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A mixed-integer nonlinear programming model for Optimal Reconfiguration of DC Distribution Feeders

ENERGIES 2020年第17期13卷 4440页

作者： Montoya, O. D. Gil-Gonzalez, W. Hernandez, J. C. Giral-Ramirez, D. A. Medina-Quesada, A. Univ Dist Francisco Jose de Caldas Fac Ingn Bogota 11021 DC Colombia Univ Tecnol Bolivar Lab Inteligente Energia Cartagena 131001 Colombia Inst Univ Pascual Bravo Fac Ingn Grp GIIEN Campus Robledo Medellin 050036 Colombia Univ Jaen Dept Elect Engn Campus Lagunillas S-NEdificio A3 Jaen 23071 Spain Univ Dist Francisco Jose de Caldas Fac Tecnol Bogota 11021 DC Colombia

This paper deals with the optimal reconfiguration problem of DC distribution networks by proposing a new mixed-integer nonlinear programming (MINLP) formulation. This MINLP model focuses on minimising the power losses in the distribution lines by reformulating the classical power balance equations through a branch-to-node incidence matrix. The general algebraic modelling system (GAMS) is chosen as a solution tool, showing in tutorial form the implementation of the proposed MINLP model in a 6-nodes test feeder with 10 candidate lines. The validation of the MINLP formulation is performed in two classical 10-nodes DC test feeders. These are typically used for power flow and optimal power flow analyses. Numerical results demonstrate that power losses are reduced by about 16% when the optimal reconfiguration plan is found. The numerical validations are made in the GAMS software licensed by Universidad Tecnologica de Bolivar.

关键词： branch-to-node incidence matrix direct current networks mixed-integer nonlinear programming model general algebraic modelling system optimal reconfiguration of distribution grids

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mixed-integer programming model and hybrid immune clone select algorithm for multi-objective double floor corridor allocation problem with vertical conveyor

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2022年第0期77卷 1页

作者： Liu, Juniqi Zhang, Zeqiang Zhang, Yu Liu, Silu Chen, Feng Yin, Tao Southwest Jiaotong Univ Sch Mech Engn Chengdu 610031 Peoples R China Technol & Equipment Rail Transit Operat & Maintena Chengdu 610031 Peoples R China

Detailed research on the impact of longitudinal material transportation mode and facility direction on the layout based on the double-floor corridor allocation problem (DFCAP) is lacking. Hence, we proposed a mixed-integer nonlinear programming (MINLP) model of a multi-objective DFCAP (MODFCAP) for minimising the material handling cost (MHC), minimising total layout area, and optimising the equilibrium index of double elevators. Moreover, we proposed a multi-objective clonal selection algorithm with variable neighbourhood search (VNS) operations (ICSAVNS) for solving MODFCAP efficiently. ICSAVNS performs a deep search of the population using the Metropolis-based VNS operation and also performs a breadth search through the two-segment mutation simultaneously. The accuracy of the model and algorithm is validated experimentally using a 9-scale calculation instance. We designed the Taguchi experiment to explore reasonable algorithm parameters and analysed the advantages and disadvantages of the layout schemes under different target preferences based on the results of a set of 24-scale production examples. Finally, the simulation instances of MODFCAP and bi-objective CAP are tested and compared with a series of algorithms. The results show that ICSAVNS can achieve the solution per-formance of the current advanced multi-objective algorithm.

