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The impact of supply chain disruption on the closed-loop supply chain configuration profit: a study of sourcing policies

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第17期58卷 5380-5400页

作者： Gaur, Jighyasu Amini, Mehdi Rao, Arza Keshava TA Pai Management Inst Manipal Karnataka India Univ Memphis Fogelman Coll Business & Econ Dept Mkt & Supply Chain Management Memphis TN 38152 USA ICFAI Business Sch IBS Hyderabad Operat & IT Hyderabad Telangana India

A closed-loop supply chain configuration (CLSCC) encompasses the decisions related to the optimal selection of options at each stage of a closed-loop supply chain (CLSC) for the introduction and reconstruction of new products. The extant literature ignores the impact of supply chain disruptions on CLSCC. An attempt is made to fill this gap in this study. Thus, an integrated multi-sourcing CLSCC optimisation model for new and reconstructed products is developed. The optimisation model presented is a mixed-integer nonlinear programming (MINLP) model. Based on a real-world case study of an auto-parts manufacturer in India presented, a comprehensive set of computational experiments, scenario analyses are conducted. The key finding/observation that resulted from our computational experiments is that multi-sourcing generates higher net present value of total profit compared to single sourcing under the risk of supply chain disruption. Several other observations and managerial insights are drawn from computational experiments, and scenario analyses. Firms interested in configuring their CLSC under the risk of supply chain disruption may use the study's outcomes to understand the profit impact of various CLSCC parameters, individually and in combination.

关键词： supply chain management closed-loop supply chain uncertainty nonlinear programming modelling

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Resilience-based tri-level framework for simultaneous transmission and substation expansion planning considering extreme weather-related events

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第16期14卷 3310-3321页

作者： Shivaie, Mojtaba Kiani-Moghaddam, Mohammad Weinsier, Philip D. Shahrood Univ Technol Fac Elect Engn & Robot Shahrood Iran Shahid Beheshti Univ Dept Elect Engn Tehran Iran Bowling Green State Univ Firelands Dept Appl Elect Engn Huron OH USA

In this study, a new resilience-based framework is presented for multi-period simultaneous transmission and substation expansion planning (ST&SEP) considering extreme weather-related events (EWEs). The formation of the proposed planning framework falls into a tri-level optimisation problem with the aim of strengthening power network resilience in response to the EWEs. In the lower-level problem, short-term remedial corrective strategies of the independent system operator (ISO) after the EWEs are determined by applying network reconfiguration and generation redispatch. In the intermediate-level problem, an enhanced scenario-building approach is developed to model and analyse the EWEs, as non-random uncertain events, and their subsequent detrimental effects using the notion of the fragility curves corresponding to power network components. In the upper-level problem, however, long-term remedial preventive strategies of the ISO, as network planner, after the EWEs are obtained through integrated decisions between multi-period ST&SEP and transmission switching equipment planning. The newly proposed planning framework is formulated as a large-scale mixed-integer non-linear tri-level optimisation problem and is solved by a powerful symphony orchestra search algorithm in order to obtain the final optimal solution. The proposed planning framework is examined on the real-world large-scale Iranian 400-kV power transmission network and its profitableness is assured by thorough simulation studies.

关键词： integer programming nonlinear programming substations power transmission planning power generation dispatch search problems transmission switching equipment placement symphony orchestra search algorithm resilience-based tri-level framework substation expansion planning extreme weather-related events EWE power network resilience short-term remedial corrective strategies independent system operator ISO network reconfiguration generation redispatch enhanced scenario generation approach long-term remedial preventive strategies network planner mixed-integer nonlinear tri-level optimisation problem Iranian power transmission network

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Optimal Planning Method of Distributed Photovoltaic Access Distribution Network Based on Power Data 6

Optimal Planning Method of Distributed Photovoltaic Access D...

