检索结果-内蒙古大学图书馆

A multi-objective stochastic programming model for post-disaster management

TRANSPORTMETRICA A-TRANSPORT SCIENCE 2022年第3期18卷 1103-1126页

作者： Gharib, Mehrdad Fatemi Ghomi, Seyyed Mohammad Taghi Jolai, Fariborz Amirkabir Univ Technol Dept Ind Engn 424 Hafez Ave Tehran *** Iran Univ Tehran Coll Engn Dept Ind Engn Tehran Iran

This paper develops a mathematical model for post-disaster planning with human casualties, which can be considered as operational guidance for the proper use of emergency resources. For this purpose, a stochastic mixed-integer programming model is provided to formulate the problem. The objective functions of the model are (1) maximizing the survival probability of patients, (2) minimizing the maximum of completion time of treatment of all patients, and (3) minimizing the total cost of operations. The model is solved with the epsilon-constraint method. Due to the NP-hardness of the problem which is a significant challenge in the literature, two innovative meta-heuristic algorithms are proposed, i.e. a non-dominated sorting genetic algorithm (NSGA-II) and a multi-objective simulated annealing (MOSA). Finally, a comprehensive computational analysis is performed for evaluation purposes. Also, a case study is made on the earthquake in Iran, which illustrates the real-world application of the model.

关键词： Emergency medical services multi-objective stochastic programming epsilon-constraint method multi-objective simulated annealing non-dominated sorting genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Sequential Clustering and Classification Approach to Analyze Sales Performance of Retail Stores Based on Point-of-Sale Data

引用

INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 2022年第3期21卷 885-910页

作者： Yang, Chao-Lung Nguyen, Thi Phuong Quyen Natl Taiwan Univ Sci & Technol Dept Ind Management 43Sec 4Keelung Rd Keelung Taiwan Univ Sci & Technol Univ Danang Fac Project Management 54 Nguyen Luong Bang Danang Vietnam

Point-of-Sale (POS) data analysis is usually used to explore sales performance in business commence. This manuscript aims to combine unsupervised clustering and supervised classification methods in an integrated data analysis framework to analyze the real-world POS data. Clustering method, which is performed on sales dataset, is used to cluster the stores into several groups. The clustering results, data labels, are then combined with other information in store features dataset as the inputs of the classification model which classifies the clustering labels by using store features dataset. non-dominated sorting generic algorithm-II (NSGA-II) is applied in the framework to employ the multi-objective of clustering and classification. The experimental case study shows clustering results can reveal the hidden structure of sales performance of retail stores while classification can reveal the major factors that effect to the sales performance under different group of retail stores. The correlations between sales clusters and the store information can be obtained sequentially under a series of data analysis with the proposed framework.

关键词： Data Clustering data classification multi-objective optimization non-dominated sorting genetic algorithm point of sale data

来源：评论

学校读者我要写书评

暂无评论

Design Optimization of Magneto-active Elastomer Unimorph Actuator for Shape Programming 17

Design Optimization of Magneto-active Elastomer Unimorph Act...

引用

Conference on Behavior and Mechanics of Multifunctional Materials XVII

作者： Pan, Tan Frecker, Mary Penn State Univ Dept Mech Engn University Pk PA 16802 USA

ISBN: (纸本)9781510660755;9781510660762

In this study, a magneto-active elastomer (MAE) unimorph actuator is optimally designed for shape programming. An optimization design approach for the MAE unimorph actuator is developed to design the geometry and material properties of the structure. Within the design optimization, a previously developed and validated analytical model is applied to predict the actuation performance of MAE unimorph actuator under a user-specified external magnetic field. This model considers the unimorph as a segmented beam with large deflections and approximates the response of the material to the magnetic field as segment-wise applied torques. Then a single objective function representing the shape error is minimized using a genetic algorithm (GA). The multi-objective non-dominated sorting genetic algorithm II (NSGA-II) is also implemented to maximize both normalized free deflection and blocked force. A Pareto set of optimal solutions is obtained and the best design can be selected based on application requirements. This work has the potential to provide tailorable shape change in medical device applications that require adjustments over time such as changing patient anatomy as treatment progresses. The devices can be actuated under an external magnetic field without wires or human interference. Additive manufacturing can realize the feasibility of fabrication for the designed MAE unimorph actuator by printing complex geometry and spatially tailored magnetic and mechanical properties.

