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Optimal mathematical programming for the warehouse location problem with Euclidean distance linearization

COMPUTERS & INDUSTRIAL ENGINEERING 2019年 136卷 70-79页

作者： You, Meng Xiao, Yiyong Zhang, Siyue Yang, Pei Zhou, Shenghan Beihang Univ Sch Reliabil & Syst Engn Beijing 100191 Peoples R China

The warehouse location problem (WLP) involves determining one (or multiple) locations as the materials/products collecting/distributing centers for serving a group of customers scattered geographically in a region, at a minimum total transportation cost. The most conventional and widely used approach for solving the WLP is the weighted k-means algorithm. However, this is not a global approach, because it always traps into local optima and is sensitive to the initial settings. Our numeric examples demonstrated that the solutions obtained by the weighted k-means could depart from the optimal values by as much as 16.8% on average. In this paper, we present an optimal programming approach based on mixed-integer linear programming (MILP) for the WLP, which is irrelative to the initial solution and can be optimally solved by commercial solvers. For large-sized datasets, we developed an MILP-based dynamic iterative partial optimization (MILP-DIPO) to search for the near-optimal results with controllable computational time. Experiments on 14 datasets, including 6 small-sized synthesized datasets and 8 variants of the known benchmark datasets in the UEF repository, were performed to validate the proposed model and heuristics. The computational results confirm that improvements with the proposed method could be as great as -22.9% (-14.0% on average) for small-sized datasets. For the eight benchmark datasets, the MILP-DIPO algorithm delivered near-optimal solutions in a reasonable computational time, with up to - 8.0% (- 2.6% on average) improvement compared to the results obtained by the conventional weighted k-means algorithm.

关键词： Warehouse location problem mixed-integer linear programming Clustering Optimization

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Optimization model for long-distance integrated transmission of wind farms and pumped-storage hydropower plants

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APPLIED ENERGY 2019年 242卷 285-293页

作者： Su, Chengguo Cheng, Chuntian Wang, Peilin Shen, Jianjian Wu, Xinyu Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Yellow River Conservancy Tech Inst Sch Hydraul Engn Kaifeng 475004 Peoples R China

Long-distance and large-capacity wind power transmission from western and northern China to load centers through ultra-high voltage (UHV) transmission lines is an important and effective measure for large-scale wind power accommodation in China. This paper proposes a novel practical integrated transmission mode for a wind farm (WF) and a pumped-storage hydropower plant (PSHP). In order to cope with additional imbalance costs caused by deviations from the submitted day-ahead schedule and increase the total operational profit, an optimization model for the integrated transmission of a WF and a PSHP has been formulated. The forecast errors for wind power generation are modeled by a scenario analysis technique. Hydraulic constraints and the head effect on the performance of each pumped-storage hydropower unit (PSHU) in both generating and pumping modes have been considered. Through incorporating the nonlinearities, including constraints on the operation status of units and turbine performance curves, the model is converted into a mixed-integer linear programming (MILP) formulation using piecewise linear approximation techniques. Case studies demonstrate that the integrated transmission of the WF and PHSP can efficiently alleviate the negative effect of wind power fluctuations and significantly increase profit. Sensitivity analyses have been carried out to evaluate the effect of the penalty factor for energy imbalance and the electricity price mechanism in the receiving-end power grid on the overall performance of the WF-PSHP union.

关键词： Integrated transmission Wind farm Pumped-storage hydropower plant Wind power forecast errors mixed-integer linear programming

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Increased utilisation of renewable energies through demand response in the water supply sector - A case study

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ENERGY 2019年 175卷 810-817页

作者： Meschede, Henning Univ Kassel Dept Sustainable Prod & Proc Kassel Germany

Renewable energy systems (RES) play a key role in sustainable energy supply systems. Due to the volatile nature of RES, storage capacities and demand shifting strategies must be implemented. In remote areas like islands, the water supply sector mainly consisting of desalination plants and wells has a significant impact on the energy system. The objective of this paper is the evaluation of the demand shifting potential within this sector with respect to its robustness against probabilistic influencing variables. mixed integer linear programming is used to simulate the optimised dispatch. Compared to the total annual electricity demand of the island, the study shows that up to 2.1% (1.5 GWh) positive and 5.0% (3.6 GWh) negative demand shifting potential can be assumed if only existing plants are used. Utilisation of micro pumped hydro storage can increase these potentials to 5.5% (4.2 GWh) in positive and 10.3% (7.9 GWh) in negative direction. Furthermore, probabilistic solar radiation has no significant influence on the DR potential while for wind power a saturation of the DR potential for higher degrees of self-sufficiency can be found. Nevertheless, the absolute highest degrees of self-sufficiency come along with the utilisation of both photovoltaic (PV) and wind. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Demand response Water supply Sector coupling mixed-integer linear programming Island energy system Smart energy system