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6th International Conference on Power and Renewable Energy, ICPRE 2021

作者： Su, Xinyong Gong, Xiaoxu Miao, Chunyu Wu, Hongwei Zhang, Yong Sa, Bowen State Grid Chifeng Power Supply Company 024000 China Tsinghua Sichuan Energy Internet Research Institute Sichuan Chengdu610213 China

ISBN: (纸本)9781665449618

In order to analyze the capacity of distributed photovoltaic access to rural 10kV overhead lines and reasonably determine the credible capacity of distributed photovoltaic access distribution transformers, based on the analysis of typical access modes and voltage deviation analysis, for radial overhead power grids, the nodes voltage deviation, the rated capacity of the line and the distribution transformer are constraints, and based on the topological relationship of the radial network, the correlation matrix of nodes and branches is constructed, and the method of solving the node voltage is optimized by applying matrix. Construct a distributed photovoltaic consumption capacity analysis model based on feeder distribution, and solve the model by particle swarm optimization algorithm for solving nonlinear programming problems. Finally, for typical calculation examples, the distributed photovoltaic capacity of each node is calculated. The results show that the model and method can assist the calculation of distributed photovoltaic consumption capacity based on feeder distribution, and provide planning guidance and construction reference for distributed photovoltaic access via overhead lines. © 2021 IEEE.

关键词： nonlinear programming

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Probabilistic decomposition-based security constrained transmission expansion planning incorporating distributed series reactor

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第17期14卷 3478-3487页

作者： Yuan, Zhi Wang, Weiqing Wang, Haiyun Ghadimi, Noradin Xinjiang Univ Engn Res Ctr Renewable Energy Power Generat & Gri Minist Educ Urumqi 830047 Xinjiang Peoples R China Islamic Azad Univ Ardabil Branch Young Researchers & Elite Club Ardebil Iran

This study presents a probabilistic transmission expansion planning model incorporating distributed series reactors, which are aimed at improving network flexibility. Although the whole problem is a mixed-integer non-linear programming problem, this study proposes an approximation method to linearise it in the structure of the Benders decomposition (BD) algorithm. In the first stage of the BD algorithm, optimal number of new transmission lines and distributed series reactors are determined. In the second stage, the developed optimal power flow problem, as a linear sub-problem, is performed for different scenarios of uncertainties and a set of probable contingencies. The Benders cuts are iteratively added to the first stage problem to decrease the optimality gap below a given threshold. The proposed model utilises the Monte Carlo simulation method to take into account uncertainty of wind generations and demands. Several case studies on three test systems are presented to validate the efficacy of the proposed approach.

关键词： power transmission planning power system security linear programming load flow Monte Carlo methods probability power generation planning integer programming power transmission reliability nonlinear programming BD algorithm optimal number transmission lines distributed series reactors developed optimal power flow problem linear sub-problem stage problem optimality gap probabilistic decomposition-based security transmission expansion planning incorporating distributed series reactor probabilistic transmission expansion planning model network flexibility mixed-integer nonlinear programming problem approximation method Benders decomposition algorithm

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Research on Preparation of C4 Olefins Based on Multiple Regression Analysis and Genetic Algorithm Optimization

Research on Preparation of C4 Olefins Based on Multiple Regr...

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2021 IEEE Conference on Telecommunications, Optics and Computer Science, TOCS 2021

作者： Xiaokang, Li Xin, Tang Yukun, Yuan Shanghai Ocean University School of Engineering Shanghai201306 China Shanghai Ocean University School of Information Shanghai201306 China Shanghai Ocean University School of Economics and Management Shanghai201306 China

ISBN: (纸本)9781665424981

In this paper, aiming at the process of preparing C4 olefins from ethanol through coupling reaction, a multi-objective optimization model is established with the goal of C4 olefin yield, and the system parameters such as catalyst combination mode and temperature are searched and solved. Firstly, it is found that there is a certain relationship between ethanol conversion, C4 olefin selectivity and temperature change, and multiple functions are used for regression analysis. Taking catalyst A1 as an example, the best regression model between ethanol conversion and temperature is y1 = 0.003x2 - 1.193x + 141.807. The best regression model between C4 olefin selectivity and temperature is y2 = 0.001x2 - 0.681x + 88.406. Ethylene selectivity time optimal model: y3 = - 8.936e - 05x2 + 0.030x + 2.252. Then, the influence model of ethanol conversion rate is established, the model is solved by the least square method, and the genetic algorithm is used to optimize the model. The optimal model of ethanol conversion rate is:w1 = 83.9812pethanol + 0.9895t + 0.4925βCo/Sio2 - 84.2251. The optimal model of C4 olefin absorption is: w2 = -2.2047λco + 0.6778t + 0.5841βCo/Sio2 - 44.4423. © 2021 IEEE.