关键词： Facilities planning and design Double floor corridor allocation problem mixed-integer nonlinear programming model Clonal select algorithm Variable neighbourhood search operation

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A smart energy scheduling under uncertainties of an iron ore stockyard-port system using a rolling horizon algorithm

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COMPUTERS & OPERATIONS RESEARCH 2024年 164卷

作者： Junior, Marcos W. J. Servare Rocha, Helder R. de Oliveira Salles, Jose L. Felix Fed Univ Espirito St Elect Eng Dept Ave Fernando Ferrari 514 BR-29075910 Vitoria ES Brazil

Planning the efficient use of electricity in iron ore stockyard operations is a strategic issue due to the constant rise in energy prices nowadays and its considerable impact on production costs. This paper proposes a new large-scale mixed-integer nonlinear programming (MINLP) model for stockyard-port energy planning solved by the energy scheduling algorithm and a commercial solver to minimize power costs. The proposed nonlinear optimization problem is solved through an equivalent MILP model to minimize the flows of power and material between the stockyard-port equipment. The electrical machines are powered by different electricity energy providers, and eventually consume storage energy from batteries. The energy scheduling algorithm allows the planner to find a solution that saves electrical power costs in real time under unforeseen operational changes. Numerical results obtained through the proposed algorithm with a scheduling horizon of 24 h, show that the presence of the battery in the stockyard-port electrical grid allows for an energy cost reduction of up to 17.88% compared to the case without the battery. The energy scheduling based on rolling horizon algorithm provides feasible solutions near to the optimal solution, with an average distance of 1.78%, and it has an affordable computation time in instances where the MINLP model is not able to provide a solution.

关键词： Stockyard Port Energy scheduling Rolling horizon algorithm mixed-integer nonlinear programming model Battery management

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Probabilistic tabu search algorithm for container liner shipping problem with speed optimisation

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2022年第12期60卷 3651-3668页

作者： Wang, Shijin Zhao, Qianyang Tongji Univ Sch Econ & Management Shanghai 200092 Peoples R China

This paper considers a container liner shipping problem with speed optimisation (CLSP-SO) to minimise the total costs of the fleet, which includes operating costs, capital costs and voyage costs. A mixed-integer nonlinear programming model is first formulated to illustrate the problem, in which the oil consumption of ships is treated as a cubic function of speeds. Then, the computational complexity of the problem is analysed and a lower bound is given based on the theoretical optimised speed of ships. To solve the problem, a probabilistic tabu search (PTS)-based algorithm is developed considering the NP-hardness of the problem. Extensive computational experiments on randomly generated data and a real-world case are conducted and the performance of the proposed method is compared with the lower bound and that of the basic tabu search (TS) algorithm. The results show that the proposed PTS-based algorithm obtains satisfactory solutions with respect to lower bounds in reasonable computation time and it outperforms the basic TS-based algorithm.

关键词： Container liner shipping speed optimisation probabilistic tabu search generalised assignment problem mixed-integer nonlinear programming model

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Optimization of medical waste recycling network considering disposal capacity bottlenecks under a novel coronavirus pneumonia outbreak

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2022年第53期29卷 79669-79687页

作者： Mei, Xueyun Hao, Hao Sun, Yichen Wang, Xinyang Zhou, Yanjun Shanghai Polytech Univ Sch Econ & Management Shanghai 201209 Peoples R China

The sudden outbreak and prolonged impact of the global novel coronavirus disease (COVID-19) epidemic has caused an increase in demand for medical products, such as masks and protective clothing, leading to an exponential increase in the generation of medical waste. As medical waste under the epidemic is highly infectious, it poses a great danger to human health. Therefore, with the proliferation of medical waste, it has become crucial to construct a reverse logistics recycling network that can handle medical waste quickly and efficiently. In this study, we construct a multi-period medical waste emergency reverse logistics network siting model with the objectives of minimum cost, minimum safety risk, and minimum time for the safe and quick disposal of medical waste. The model considers disposal capacity bottlenecks of existing facilities. Based on an empirical analysis using the COVID-19 epidemic in New York City, USA, as a case study, we find that the use of a suitable number of synergistic facilities and the establishment of temporary medical waste disposal centers are viable options for handling the dramatic increase in medical waste during the peak of the COVID-19 epidemic.