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Scheduling ships movements within a canal harbor

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SOFT COMPUTING 2019年第9期23卷 2923-2936页

作者： Pellegrini, Paola di Tollo, Giacomo Pesenti, Raffaele Univ Lille Nord de France IFSTTAR COSYS LEOST 20 Rue Elisee ReclusBP 70317 F-59666 Villeneuve Dascq France Ca Foscari Univ Venice Dept Management Cannaregio 873 I-30121 Venice Italy

In this paper we propose a model for the in-port ship scheduling problem that consists in scheduling the movement of ships inside a canal harbor. Our model, which we name RECIP-MILP, is inspired by a model for scheduling trains, to exploit the analogies between a canal harbor and a single track railway network. Moreover, we show how to translate spatial safety constraints into time ones. We apply our model to instances representing ship movements in the Port of Venice. We test the performance of both the exact RECIP-MILP model and a heuristic solution algorithm based on it. We show that we can exactly solve most instances in few minutes.

关键词： In-port ship scheduling problem Ship scheduling mixed-integer linear programming Venice

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A multi-stage supply chain network design problem with in-house production and partial product outsourcing

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APPLIED MATHEMATICAL MODELLING 2019年 70卷 572-594页

作者： Cortinhal, M. J. Lopes, M. J. Melo, M. T. Univ Inst Lisbon ISCTE IUL Av Forcas Armadas P-1649026 Lisbon Portugal Univ Lisbon Fac Ciencias CMAF CIO P-1749016 Campo Grande Portugal Saarland Univ Appl Sci Business Sch Waldhausweg 14 D-66123 Saarbrucken Germany

We propose a mixed-integer linear programming model for a novel multi-stage supply chain network design problem. Our model integrates location and capacity choices for plants and warehouses with supplier and transportation mode selection, and the distribution of multiple products through the network. The aim is to identify the network configuration with the least total cost subject to side constraints related to resource availability, technological conditions, and customer service level requirements. In addition to in-house manufacturing, end products may also be purchased from external sources and consolidated in warehouses. Therefore, our model identifies the best mix between in-house production and product outsourcing. To measure the impact of this strategy, we further present two additional formulations for alternative network design approaches that do not include partial product outsourcing. Several classes of valid inequalities tailored to the problems at hand are also proposed. We test our models on randomly generated instances and analyze the trade-offs achieved by integrating partial outsourcing into the design of a supply chain network against a pure in-house manufacturing strategy, and the extent to which it may not be economically attractive to provide full demand coverage. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Supply chain network design In-house production Product outsourcing Transportation mode selection Single-assignment mixed-integer linear programming

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Surgical case scheduling with sterilising activity constraints

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2019年第10期57卷 2984-3002页

作者： Al Hasan, Hasan Gueret, Christelle Lemoine, David Rivreau, David Univ Angers LARIS Angers France IMT Atlantique LS2N Nantes France Univ Catholique Ouest LARIS Angers France

In this paper, we study a real scheduling problem which consists in scheduling a set of elective surgical cases requiring surgical instruments and tools in several operating rooms. The objectives are to minimise the overtime of the surgical unit staff, the number of operating rooms used and the number of instruments processed in emergency in the sterilising unit while respecting the current level of service represented by the total number of patients operated per month at the orthopaedic surgery unit. This research was performed in collaboration with the University Hospital of Angers in France (CHU Angers), which has also provided historical data for the experiments. We propose a mixed integer linear programming model for the problem which is solved in a lexicographic fashion. We also propose a robust formulation to deal with the uncertain surgery durations. Both the deterministic and robust formulations are then compared over a set of instances provided by the CHU. The solutions obtained are competitive in terms of number of operating rooms and significantly improve those implemented operationally at the CHU in terms of overtime and emergencies at the sterilising unit.

