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Stochastic energy management in a renewable energy-based microgrid considering demand response program

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 129卷 106791-106791页

作者： Hajiamoosha, Pouria Rastgou, Abdollah Bahramara, Salah Sadati, S. Muhammad Bagher Islamic Azad Univ Dept Elect Engn Kermanshah Branch Kermanshah Iran Islamic Azad Univ Dept Elect Engn Sanandaj Branch Sanandaj Iran

Climate changes increase concerns about global warming caused by greenhouse gases and have also increased the focus and implementation of renewable energy sources (RESs) planning. One of the important RESs is tidal energy or tidal power, which is a form of hydropower that converts the energy obtained from tides into the electrical power. Although tidal power is still not widely used, this energy resource has the potential for the future electricity generation. This paper addresses the stochastic energy management in a microgrid considering RESs such as solar, wind and tidal sources in the presence of the demand response program and storage devices. The uncertainty of the RESs, demand, and electricity price is handled by Monte Carlo simulation (MCS). The model is a linear multi-objective optimization which the first objective aims to reduce the cost and the second aims to reduce the emission. Augmented ?-constraint approach is applied to solve the problem in the CPLEX/ GAMS software environment. The interactive fuzzy decision-making is applied to choose the best answer among the Pareto answers according to the planner criteria.

关键词： multi-objective programming Tidal energy Renewable energy sources Augmented ?-constraint method Pollution emission

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Slotting Optimization of Distribution Center for Agriculture Products Considering ＂Freshness＂ under Traceable Cold Chain

World Scientific Research Journal

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World Scientific Research Journal 2021年第5期7卷 19-31页

作者： Haimei Zhang Weijiong Chen

With the rapid development of logistics, trade, and people's pursuit of health, the demand for fresh and safe fresh products is increasing, and logistics providers are facing great challenges. Distribution is an important part of fresh food delivery from the origin to the dining table, and its operation efficiency and service level are very important. Since the actual freshness of fresh products will be different due to the different operation conditions of different logistics links from the origin to the cold storage of distribution center, the purpose of this study is to explore the freshness evaluation method of fresh products, and to optimize the operation of the distribution center in the later stage by tracing the logistics operation information in the early stage. First of all, for a fresh product, the concentration of CO_2 in the closed environment at different temperatures was measured. The respiration rate was calculated, and then the freshness decline rate of fresh products at different temperatures was obtained. Secondly, the system flow chart of fresh products from picking, packaging, precooling, transportation, loading and unloading and handling is constructed, and the freshness is taken as the system reliability. Through the information traceability of the early temperature and operation time, the freshness rating of fresh products before warehousing is completed based on GO-FLOW method. Finally, taking the overall freshness, warehousing efficiency and shelf stability of cold storage as indicators, a multi-objective location optimization model is constructed, and the location allocation scheme is obtained through NSGA-II algorithm, which makes it more convenient for ＂perishable and perishable＂ fresh products and fresh products with high turnover rate. This paper provides a new idea for fresh product freshness rating and fresh product distribution center location optimization research, which is of great significance for improving fresh product freshnes

关键词： Freshness rating GO‐FLOW multi-objective programming Location optimization NSGA-II

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Eco-innovation analysis: A data envelopment analysis methodology

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ENVIRONMENTAL TECHNOLOGY & INNOVATION 2021年 23卷

作者： Arman, H. Jamshidi, A. Hadi-Vencheh, A. Islamic Azad Univ Najafabad Branch Dept Management Najafabad Iran Islamic Azad Univ Isfahan Khorasgan Branch Dept Math Esfahan Iran

The examination of financial development and environmental effect has driven inquiry into creating assessment models on environmental and economic changes, particularly on eco-innovation goods. Here, a new approach is proposed to find the common set of weights (CSWs) in data envelopment analysis (DEA) to examine the eco-innovation in the presence of undesirable factors. For this purpose, first, the current models are reviewed and criticized, and their shortcomings are clarified. Then, a simple way is proposed to find CSWs in DEA. We show the proposed approach leads to a better solution compared to current methods in the literature. Finally, the proposed model is applied to the eco-innovation analysis of OECD countries. Our findings show that the Czech Republic has the highest rank in eco-innovation. (C) 2021 Elsevier B.V. All rights reserved.