关键词： Disposal capacity bottlenecks COVID-19 mixed-integer nonlinear programming model Emergency reverse logistics network Third-order polynomial function Safety risk

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A MIQP model for optimal location and sizing of dispatchable DGs in DC networks

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ENERGY SYSTEMS-OPTIMIZATION modelING SIMULATION AND ECONOMIC ASPECTS 2021年第1期12卷 181-202页

作者： Danilo Montoya, Oscar Gil-Gonzalez, Walter Univ Dist Francisco Jose de Caldas Fac Ingn Carrera 7 40B-53 Bogota 11021 DC Colombia Univ Tecnol Bolivar Lab Inteligente Energia Km 1 Via Turbaco Cartagena 131001 Colombia Inst Univ Pascual Bravo Fac Ingn Grp GIIEN Campus Robledo Medellin 050036 Colombia

The allocation and dimensioning of distributed generators (DGs) in direct current (DC) power grids were addressed in this study by using a mixed-integer quadratic programming (MIQP) formulation. The MIQP model corresponded to an approximation of the mixed-integer nonlinear programming (MINLP) model that represents this problem correctly. The proposed MIQP had, for its objective function, the minimization of the power losses;as constraints, it had power balance, voltage regulation, distributed generation capacity, and the number of DGs available, among others. The general algebraic modeling system (GAMS) was employed for solving the proposed MIQP as well as the MINLP formulation. Simulation results for one DC network with 21 nodes and another with 69 revealed that the proposed MIQP model obtains high-quality results regarding the locations of the generators, the objective function, and the power dispatch in comparison to the exact MINLP model and metaheuristic techniques recently reported in specialized literature.

关键词： Direct current power grids Distributed generators mixed-integer programming model mixed-integer nonlinear programming model Optimal power flow

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Linearization technique with superior expressions for centralized planning problem with discount policy

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2020年 542卷 122746-122746页

作者： Yang, Fang Huang, Yao-Huei Southwest Jiaotong Univ Sch Econ & Management Chengdu 610031 Peoples R China Fu Jen Catholic Univ Dept Informat Management New Taipei Taiwan

This paper studies a centralized planning problem (CPP), which is a variant of the winner determination problem (WDP) in transportation service procurement. The WDP contains one shipper with multiple depots, and multiple carriers. Traditionally, the shipper solves the WDP to obtain winning carriers for serving lanes. In this paper, the shipper specifically considers J possible locations, and then only p locations can be selected as depots. These carriers provided the best quantity discount are able to obtain the best chance of being winners for serving lanes. This study proposes a mixed-integer nonlinear programming (MINP) model for the CPP. The non-convex property of the MINP makes the model difficult to find an exact global optimal solution efficiently and effectively. To overcome the difficulty, the MINP model can be converted into a mixed-integer linear programming (MILP) model to obtain an optimal solution by utilizing the proposed linearization technique with superior expressions. Numerical experiments also show the usefulness of the proposed model, and indicate that moderately sized realistic instances can be solved efficiently and effectively. (C) 2019 Published by Elsevier B.V.

关键词： Centralized planning programming Transportation service procurement mixed-integer nonlinear programming model Superior expressions Linearization technique

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Moving beyond the optimal transmission switching: stochastic linearised SCUC for the integration of wind power generation and equipment failures uncertainties

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第15期12卷 3780-3792页

作者： Nikoobakht, Ahmad Aghaei, Jamshid Mardaneh, Mohammad Niknam, Taher Vahidinasab, Vahid Higher Educ Ctr Eghlid Eghlid Iran Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Shahid Beheshti Univ Abbaspour Sch Engn Dept Elect Engn Tehran Iran

This study recommends a stochastic optimization model for the security constrained unit commitment (SCUC), which incorporates the optimal transmission switching (OTS) for managing the uncertainty of wind power generation and equipment failures, i.e. unit/line outages. Also, this study presents a technique in stochastic SCUC model with the OTS action using the AC optimal power flow (AC OPF). The AC OPF provides a more accurate picture of power flow in the power system compared to the DC optimal power flow that is usually considered in the literature for the stochastic SCUC models and the OTS action. While the stochastic SCUC model with the OTS action based on AC OPF is a mixed-integer non-linear programming model, this study transforms it into a mixed-integer linear programming (MILP) model. The MILP approach uses a piecewise linear model of AC OPF, which allows the reactive power and voltage to be considered directly in power flow model. The proposed stochastic SCUC problem is evaluated on the 6 bus, IEEE 118-bus and 662-bus test systems in pre- and post-OTS action. Obtained results demonstrate the effectiveness of the proposed model.