关键词： Magnetoactive elastomer genetic algorithm non-dominated sorting genetic algorithm non-dominated sorting genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Model Free Adaptive Control for Air-Conditioning System in Office Buildings Based on Improved NSGA-II algorithm 12

Model Free Adaptive Control for Air-Conditioning System in O...

引用

IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)

作者： Chen, Pan Gaol, Jingjing Yang, Xu Zhangl, Tao Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

ISBN: (纸本)9798350321050

Driven by the increasing demand for thermal comfort in office building environment and energy saving in building operation process, a model free adaptive control (MFAC) method for air conditioning system based on optimal environmental parameter settings is proposed in this paper. To this end, on the basis of the energy consumption model of common office buildings, the cooling load brought by the fresh air system is considered. The model is combined with the predicted mean vote (PMV) thermal comfort model to constitute an optimization problem. The improved non-dominated sorting genetic algorithm is used to solve the optimization problem to obtain the optimal environmental parameter settings at first. Then, an improved model-free adaptive control method is used for regulation. An adjustment item is added to the estimation algorithm to make the pseudo partial derivative reach the ideal value faster, to reach the optimal environmental parameter setting value faster. Finally, the experimental verification is carried out on the building environment monitoring system of an office building demonstration room, which shows the proposed method can achieve the optimal environment parameter settings, and at the same time can reduce the number of regulation of the air conditioning system and extend the service life of the equipment.

关键词： Office buildings predicted mean vote non-dominated sorting genetic algorithm model-free adaptive control

来源：评论

学校读者我要写书评

暂无评论

A Multiobjective Approach for the Optimal Placement of Protection and Control Devices in Distribution Networks With Microgrids

引用

IEEE ACCESS 2022年 10卷 41776-41788页

作者： Reiz, Cleberton de Lima, Tayenne Dias Leite, Jonatas Boas Javadi, Mohammad Sadegh Gouveia, Clara Sofia Sao Paulo State Univ Dept Elect Engn BR-15385 Ilha Solteira Brazil Inst Syst & Comp Engn Technol & Sci P-4200465 Porto Portugal

Protection and control systems represent an essential part of distribution networks by ensuring the physical integrity of components and by improving system reliability. Protection devices isolate a portion of the network affected by a fault, while control devices reduce the number of de-energized loads by transferring loads to neighboring feeders. The integration of distributed generation has the potential to enhance the continuity of energy services through islanding operation during outage conditions. In this context, this study presents a multi-objective optimization approach for sizing and allocating protection and control devices in distribution networks with microgrids supplied by renewable energy sources. Reclosers, fuses, remote-controlled switches, and directional relays are considered in the formulation. Demand and generation uncertainties define the islanding operation and the load transfer possibilities. A non-dominated sorting genetic algorithm is applied in the solution of the allocation problem considering two conflicting objectives: cost of energy not supplied and equipment cost. The compromise programming is then performed to achieve the best solution from the Pareto front. The results show interesting setups for the protection system and viability of islanding operation.

关键词： Circuit faults Fuses Microgrids Uncertainty Renewable energy sources Distribution networks Reliability Distribution systems microgrids protection system planning non-dominated sorting genetic algorithm compromise programming

来源：评论

学校读者我要写书评

暂无评论

Multi-objective casting production scheduling problem by a neighborhood structure enhanced discrete NSGA-II: an application from real-world workshop

引用

SOFT COMPUTING 2022年第17期26卷 8911-8928页

作者： Tan, Weihua Yuan, Xiaofang Yang, Yuhui Wu, Lianghong Hunan Univ Coll Elect & Informat Engn Changsha 410082 Hunan Peoples R China Hunan Univ Sci & Technol Coll Informat & Elect Engn Xiangtan 411201 Peoples R China