关键词： Data envelopment analysis (DEA) Common set of weights (CSW) Efficiency multi-objective programming Eco-innovation

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Hovering efficiency optimization of the ducted propeller with weight penalty taken into account

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AEROSPACE SCIENCE AND TECHNOLOGY 2021年 117卷 106937-106937页

作者： Hu, Yu Qing, Ji Xiang Liu, Zhong Huan Conrad, Zachary J. Cao, Jia Ning Zhang, Xue Peng Northwestern Polytech Univ Sch Aeronaut 127 You Yi Xi Lu Xian 710072 Shaanxi Peoples R China

The ducted propeller is superior to the open propeller in hovering efficiency. However, the overall system efficiency of a ducted propeller is reduced due to its heavy structure. If the weight penalty is taken into account, will the ducted propeller still be superior to an open propeller? And in this scenario, how will a ducted propeller with better efficiency than an open propeller be designed? This paper investigates these questions by parametric analysis based on experiments and then parametric optimization that involves hovering efficiency and structural weight in objective functions. Both multi-disciplinary design optimization and multi-objective programming are performed by surrogate-based optimization. An in-house automatic structured mesh generation module is developed to deal with significant geometry variation in design space. Finally, the optimization results are validated by post-optimization experiments. The results of experiment and optimization indicate that the effects of weight penalty play a leading role at low disk loading and hence in this case, the one with lighter structure is superior. But at high disk loading, as thrust gets higher, the leading factor turns into aerodynamic hovering efficiency, therefore the one with higher aerodynamic hovering efficiency prevails. The multi-objective optimization produces an L-shaped Pareto front, and the optimum of multi-disciplinary optimization is quite close to the Pareto front knee point. The designs in this region encounter limited aerodynamic hovering efficiency loss but gain significant weight reduction. Therefore, we can obtain a ducted propeller superior to an open propeller in system efficiency with pretty low disk loading, although the weight penalty is considered. These designs feature a relatively large inner lip radius, a small outer lip radius, and a short or even no diffuser. This means that the inner lip radius contributes the most to the aerodynamic hovering efficiency, followed by the dif

关键词： Ducted propeller Surrogate assisted optimization multi-objective programming multi-disciplinary optimization UAV

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A proposed method for third-party reverse logistics partner selection and order allocation in the cellphone industry

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COMPUTERS & INDUSTRIAL ENGINEERING 2021年 162卷

作者： Jauhar, Sunil Kumar Amin, Saman Hassanzadeh Zolfagharinia, Hossein Indian Inst Management Kashipur Operat Management & Decis Sci Kashipur India Ryerson Univ Ted Rogers Sch Management 575 Bay St Toronto ON Canada Ryerson Univ Dept Mech & Ind Engn Toronto ON Canada Indian Inst Management Kashipur India Ryerson Univ Toronto ON Canada

There are growing social and government pressures that encourage end of life (EOL) electronic products companies to focus on reverse logistics (RL) and recovery options. The complexity of RL elements for EOL electronic products is a challenge in this field. Recently, original equipment manufacturers (OEMs) have focused on RL activities. To this aim, third-party reverse logistics partners (3PRLPs) play an important role. This paper simultaneously draws attention to the selection of 3PRLPs and determine how orders are assigned to every 3PRLP using a new framework. There are two phases in this framework. The first phase includes an approach that integrates data envelopment analysis (DEA) with a differential evolution (DE) algorithm to increase the discriminatory power and distinguish the 3PRLPs based on their efficiencies. DEA is considered in this study because it is an effective method to determine the efficiency based on the simultaneous analysis of inputs and outputs. In Phase 2, those efficiency scores are utilized to allocate orders to 3PRLPs using a multi-objective model. Two solution approaches are employed for solving the proposed multi-objective model and to find Pareto-optimal solutions. The application of the models is shown in Canada's cellphone industry. The results reveal that the efficiency of 3PRLPs may have an effect on both third-party reverse logistics partner selection and the orders allocated to them.