关键词： wind power plants power generation reliability power transmission reliability failure analysis stochastic programming power system security power generation dispatch power generation scheduling load flow integer programming linear programming piecewise linear techniques reactive power optimal transmission switching stochastic linearised SCUC equipment failure uncertainties stochastic optimisation model security constrained unit commitment OTS wind power generation uncertainty managing stochastic SCUC model AC optimal power flow AC OPF power system mixed-integer nonlinear programming model mixed-integer linear programming model MILP approach piecewise linear model reactive power global optimal solution IEEE 118-bus test system IEEE 662-bus test system post-OTS action pre-OTS action

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Liner container seasonal shipping revenue management

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2015年 82卷 141-161页

作者： Wang, Yadong Meng, Qiang Du, Yuquan Natl Univ Singapore Dept Civil & Environm Engn Singapore 117576 Singapore Natl Univ Singapore Ctr Maritime Studies Singapore 118414 Singapore

This paper proposes a liner container seasonal shipping revenue management problem for a container shipping company. For a given weekly multi-type shipment demand pattern in a particular season, the proposed problem aims to maximize the total seasonal shipping profit by determining the number of multi-type containers to be transported and assigned on each container route, the number of containerships deployed on each ship route, and the sailing speed of containerships on each shipping leg subject to both the volume and capacity constraints of each containership. By adopting the realistic bunker consumption rate of a containership as a function of its sailing speed and payload (displacement), we develop a mixed-integer nonlinear programing with a nonconvex objective function for the proposed liner container seasonal shipping revenue management problem. A tailored branch and bound (B&B) method is designed to obtain the global epsilon-optimal solution of the model. Numerical experiments are finally conducted to assess the efficiency of the solution algorithm and to show the applicability of the developed model. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Liner shipping Bunker consumption Revenue management mixed-integer nonlinear programming model Global optimization Branch and bound

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Two-Stage Method and Application for Molten Iron Scheduling Problem between Iron-Making Plants and Steel-Making Plants

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IFAC Proceedings Volumes 2011年第1期44卷 9476-9481页

作者： Hui Huang Tianyou Chai Xiaochuan Luo Binglin Zheng Hong Wang State Key Laboratory of Integrated Automation for Process Industry (Northeastern University) Shenyang China 110819 (Tel: +86-24-83678332) National Metallurgical Automation Engineering Technology Research Center Northeastern University Shenyang China 110819 Control Systems Centre School of Electrical and Electronic Engineering the University of Manchester P O Box 88Manchester M60 1QD UK

Abstract In this paper, a two-stage method is proposed to solve the molten iron scheduling problem (MISP). Firstly, a 0-1 mixed-integer nonlinear programming model is established for special type of molten iron scheduling problem (STMISP). A method to solve mathematical model of STMISP is presented, which include assigning machine strategy of STMISP and determining mathematical model of eliminating machine conflicts. Secondly, on the basis of results of STMISP, a heuristic algorithm based on the rule of first come first serve (FCFS) principle is established to solve normal type of molten iron scheduling problem (NTMISP). The molten iron scheduling system with the two-stage method has been successfully applied to Shanghai Baosteel Company to realize quickly optimal molten iron scheduling. Application results show that the two-stage method is both effective and feasible.

关键词： Molten iron scheduling problem Two-stage method Hybrid flow shop mixed-integer nonlinear programming model Heuristic algorithm

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