键词： Inventory strategy Perishable items Defective products intelligent algorithm

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Thermal Tactile Perception: Device, Technology, and Experiments

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INTERNATIONAL JOURNAL OF COGNITIVE INFORMATICS AND NATURAL INTELLIGENCE 2021年第4期15卷 1页

作者： Bai, Junjie Peng, Jun Tang, Dedong Li, Zuojin Luo, Kan Li, Jianxin Zhang, Xue Chongqing Univ Sci & Technol Sch Elect Engn Chongqing Peoples R China Chongqing Univ Sci & Technol Sch Intelligent Technol & Engn Chongqing Peoples R China Fujian Univ Technol Sch Informat Sci & Engn Fuzhou Peoples R China

Using thermal tactile sensing mechanism based on semi-infinite body model, and combining with the advantages of maximum proportional controller, fuzzy and PID controller, a thermal tactile perception and reproduction experiment device (TTPRED) was designed based on the composite control strategy of threshold switching. The finger difference threshold measurement experiment of thermal tactile was carried out, and the finger thermal tactile difference threshold was measured. The relationship between thermal tactile sensation and emotion based on temperature cues has been explored. The experiment results show that the temperature control range of TTPRED is from -10 degrees C to 130 degrees C, the temperature resolution and precision are 0.01 degrees C and +/- 0.1 degrees C respectively, the maximum heating or cooling rate is greater than 12 degrees C, and the TTPRED can realize the temperature output of the specific waveform quickly and accurately. The experiment results of psychophysical experiment will provide the experimental foundations and technical support for the further study of thermal tactile perception and reproduction.

关键词： Composite Control intelligent algorithm intelligent Perception Perception and Reproduction Experiment Device Thermal Tactile

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The Research Overview of Global Path Planning Technology for Mobile Robot

Frontiers in Sustainable Development

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Frontiers in Sustainable Development 2021年第9期1卷 42-46页

作者： Taizhi Lv Yong Chen

Path planning is a key problem to be solved for mobile robot to realize autonomous navigation, which has important theoretical and application value. Path planning technology is the key factor restricting the intelligent level of mobile robot. If path planning cannot be intelligent, mobile robot will have developed limbs and simple mind, which will affect the transformation and promotion of technology. Taking mobile robot path planning as the research object, this paper introduces the research progress of global path planning and local path planning.

关键词： Mobile robot Autonomous navigation Path planning intelligent algorithm Map

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Investment decision-making optimization of energy efficiency retrofit measures in multiple buildings under financing budgetary restraint

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JOURNAL OF CLEANER PRODUCTION 2019年 215卷 1078-1094页

作者： He, Yong Liao, Nuo Bi, Jiajing Guo, Liwei Guangdong Univ Technol Sch Management Guangzhou 510520 Guangdong Peoples R China Univ Delaware Ctr Energy & Environm Policy Newark DE 19716 USA Hangzhou Polytech Sch Business Hangzhou 311402 Zhejiang Peoples R China

Regarding to energy efficiency retrofit investment to numerous buildings, which buildings should be invested and which of the retrofit measures should be implemented for investable buildings are challenging tasks. The current literature have studied on choosing energy efficiency retrofit measures in single building, relatively little attention has been paid to the retrofit investment decision-making in multiple buildings. In addition, the existing studies almost put the retrofit cost as an objective that need to be minimized, and the retrofit capital budget is not taken into consideration. This paper proposes a decision-making optimization framework for energy efficiency retrofit investment in numerous buildings under financing budgetary restraint. A multi-objective optimization model with the economic goals being the net present value and time of return, and the environmental goals being the energy saving and emission reduction is presented, and then the intelligent optimization method combing particle swarm optimization and genetic algorithm is designed to search the retrofit investment strategy. The obtained investment strategy could determine which of the buildings should be invested to retrofit, and the combination of retrofitting measures for every investable building. An empirical study is conducted on 27 buildings of non-governmental organization in the state of Delaware in the United States, and the results indicate that the validity of the proposed framework. The findings indicate that the framework is an effective approach to assist the sustainability goal at regional level. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Buildings energy efficiency Energy efficiency retrofit Investment decision-making Multi-objective optimization intelligent algorithm

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Cooperative green supply chain management with greenhouse gas emissions and fuzzy demand

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JOURNAL OF CLEANER PRODUCTION 2019年 208卷 1421-1435页

作者： Noh, Jiseong Kim, Jong Soo Hanyang Univ Dept Ind & Management Engn Erica Campus Ansan 15588 South Korea

Concerns about environmentally sustainable supply chain management have increased widely in recent years. As a consequence, supply chain members have cooperated with one another to make efficient contracts, frequently called green supply-chain management contracts. The purpose of this paper is to investigate one such contract between a single manufacturer and multiple retailers with limited resources for several types of products under greenhouse-gas emission regulations. Each retailer orders the products regularly within a limited budget and warehouse capacity. In response to orders, the manufacturer produces products and ships them after inspections. Demand for the products can be either known or have some uncertainty, which can best be represented using fuzzy number demand. To reflect demand properties, this paper introduces two nonlinear integer programming models, a crisp model and a fuzzy model. A genetic algorithm (GA) and hybrid genetic algorithm-pattern search (HGAS) are developed to solve the models. Numerical experiments evaluating the efficiency of the algorithms showed that the HGAS method performed better than the GA. Also observed is that the crisp model's average total costs were lower than those of the fuzzy model. The results as a whole indicate that the models can evaluate the performance of contracts and optimize cooperative green supply chain management. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Green supply chain management Greenhouse gas Nonlinear integer programming intelligent algorithm