关键词： Third-party reverse logistics partners (3PRLPs) Data envelopment analysis (DEA) multi-objective programming Reverse logistics (RL)

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Air traffic management in parallel-point merge systems under wind uncertainties

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JOURNAL OF AIR TRANSPORT MANAGEMENT 2022年第0期104卷

作者： Donmez, Kadir Cetek, Cem Kaya, Onur Eskisehir Tech Univ Dept Air Traff Control Eskisehir Turkey Eskisehir Tech Univ Dept Ind Engn Eskisehir Turkey

The point merge system (PMS) was developed by EUROCONTROL in 2006 to enable controllers to implement systematic sequences and replace the traditional vector technique in Terminal Maneuver Area (TMA) even during peak hours. A conventional PMS includes two arc-shaped route segments referred to as sequencing legs and a single merge point to merge arrivals. When necessary, arrivals can be delayed along these legs using path stretching before they are directed to the merge point. After merging, aircraft join the final approach. The parallel-point merge system (P-PMS), however, has a more complex route structure which consists of two oppositely located PMS and a set of common points located between the merge points and final paths of runways. This system increases the capacity of the airspace and provides the advantages of the single PMS. However, especially in simulation studies where P-PMS has been tested, the emphasis on wind sensitivity came to the fore as one of the main issues affecting the use of the system. The use of P-PMS was stated as feasible but more difficult due to the loss of symmetry, especially when the wind is perpendicular to the sequencing legs. Controllers may need help in providing safe and efficient sequences in this type of structure. In this study, a multi-objective two-stage stochastic programming model is developed for P-PMS to obtain robust aircraft sequences, schedules, and runway assignments considering the uncertainties of both wind direction and speed. The model was implemented on the existing layout of Istanbul Airport having a P-PMS serving five parallel runways using the real traffic and wind data. A scenario-based approach was adopted to represent the uncertainties of the model. Also, to meet the demands of the various stakeholders in the air traffic system, the minimization of total fuel consumption, total flight time, and total delays were considered as single and multi-objectives. As a result, it was found that the stochastic approa

关键词： Air traffic management Stochastic programming multi-objective programming Parallel-point merge system Wind uncertainties

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Joint simulation through orthogonal factors generated by the L-SHADE optimization method

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SPATIAL STATISTICS 2021年 43卷 100521-100521页

作者： Sohrabian, Babak Soltani-Mohammadi, Saeed Bakhtavar, Ezzeddin Taherinia, Arash Urmia Univ Technol Fac Environm Dept Min Engn Orumiyeh Iran Univ Kashan Dept Min Engn Ravand St Kashan Iran Natl Iranian Copper Ind Co Miduk Copper Complex Kerman Iran

Due to its better results over the traditional co-simulation methods, joint simulation of variables through orthogonal factors has gained popularity. In this approach, practitioners transform variables into orthogonal factors, simulate them independently, and back-transform the results into the initial space. It is unlikely to generate spatially uncorrelated factors at more than two lags. Therefore, the idea of simultaneous diagonalization has become the topic of so many studies. Some approaches have used the Jacobi transformation to replace a multivariate minimization problem with a sequence of univariate problems. However, these studies do not pay attention to the interruption of the previously minimized univariate problems while solving the new one. Therefore, this study aimed to minimize the objective function by considering all the univariate problems at once using the L-SHADE optimization method. The proposed method was applied to the Meiduk porphyry copper deposit to generate the L-SHADE factors. L-SHADE was efficient due to high speed of convergence and giving logical answer. Comparison among the L-SHADE factors and those of principal component analysis and Min/max autocorrelation factors showed better performance of the L-SHADE method such that the cross-variograms of the L-SHADE factors did not show noticeable spatial pattern and generally had smaller values. Sequential simulation was used to produce fifty equiprobable realizations from the L-SHADE factors. The proposed approach could reproduce the means, variances, correlation coefficients, cumulative distributions, and auto/cross-variograms of the variables in the simulations. Therefore, the simulations were reliable to be used in long-term production planning. A weighted multi-objective model using binary integer variables was developed to find the best possible production plan among different production scheduling alternatives developed based on the simulations. Different weighting scenarios were consi

关键词： L-SHADE optimization algorithm Cross-variogram Joint simulation multi-objective programming Long-term production planning

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Research on hybrid feature selection method of power transformer based on fuzzy information entropy

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ADVANCED ENGINEERING INFORMATICS 2021年 50卷

作者： Yu, Song Tan, Weimin Zhang, Chengming Fang, Yun Tang, Chao Hu, Dong Southwest Univ Coll Engn & Technol Chongqing 400715 Peoples R China Southwest Univ Int R&D Ctr New Technol Smart Grid & Equipment Chongqing 400715 Peoples R China

