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Multi-source coordinated stochastic restoration for SOP in distribution networks with a two-stage algorithm

Global Energy Interconnection 2023年第2期6卷 141-153页

作者： Xianxu Huo Pan Zhang Tao Zhang Shiting Sun Zhanyi Li Lei Dong Electric Power Research Institute of State Grid Tianjin Electric Power Company Tianjin 300384P.R.China School of Electrical and Electronics Engineering North China Electric Power UniversityBeijing 102206P.R.China State Grid Tianjin Baodi Electric Power Supply Company Tianjin 301800P.R.China

After suffering from a grid blackout, distributed energy resources(DERs), such as local renewable energy and controllable distributed generators and energy storage can be used to restore loads enhancing the system’s resilience. In this study, a multi-source coordinated load restoration strategy was investigated for a distribution network with soft open points(SOPs). Here, the flexible regulation ability of the SOPs is fully utilized to improve the load restoration level while mitigating voltage deviations. Owing to the uncertainty, a scenario-based stochastic optimization approach was employed,and the load restoration problem was formulated as a mixed-integer nonlinear programming model. A computationally efficient solution algorithm was developed for the model using convex relaxation and linearization methods. The algorithm is organized into a two-stage structure, in which the energy storage system is dispatched in the first stage by solving a relaxed convex problem. In the second stage, an integer programming problem is calculated to acquire the outputs of both SOPs and power resources. A numerical test was conducted on both IEEE 33-bus and IEEE 123-bus systems to validate the effectiveness of the proposed strategy.

关键词： Load restoration Soft open points Distribution network Stochastic optimization two-stage algorithm

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Signal adaptive cooperative control of two adjacent traffic intersections using a two-stage algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2021年 174卷 114746-114746页

作者： Zou, Yuanyang Liu, Renhuai Li, Ya Ma, Yingshuang Wang, Guoxin Hubei Univ Econ Sch Business Adm Wuhan 430205 Peoples R China Shanghai Univ Sch Management Shanghai 200444 Peoples R China Huanggang Normal Univ Business Coll Huanggang 43800 Hubei Peoples R China Nanyang Inst Technol Sch Math & Phys Nanyang 473004 Peoples R China

It is obvious that the traffic light plans of two intersections interact with each other, and the key problem for the system adjacent intersections is how to calculate of the arrival rates of the connection lanes of each phase. To treat the interaction of the two intersections, in this paper, the transition probabilities of the connection lanes of intersections 1 and 2 are introduced, which are utilized to compute the arrival rates of the connection lanes. In addition, since the green times of connection lanes interact with each other, a corresponding model of the phases of the connection lanes is proposed, which is employed to search for the optimal phase of the connection lanes. Moreover, the traffic time of the vehicles on the connection lanes is considered in the corresponding model. hen, an optimization model of the traffic signal of the two adjacent intersections is constructed. To solve the model, a novel two-stage algorithm is proposed. The first stage matches the arrival rates and the phase of the connection lanes of the two adjacent intersections. The second stage optimizes the model. Four numerical experiments are utilized to test the model and algorithm, and three other algorithms are chosen for comparison with our algorithm. The results of the numerical experiments demonstrate that the model and the algorithm are effective and that the model and algorithm can find more reasonable plans for the plans of two adjacent intersections.

关键词： two adjacent intersections Adaptive cooperative control Traffic signal control Transition probabilities two-stage algorithm

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A lexicographic-based two-stage algorithm for vehicle routing problem with simultaneous pickup-delivery and time window

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2020年 95卷 103901-103901页

作者： Shi, Yong Zhou, Yanjie Boudouh, Toufik Grunder, Olivier Univ Paris Saclay INRAE UMR SADAPT 16 Rue Claude Bertand F-75005 Paris France Univ Bourgogne Franche Comte Nanomed Lab UTBM Rue Mieg F-90010 Belfort France Pusan Natl Univ Dept Ind Engn Busan 46241 South Korea Univ Bourgogne Franche Comte UTBM CNRS ICB UMR 6303 Rue Leupe F-90400 Sevenans France

Vehicle routing problem with simultaneous pickup-delivery and time window (VRPSPDTW) is computationally challenging as it generalizes the classical and NP-hard vehicle routing problem. According to the state-of-the-art, VRPSPDTW usually has two hierarchical optimization objectives: a primary objective of minimizing the number of vehicles (NV) and a secondary objective of reducing the transportation distance (TD). Given the existing research and our trial results, we find that the optimization of TD is not necessarily a promotion for reducing NV. In this paper, an effective learning-based two-stage algorithm, which has never been studied before, is proposed to solve the VRPSPDTW. In the first stage, a modified variable neighborhood search with a learning-based objective function is proposed to minimize the primary objective with retaining the potential structures. In the second stage, a bi-structure based tabu search (BSTS) is designed to optimize the primary and secondary objectives further. The experimental results on 93 benchmark instances demonstrate that the proposed algorithm performs remarkably well both in terms of computational efficiency and solution quality. In particular, the proposed two-stage algorithm improve several best known solutions (either a better NV or a better TD when NV are the same) from the state-of-the-art. To our knowledge, this is the first learning-based two-stage algorithm for solving VRPSPDTW reaching such a performance. Finally, we empirically analyze several critical components of the algorithm to highlight their impacts on the performance of the proposed algorithm.