关键词： nonlinear programming

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Modified Non-Linear programming Methodology for Multi-Attribute Decision-Making Problem with Interval-Valued Intuitionistic Fuzzy Soft Sets Information 2

Modified Non-Linear Programming Methodology for Multi-Attrib...

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2nd Global Conference for Advancement in Technology, GCAT 2021

作者： Singh, Akanksha Chandigarh University Department of Mathematics - Uis Punjab India

ISBN: (纸本)9780738132150

The presented work is an extensive study of the existing non-linear programming (NLP) methods in an uncertain environment of an interval-valued intuitionistic fuzzy soft set (IVIFSS) for solving multi-attribute decision-making (MADM) problems. IVIFSS is an intriguing extension of a fuzzy set (FS) involving both interval-valued intuitionistic fuzzy set (IVIFS) (which considers interval-value of both membership and non-membership elements of an intuitionistic fuzzy set (IFS)) and soft set (SS) (which gives importance to each parameter in an alternative). A comprehensive study projects that the existing NLP method in accordance with the technique for order preference by similarity to ideal solution (TOPSIS) for solving interval-valued intuitionistic fuzzy soft multi-attribute decision-making (IVIFSMADM) problems (decision-making (DM) problems in which assessment of rating of each alternative, over each character is rendered by an IVIFSS) is posing some limitations due to some mathematical incorrect assumptions and hence incorporating ambiguous results in real-life applications. Henceforth, an attempt has been made to properly understand the root cause of the posed shortcoming and suggested a new NLP method for solving IVIFSMADM problems, and also to validate this proposed NLP method a real-life problem is solved successfully. © 2021 IEEE.

关键词： nonlinear programming

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Selection of building thermal insulation materials using robust optimization

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INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT 2020年第3期25卷 443-455页

作者： Sun, Menghua Haskell, William B. Ng, Tsan Sheng Ee, Alvin W. L. Kua, Harn Wei Natl Univ Singapore Dept Ind Syst Engn & Management 1 Engn Dr 2 Singapore Singapore Natl Univ Singapore Environm Res Inst 1 Create Way Singapore Singapore Natl Univ Singapore Sch Design & Environm 4 Architecture Dr Singapore Singapore

Purpose Life cycle assessment (LCA) is commonly used to analyze the environmental profile of a material and product. For example, the selection of building insulation is crucial to ensure that energy and financial conservation goals can be met. Most of the current methods used in material selection are deterministic in nature, which ignores or neglects the effects caused by uncertainties present in various factors, including how the thermal insulation properties of insulation may change with time. In addition, during the use phase, uncertainty in operating conditions may also affect the performance of the selected material, affecting the overall environmental and economic performance. In practice, when material usage is in large quantities, uncertainty may have significant impacts. This article proposes a novel optimization model-based approach in selecting suitable building insulations using LCA results and economic consideration together with its uncertainties. Methods This work presents an optimization-based approach to select building thermal insulation materials in the presence of data uncertainties. Firstly, we developed a deterministic model, incorporating life cycle assessment and costing to evaluate various environmental impacts and costs of the different materials. Next, by considering the different uncertainties in the data used for the environmental and cost assessments, a robust optimization approach is proposed to derive the second model. A novel solution algorithm is then developed to obtain model solutions efficiently. Results and discussion Computational studies based on a high-rise apartment in Shanghai were performed to test the applicability and performance of the proposed solution. The results demonstrate that the proposed robust optimization model is effective in mitigating the data uncertainties in the material selection optimization and outperforms the deterministic model significantly in terms of probability of achieving cost and environment

关键词： Building energy consumption Life cycle assessment nonlinear programming Robust optimization Thermal insulation design

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Prediction Based Vehicular Caching: Where and What to Cache?

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MOBILE NETWORKS & APPLICATIONS 2020年第2期25卷 760-771页

作者： Zhang, Yao Li, Changle Luan, Tom H. Fu, Yuchuan Wang, Hui Xidian Univ Xian Shaanxi Peoples R China