Casting production scheduling problem has attracted increasing research attention in recent years to facilitate the profits, efficiency, and environment issues of casting industry. Casting is often characterized by the properties of intensive energy consumption and complex process routes, which motivate the in-depth investigation on construction of practical multi-objective scheduling models and development of effective algorithms. In this paper, for the first time, the multi-objective casting production scheduling problem (MOCPSP) is constructed to simultaneously minimize objectives of defective rate, makespan, and total energy consumption. Moreover, a neighborhood structure enhanced discrete NSGA-II (N-NSGA-II) is designed to better cope with the proposed MOCPSP. In the N-NSGA-II, the advantage of selection mechanism of NSGA-II is fully utilized for selecting non-dominate solution, three neighborhood structures are elaborately designed to strengthen the ability of the local search, and a novel solution generating approach is proposed to increase the diversity of solutions for global search. Finally, a real-world case is illustrated to evaluate the performance of the N-NSGA-II. Computational results show that the proposed N-NSGA-II obtains a wider range of non-dominated solutions with better quality compared to other well-known multi-objective algorithms.

关键词： Multi-objective casting production scheduling problem Defective rate Variable processing speed non-dominated sorting genetic algorithm Neighborhood structure

来源：评论

学校读者我要写书评

暂无评论

Machine learning-based optimization of geometrical accuracy in wire cut drilling

引用

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2022年第11-12期123卷 4265-4276页

作者： Ghasempour-Mouziraji, Mehran Hosseinzadeh, Morteza Hajimiri, Hossein Najafizadeh, Mojtaba Shirkharkolaei, Ehsan Marzban Univ Aveiro TEMA Ctr Mech Technol & Automat Mech Engn Dept Aveiro Portugal Univ Aveiro Sch Design Management & Prod Technol EMaRT Grp Emerging MatResTechnol Aveiro Portugal Islamic Azad Univ Dept Engn Ayatollah Amoli Branch Amol Iran Azerbaijan State Agr Univ Fac Engn Ganja Azerbaijan Shahrood Univ Technol Fac Chem & Mat Engn Shahrood *** Iran Univ Salento Dept Innovat Engn Via Arnesano I-73100 Lecce Italy Isfahan Univ Technol Dept Mech Engn Esfahan *** Iran

Wire cut electrical discharge machining (EDM) equipment is run by computer numerically controlled (CNC) instruments and it is widely used in various industries such as aerospace, medical, and electronics. Thus, producing tight corners or very intricate patterns, wire EDM's increased precision allows for intricate patterns and cuts. Not only dimensional but also geometrical precision of products does play a very important role in today's industry. To the best of our knowledge, despite the dimensional precision, the geometrical precision has been studied by few researchers. Employing machine learning techniques, such as artificial neural networks (ANN) and non-dominated sorting genetic algorithm (NSGA), this research tries to minimize the geometrical deviation of parts produced by wire cut machining. To do so, firstly, samples have been produced based on the design matrix which contained input parameters, namely wire velocity, pulse time, and feed rate. The desired deviation from cylindricity, circularity, and symmetricity are investigated using NSGA and ANN. Then, the best and optimal combination of parameters are offered, which shows that the combination of ANN and NSGA has a significant effect on finding the optimum machining parameters. This study could supply a new viewpoint for studying geometric accuracy in wire cut drilling.

关键词： Wire cut machining Geometrical tolerance Machine learning Artificial neural network non-dominated sorting genetic algorithm Coordinate measuring machine

来源：评论

学校读者我要写书评

暂无评论

Multi-objective optimization method of blast furnace operation performance indicators based on data and knowledge 35

Multi-objective optimization method of blast furnace operati...