关键词： Simultaneous pickup-delivery problem Time window Tabu search Variable neighborhood search Vehicle routing problem two-stage algorithm Learning-based approach

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Optimality analysis of the two-stage algorithm for Hammerstein system identification

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IFAC Proceedings Volumes 2009年第10期42卷 320-325页

作者： Jiandong Wang Qinghua Zhang Lennart Ljung College of Engineering Peking University Beijing China 100871 INRIA Campus de Beaulieu 35042 Rennes Cedex France Dept. of Electrical Eng. SE-581 83 Linköping University Sweden Telephone: +33(2)9984-7463 Fax: +33(2)9984-7171

The two-stage algorithm (TSA) has been extensively used and adapted for the identification of Hammerstein systems. It is essentially based on a particular formulation of Hammerstein systems in the form of bilinearly parameterized linear regressions. This paper has been motivated by a somewhat contradictory fact: though the optimality of the TSA has been established by Bai in 1998 only in the case of some special weighting matrices, the unweighted TSA is usually used in practice. It is shown in this paper that the unweighted TSA indeed gives the optimal solution of the weighted nonlinear least-squares problem formulated with a particular weighting matrix. This provides a theoretical justification of the unweighted TSA, and leads to a generalization of the obtained result to the case of colored noise with noise whitening. Numerical examples of identification of Hammerstein systems are presented to validate the theoretical analysis.

关键词： System identification Hammerstein system two-stage algorithm

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A Novel two-stage algorithm of Fuzzy C-Means Clustering

A Novel Two-stage Algorithm of Fuzzy C-Means Clustering

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2010 International Conference on Computer,Mechatronics, Control and Electronic Engineering (CMCE 2010)

作者： Shanhong ZHENG Computer Science and Technology College JiLin University Computer Science and Engineering College ChangChun University of Technology ChangChun,China Chunguang ZHOU Computer Science and Technology College JiLin University ChangChun,China Guixia LIU Computer Science and Technology College JiLin University ChangChun,China Wanlong LI Computer Science and Engineering College ChangChun University of Technology ChangChun,China

Fuzzy C-Means is one of the clustering algorithms based on optimizing an objective *** selection of the initial parameters of the number and the initial cluster centers play an important influence in the performance of the *** paper proposes a new FCM clustering algorithm with two *** proposed algorithm not only resolves the problem of the initial choice of the cluster center effectively,but also decreases the time when clustering large volume of *** computer simulation results show the effectivity and the superiority of the new algorithm.

关键词： Fuzzy C-Means clustering algorithm initial cluster center two-stage algorithm

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Convergence of a two-stage Proximal algorithm for the Equilibrium Problem in Hadamard Spaces

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CYBERNETICS AND SYSTEMS ANALYSIS 2020年第5期56卷 784-792页

作者： Vedel, Ya. I. Sandrakov, G. V. Semenov, V. V. Chabak, L. M. Taras Shevchenko Natl Univ Kyiv Kiev Ukraine State Univ Infrastruct Technol Kiev Ukraine

An iterative two-stage proximal algorithm for approximate solution of equilibrium problems in Hadamard spaces is considered. This algorithm is an analog of the already studied two-stage algorithm for equilibrium problems in a Hilbert space. For Lipschitz-type pseudo-monotone bifunctions, a theorem on the weak convergence of sequences generated by the algorithm is proved.

关键词： Hadamard space equilibrium problem pseudo-monotonicity two-stage algorithm convergence

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A two-stage metaheuristic algorithm for the dynamic vehicle routing problem in Industry 4.0 approach

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Journal of Management Analytics 2021年第1期8卷 69-83页

作者： Maryam Abdirad Krishna Krishnan Deepak Gupta Department of Industrial Systemsand Manufacturing EngineeringWichita State UniversityWichitaKSUSA

Industry 4.0 is a concept that assists companies in developing a modern supply chain(MSC)system when they are faced with a dynamic *** Industry 4.0 focuses on mobility and real-time integration,it is a good framework for a dynamic vehicle routing problem(DVRP).This research works on *** aim of this research is to minimize transportation cost without exceeding the capacity constraint of each vehicle while serving customer demands from a common ***,new orders arrive at a specific time into the system while the vehicles are executing the delivery of existing *** paper presents a two-stage hybrid algorithm for solving the *** the first stage,construction algorithms are applied to develop the initial *** the second stage,improvement algorithms are *** results were designed for different sizes of *** results show the effectiveness of the proposed algorithm.