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Hardware implementation of the fuzzy logic MPPT in an Arduino card using a Simulink support package for PV application

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IET RENEWABLE POWER GENERATION 2019年第3期13卷 510-518页

作者： Fannakh, Mhamed Elhafyani, Mohamed Larbi Zouggar, Smail Univ Mohammed 1st High Sch Technol Lab Elect Engn & Maintenance LEEM Oujda Morocco

The work presented in this study aims to develop an intelligent algorithm, based on fuzzy logic, to track the maximum power point (MPP) of a photovoltaic (PV) panel. Modelling and simulation steps of the PV panel are made by using the MATLAB/Simulink environment, before passing to the description of fuzzy logic MPP tracking (MPPT) algorithm. On an Arduino Mega 2560 controller board, a real-time implementation of the MPPT algorithm by using Simulink Support Package for Arduino Hardware in MATLAB/Simulink was conducted to experimentally validate the preliminary results of simulations. The proposed work outlines also the solution to modify pulse-width modulation frequency of Arduino when it is used with Simulink.

关键词： control system synthesis fuzzy control power generation control maximum power point trackers digital simulation control engineering computing photovoltaic power systems Matlab microcontrollers pulse width modulation software packages Arduino card Simulink support package PV application intelligent algorithm maximum power point photovoltaic panel PV panel MATLAB Simulink environment fuzzy logic MPP tracking algorithm Arduino Mega 2560 controller board hardware implementation pulse-width modulation frequency

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HEURISTIC intelligent METHOD FOR MACHINE MAINTENANCE AND PROCESS OPTIMIZATION

HEURISTIC INTELLIGENT METHOD FOR MACHINE MAINTENANCE AND PRO...

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作者： Yanfei Lu Georgia Institute of Technology

学位级别：博士

As the technology in mechanical engineering advances, increasing complex mechanical systems are developed to achieve better quality and accuracy with prolonged useful life. However, with the added components and processes included in the mechanical system, the relationship between the input process parameter and output process parameter is difficult to define precisely. Unlike the simple spring-mass-damper system, which the displacement, velocity and acceleration can be described by linear differential equations, the system exhibits a high dimensional nonlinear relationship from the input parameter to the output parameter. Additionally, with more components included in the system, the probabilities of a machinery breakdown increase. Although the quality of the components improves, it does not offset the complication of the added complexity. Traditional scheduled maintenance cannot accommodate to the change of configurations of the system in a timely manner. Therefore, condition-based-maintenance (CBM) is implemented to reduce cost and improve reliability. The CBM monitors the actual running condition of the mechanical systems by using data acquired from different sensors. After the data acquisition, various signal processing techniques are implemented to denoise and extract critical features from the acquired data. The analysis of the data yields useful information for the prognostic algorithms to predicate the types of damage and the remaining useful life (RUL) of the system. Statistical methods are generally added in the prognosis to address the stochastic nature of the mechanical system and determine an interval for optimal maintenance. The addition of machine learning tools helps solving the complex problems without the requirement of complete understandings of the sophisticated systems or analytical models. The major two categories machine learning are implemented to understand mechanical systems are regression and classification. In machinery diagnosis, the ma

关键词： Signal processing Bearing diagnosis Bearing prognosis Machine learning intelligent algorithm Optimization

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Research on Flexible Flow⁃Shop Scheduling Problem with Lot Streaming in IOT⁃Based Manufacturing Environment

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Transactions of Nanjing University of Aeronautics and Astronautics 2020年第6期37卷 831-838页

作者： DAI Min WANG Lixing GU Wenbin ZHANG Yuwei DORJOY M M H College of Mechanical Engineering Yangzhou UniversityYangzhou 225127P.R.China Department of Mechanical and Electrical Engineering Hohai UniversityChangzhou 213022P.R.China

It is urgent to effectively improve the production efficiency in the running process of manufacturing systems through a new generation of information *** to the current growing trend of the internet of things(IOT)in the manufacturing industry,aiming at the capacitor manufacturing plant,a multi-level architecture oriented to IOT-based manufacturing environment is established for a flexible flow-shop scheduling ***,according to multi-source manufacturing information driven in the manufacturing execution process,a scheduling optimization model based on the lot-streaming strategy is proposed under the *** improved distribution estimation algorithm is developed to obtain the optimal solution of the problem by balancing local search and global ***,experiments are carried out and the results verify the feasibility and effectiveness of the proposed approach.

关键词： IOT-based manufacturing flexible flow-shop scheduling intelligent algorithm lot-streaming strategy

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