引用

35th Chinese Control and Decision Conference (CCDC)

作者： Yan, Duojin Yang, Chunjie Yang, Bo Chen, Yu Kong, Liyuan Chen, Jian Zhejiang Univ Coll Control Sci & Engn Hangzhou Peoples R China Tsinghua Univ Dept Automat Beijing Peoples R China Jiangsu Binxin Iron & Steel Grp Co Ltd Lianyungang Peoples R China

ISBN: (纸本)9798350334722

During blast furnace (BF) ironmaking, hot metal quality and energy consumption directly affect industrial economic benefits. Field engineers usually adjust the production state based on their experience, which makes control optimization uncertain. A data and knowledge-based optimization framework for BF operation performance indicators is proposed in this paper. Firstly, design the Attention Long Short Term Memory (Attention-LSTM) neural network to predict the Silicon content and coke ratio, which is used as fitness value function of the multi-objective optimization model. To initialize the population, knowledge based non-dominated sorting genetic algorithm (KB-NSGA) uses a knowledge base of historical optimal solutions. Finally, an optimization solution set that meets the actual production requirements is obtained using the TOPSIS evaluation method. The KB-NSGA successfully achieves the goal compared with other genetic algorithms. The effectiveness of the proposed method is verified by long-term running experiments.

关键词： Blast furnace ironmaking multi-objective optimization Attention Long Short Term Memory non-dominated sorting genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Solving a bi-objective unmanned aircraft system location-allocation problem

引用

ANNALS OF OPERATIONS RESEARCH 2022年第2期319卷 1631-1654页

作者： Karatas, Mumtaz Yakici, Ertan Dasci, Abdullah Natl Def Univ Naval Acad TR-34940 Istanbul Turkey Sabanci Univ Sabanci Business Sch TR-34956 Istanbul Turkey

In this paper we introduce a bi-objective location-allocation problem for Unmanned Aircraft Systems (UASs) operating in a hostile environment. The objective is to find the locations to deploy UASs and assign Unmanned Aerial Vehicles to regions for surveillance. One of the objectives is to maximize search effectiveness, while the second is the minimization of the threats posed to the UASs. These two objectives are in conflict, because they are affected differently by the proximity between the UAS locations and the target regions. First, we have formulated this problem as a mixed integer nonlinear program. Next, we have developed its linearization which can be solved by a commercial optimizer for small-scale problem instances. To solve large-scale problems, we have adopted a well-known metaheuristic for multi-objective problems, namely the elitist non-dominated sorting genetic algorithm. We have also developed a hybrid approach, which has proven to be more effective than each approach alone.

关键词： Location Multi-objective Unmanned aircraft system Unmanned aircraft vehicle non-dominated sorting genetic algorithm

来源：评论

学校读者我要写书评

暂无评论

Review of hybrid electric powered aircraft,its conceptual design and energy management methodologies

引用

Chinese Journal of Aeronautics 2021年第4期34卷 432-450页

作者： Ye XIE Al SAVVARISAL Antonios TSOURDOS Dan ZHANG Jason GU Intelligent Robot Research Centre Zhejiang LabHangzhou311100China School of Aerospace Transport and ManufacturingCranfield UniversityBedford MK430ALUnited Kingdom York University North YorkToronto M3J 1P3Canada Dalhousie University HalifaxNova Scotia B3H 4R2Canada

The paper overviews the state-of-art of aircraft powered by hybrid electric propulsion *** research status of the design and energy management of hybrid aircraft and hybrid propulsion systems are further *** first contribution of the review is to demonstrate that,in the context of relatively underdeveloped electrical storage technologies,the study of mid-scale hybrid aircraft can contribute the most to both theoretical and practical ***,the profits and potential drawbacks of applying hybrid propulsion to mid-scale hybrid airplanes have not been thoroughly ***,as summed in the overview of design methodologies,the multi-objective optimization transcends the single-objective *** potential of the hybrid propulsion system can be thoroughly evaluated in only one optimization run,if several objectives optimized *** there are few researches covering the conceptual design of hybrid aircraft using multi-objective *** review of the most popular energy management strategies discloses the third research gap—current methodologies favoured in hybrid ground vehicles do not consider the aircraft ***,both non-causal and causal energy management are needed for performing a complicated flight mission with several sub-tasks.

关键词： Aircraft Convex optimization Energy management Fuzzy logic control Hybrid electric propulsion system non-dominated sorting genetic algorithm Sizing

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：