关键词： dynamic vehicle routing problem Industry 4.0 two-stage algorithm heuristic algorithms

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A Novel two-stage algorithm of Fuzzy C-Means Clustering

A Novel Two-stage Algorithm of Fuzzy C-Means Clustering

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2010 International Conference on Computer,Mechatronics,Control and Electronic Engineering(2010计算机、机电、控制与电子工程国际会议 CMCE 2010)

作者： Shanhong ZHENG Chunguang ZHOU Guixia LIU Wanlong LI Computer Science and Technology College JiLin University Computer Science and Engineering College Ch Computer Science and Technology College JiLin University ChangChun China Computer Science and Engineering College ChangChun University of Technology ChangChun China

Fuzzy C-Means is one of the clustering algorithms based on optimizing an objective function. The selection of the initial parameters of the number and the initial cluster centers play an important influence in the performance of the FCM. This paper proposes a new FCM clustering algorithm with two stages. The proposed algorithm not only resolves the problem of the initial choice of the cluster center effectively, but also decreases the time when clustering large volume of data. The computer simulation results show the effectivity and the superiority of the new algorithm.

关键词： Fuzzy C-Means clustering algorithm initial cluster center two-stage algorithm

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A Pareto-based two-stage evolutionary algorithm for flexible job shop scheduling problem with worker cooperation flexibility

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2023年第1期82卷

作者： Luo, Qiang Deng, Qianwang Xie, Guanhua Gong, Guiliang Hunan Univ State Key Lab Adv Design & Mfg Vehicle Body Changsha 410082 Peoples R China Cent South Univ Forestry & Technol Dept Mech & Elect Engn Changsha 410004 Peoples R China

The previous studies on the flexible job shop scheduling problems (FJSP) with machine flexibility and worker flexibility normally assume that each machine is operated by one worker at any time. However, it is not accurate in many cases because many workers may be required for machines in processing complex operations. Hence, this paper studies a universal version, i.e., FJSP with worker cooperation flexibility (FJSPWC), which defines that each machine can be used only if their required workers are prepared. A mixed-integer linear programming model tuned by CPLEX is established for the problem aiming to collaboratively minimize the makespan, maximum workload of machines and maximum workload of workers. To solve the problem efficiently, a Paretobased two-stage evolutionary algorithm (PTEA) is proposed. In the PTEA, a well-tailored initialization operator and the NSGA-II structure are designed for global exploration in the first stage, and a competitive objective-based local search operator is developed to improve its local search ability and accelerate the convergence in the second stage. Extensive experiments based on fifty-eight newly formulated benchmarks are carried out to validate the effectiveness of the well-designed initialization operator and two-stage architecture. Comprehensive experiments are performed to evaluate the proposed PTEA, and the results reveal that the PTEA is superior to four comparison algorithms concerning the distribution, convergence, and overall performance.

关键词： Flexible job shop scheduling Cooperation flexibility two-stage algorithm NSGA-II Objective-based local search

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Reducing Rebar Cutting Waste and Rebar Usage of Beams: A two-stage Optimization algorithm

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BUILDINGS 2023年第9期13卷 2279页

作者： Widjaja, Daniel Darma Kim, Sunkuk Kyung Hee Univ Dept Architectural Engn Yongin 17104 South Korea

While various approaches have been developed to minimize rebar cutting waste, such as optimizing cutting patterns and the lap splice position, reducing rebar usage by minimizing the number of splices remains uninvestigated. In response to these issues, a two-stage optimization algorithm was developed that prioritizes the use of special-length rebar to achieve a near-zero rebar cutting waste (N0RCW) of less than 1%, while also reducing overall rebar usage. The two-stage algorithm first optimizes the lap splice position for continuous rebar considering the use of a special-length rebar, which reduces the number of splices required. It then integrates a special-length minimization algorithm to combine the additional rebar. The algorithm was applied to beam structures in a small-sized factory building project, and it resulted in a notable reduction of 29.624 tons of rebar, equivalent to 12.31% of the total purchased quantity. Greenhouse gas emissions were reduced by 102.68 tons, and associated costs decreased by USD 30,256. A rebar cutting waste of 0.93%, which is near zero, was achieved. These findings highlight the significant potential of the proposed algorithm for reducing rebar waste and facilitating sustainable construction practices. The algorithm is also applicable to other reinforced concrete projects, where the associated advantages will be amplified accordingly.

关键词： rebar cutting waste rebar usage lap splice cutting pattern two-stage algorithm optimization

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