The data of dissolved gas in oil analysis (DGA) is uncertain affected by the influence of transformer capacity and fault location, which makes transformer fault diagnosis model based on DGA has low accuracy. Therefore, we propose a hybrid feature selection method based on fuzzy information entropy, whereby optimizing the reasonable DGA feature parameter according to the feature information between the parameter and fault type, to reduce the influence of DGA data uncertainty on the fault diagnosis accuracy. Firstly, the characteristic relevance and redundancy functions are constructed based on fuzzy information entropy theory. Secondly, these functions are taken as the optimization objectives of binary-chaotic multi-objective particle swarm optimization algorithm (B-CMOPSO), to search for the feature subsets in the feature space composed of 46 DGA feature parameters. Then, the optimal feature subset is selected based on the simulation accuracy of ELM, SVM, Adaboost.M1 and BPNN on the feature subsets. Finally, 30 simulation experiments are carried out to compare with several multiobjective optimization algorithms, common Filter methods and common DGA feature combinations, and the rationality of the proposed method is verified by the t-test method. The results show that the 4 classifiers accuracy means is maximatily improved by 18.95%, 20.77%, 19.85% and 21.27% respectively compared with common DGA feature combinations, indicating that the optimal feature subset preserves more feature information and can effectively reduce the influence of DGA data uncertainty on diagnostic accuracy.

关键词： Power transformer DGA Feature selection multi-objective programming Fuzzy information entropy

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A priority-based multi-objective framework for water resources diversion and allocation in the middle route of the South-to-North Water Diversion Project

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SOCIO-ECONOMIC PLANNING SCIENCES 2021年 78卷

作者： Zhao, Siwei Liu, Weidong Zhu, Mengyuan Ma, Yanfang Li, Zongmin Sichuan Agr Univ Coll Landscape Architecture Chengdu 611130 Peoples R China Sichuan Univ Business Sch Chengdu 610064 Peoples R China Hebei Univ Technol Sch Econ & Management Tianjin 300401 Peoples R China

Because of the degradation of the social-ecological-economic-environmental (SEEE) system, water scarcity has been a growing source of conflicts over the globe. Further, the uncertainty arising from complex water resource scenarios increases the conflicts between the different water users and destabilizes water allocation systems. In this study, a priority-based multi-objective programming (MOP) model (quantitative path) with fuzzy random variables (FRVs) is established for a water resource diversion and allocation (WRDA) problem. To determine the priorities of the multiple objectives, a priority-determination approach (qualitative path) is designed, comprising of a pressure-state-response (PSR) multiple attribute assessment system and a technique for order preference by similarity to an ideal solution (TOPSIS)-based evaluation method. Then the MOP model is transformed into a solvable goal programming (GP)-based model. Because of the inclusion of FRVs, the obtained results can be adjusted to local conditions in view of social, economic, environmental and ecological objective priorities. Therefore, they are more applicable than traditional weight sum or Pareto multi-objective WRDA methodologies. A case study from the middle route of the South-to-North Water Diversion Project (SNWDP-MRP) in China is given to demonstrate the practicability and rationality of the proposed methodology in obtaining scientific WRDA plans.

关键词： Fuzzy random variable multi-objective programming Priority Water resources diversion and allocation

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Optimization of Electronic Waste Recycling Network Designing 5

Optimization of Electronic Waste Recycling Network Designing

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5th International Conference on Electromechanical Control Technology and Transportation (ICECTT)

作者： Wang, Bin Li, Hehua Shanghai Polytech Univ Coll Int Vocat Educ Shanghai Peoples R China Shanghai Polytech Univ Sch Econ & Management Shanghai Peoples R China

ISBN: (数字)9781728199283

ISBN: (纸本)9781728199283

Reverse logistics is an important part of a low-carbon economy. Electronic waste recycling logistics network design plays an important role in reverse logistics management. In this paper, a multi-objective planning is used to establish a network model of electronic waste recycling. The objective function is to minimize operating costs and maximize customer service levels. The decision variables include the setting of nodes in the recycling network and the amount of transportation between the nodes of the network. Constraints include meeting customer needs and balancing the inflow and outflow of nodes. The multi-objective programming is transformed into a single-objective programming by epsilon-constraint. The numerical example shows that the two objects can be consistent within a certain range, so that the electronic waste logistics enterprise can achieve the goals of simultaneously reducing costs and improving customer service levels.

关键词： supply chain logistics reverse logistics multi-objective programming epsilon-constraint

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