The explosive growth of user demands for mobile data puts forward higher requirements for existing network architecture. In this case, many novel technologies, such as edge computing, ultra-dense network (UND), are recently proposed to alleviate the network burden of cellular macro base stations (MBSs). However, their performance is limited by dynamic user requests and uncertain user mobility since they highly rely on the fixed infrastructure. Along with the advent of autonomous driving era, autonomous vehicles possess strong computing and communication ability, which provide a new idea to resolve the limitation of infrastructure based network architecture. In this paper, we exploit the performance of a vehicular caching scheme where the role of moving vehicles is changed from service consumers in traditional networks to service providers and service consumers. As such, a prediction based vehicular caching scheme is proposed. Specifically, an optimization problem is firstly formulated by exploring the relationship of caching vehicles and mobile users, in order to optimize the network energy efficiency. The nonconvex optimization problem is solved by decomposing it into a nonlinear programming problem. By applying the Lyapunov method and autoregressive neural network (ANN), an online caching decision algorithm is finally proposed to make caching decisions. Extensive simulations are conducted to evaluate the caching scheme in different scenarios. Results show that the vehicular caching scheme can obviously improve network energy efficiency with different requests, but the increment is reduced under the scenario of intensive requests. The comparison between online and offline caching also shows the necessity of online caching decision making due to its benefit in resource utilization where system gain is increased from 8.4% to 59.24%.

关键词： Edge caching nonlinear programming Lyapunov optimization Neural network

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A full mixed-integer linear programming formulation for economic dispatch with valve-point effects, transmission loss and prohibited operating zones

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ELECTRIC POWER SYSTEMS RESEARCH 2020年第0期180卷 106061-000页

作者： Pan, Shanshan Jian, Jinbao Chen, Huangyue Yang, Linfeng Guangxi Univ Sci & Technol Sch Sci Liuzhou 545006 Peoples R China Guangxi Univ Nationalities Coll Sci Nanning 530006 Peoples R China Beijing Jiaotong Univ Dept Appl Math Beijing 100044 Peoples R China Guangxi Univ Guangxi Key Lab Multimedia Commun & Network Techn Nanning 530004 Peoples R China

The economic dispatch (ED) problem considering valve-point effects (VPE), transmission loss and prohibited operating zones (POZ) is a very challenging issue due to its intrinsic nonconvex, nonsmooth and noncontinuous nature. To achieve a nearly global solution, a full mixed-integer linear programming (FMILP) formulation is proposed. Since the original loss function is highly coupled on N-dimensional space, it is usually hard to linearize entirely. To handle this difficulty, a reformulation trick is utilized, transforming the problem into a group of tractable quadratic constraints. By taking full advantage of the variable coupling relationships and applying a logarithmic size formulation technique, an FMILP formulation that requires as few binary variables and constraints as possible is consequently constructed. When the POZ restrictions are also considered, a distance-based technique is adopted, reconstructing them compatible with the previous FMILP formulation. By solving such an FMILP formulation, a nearly global solution is thus efficiently obtained. To search for a better solution, a nonlinear programming (NLP) model for the ED will be given and solved based on the FMILP solution. The case study results show that the presented FMILP formulation is very effective in solving the ED problem that involves nonconvex, nonsmooth and noncontinuous features.

关键词： Economic dispatch Nonconvex Nonsmooth Noncontinuous Full mixed-integer linear programming nonlinear programming

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An integrated energy system scheduling optimization method considering economy, stability and environmental protection

An integrated energy system scheduling optimization method c...

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2021 International Conference on Electrical, Electronics and Computing Technology, EECT 2021

作者： Lou, Qinghui Chen, Jun Niu, Honghai Qiu, Rui Wu, Jun Gao, Yuan Ma, Xiangzhui Guan, Xiaocheng Ouyang, Jun Nanjing NARI-Relays Engineering Co. Ltd Nanjing210000 China School of Electrical Engineering and Automation Wuhan University Wuhan430000 China Co. LTD Tianjin Branch Tianjin300000 China

In this paper, first, an energy efficiency evaluation method including economy, stability and environmental protection was given. Second, a mathematical model of the integrated energy system and a single-objective economic optimization model under different operation conditions, which add renewable energy and power storage equipment and could be solved based on the greedy algorithm, were given to improve the energy efficiency. Finally, an integrated energy system including wind power, photovoltaics, power storage equipment and conventional loads was taken as an example. Considering the time-of-use electricity price and the full utilization of energy storage, 4 optimization plans were set up for comprehensive energy efficiency evaluation and comparison. The result shows that the energy efficiency evaluation method proposed in this paper is practical and feasible, and the optimization method proposed plays a guiding role in the operation of similar parks. © Published under licence by IOP Publishing Ltd.

关键词： nonlinear programming

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