关键词： operating rooms in health services elective surgeries planning sterilisation unit scheduling mixed-integer linear programming robust optimisation

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Flexible feeder interconnections for increased penetration of renewables and improved volt/VAr control in distribution networks

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第21期13卷 4861-4869页

作者： Baghban-Novin, Salar Golshannavaz, Sajjad Nazarpour, Daryoush Hamidi, Amir Urmia Univ Elect Engn Dept Orumiyeh Iran

In this study, a daily distribution management system (DMS) is developed, which utilises the potential of soft open points (SOPs) to enhance the renewable share in power provision task. The active and reactive power contributions of SOPs, as a flexible interconnection, amend the voltage security issues due to high penetration of photovoltaics (PVs). A complete model for SOP is developed to address the conduction and switching losses that affect the technical and economic operation indices. The optimal scheduling framework of DMS is linearly modelled within mixed-integer linear programming to lower the computational burden of the problem. Case studies are carried out on IEEE 33-node system to illustrate and verify the effectiveness of the proposed model. The comparative analysis shows a lower operation cost besides the improved voltage profile and the reduced losses of the whole system. The effective collaboration of PVs and dispatchable distributed generations (DDGs) assisted by the SOPs power processes causes higher penetration of PVs and enhanced the exploitation of DDGs results in a 9.8% increment of PV power exploitation and improved power factor of DDGs operation.

关键词： integer programming scheduling distributed power generation photovoltaic power systems reactive power linear programming optimisation reactive power control voltage control power distribution control power system security distribution networks renewable share power provision task active power contributions reactive power contributions SOP flexible interconnection voltage security issues switching losses technical operation indices economic operation indices optimal scheduling framework DMS mixed-integer linear programming computational burden IEEE 33-node system lower operation cost improved voltage profile reduced losses dispatchable distributed generations SOPs power processes higher penetration PV power exploitation power factor DDGs operation flexible feeder interconnections distribution networks daily distribution management system soft open points

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Toward a Synthetic Model for Distribution System Restoration and Crew Dispatch

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第3期34卷 2228-2239页

作者： Chen, Bo Ye, Zhigang Chen, Chen Wang, Jianhui Ding, Tao Bie, Zhaohong Argonne Natl Lab Energy Syst Div Argonne IL 60439 USA Xi An Jiao Tong Univ State Key Lab Elect Insulat & Power Equipment Xian 710049 Peoples R China Southern Methodist Univ Dept Elect Engn Dallas TX 75205 USA Xi An Jiao Tong Univ Xian 710049 Shaanxi Peoples R China

Distribution service restoration (DSR) is critical for improving the resilience and reliability of modern distribution systems by strategically and sequentially energizing the system components and customer loads. Restoring electricity service to affected customers also requires multiple crews with different skill sets to perform multiple tasks that are procedurally interdependent with safety guaranteed. However, in existing DSR practices, switch operations and crew dispatch are scheduled separately, and their interdependence is not fully considered. As advanced technologies are enabling remote communication, control, and dispatch, utilities now desire an integrated DSR framework to achieve seamless coordination among multiple DSR tasks such as switch operation, crew dispatch, and component repair. In this paper, we introduce a synthetic model that integrates the service restoration model and the crew dispatch model based on a universal routing model. The proposed model can provide the estimated time of restoration for each load, the switching sequence for safely operating remotely/manually operated switches, and dispatch solutions for crews with different skill sets. The proposed synthetic model is formulated as a mixed-integer linear programming model, and its effectiveness is evaluated via the IEEE 123 bus test feeder and several large-scale test feeders (EPRI Ckt5, Ckt7, Ckt24, and IEEE 8500 node test feeder.

关键词： Distribution service restoration crew dispatch mixed-integer linear programming repair switching sequence management

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Data-driven distributionally robust optimization of shale gas supply chains under uncertainty

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AICHE JOURNAL 2019年第3期65卷 947-963页

作者： Gao, Jiyao Ning, Chao You, Fengqi Cornell Univ Robert Frederick Smith Sch Chem & Biomol Engn Ithaca NY 14853 USA

This article aims to leverage the big data in shale gas industry for better decision making in optimal design and operations of shale gas supply chains under uncertainty. We propose a two-stage distributionally robust optimization model, where uncertainties associated with both the upstream shale well estimated ultimate recovery and downstream market demand are simultaneously considered. In this model, decisions are classified into first-stage design decisions, which are related to drilling schedule, pipeline installment, and processing plant construction, as well as second-stage operational decisions associated with shale gas production, processing, transportation, and distribution. A data-driven approach is applied to construct the ambiguity set based on principal component analysis and first-order deviation functions. By taking advantage of affine decision rules, a tractable mixed-integer linear programming formulation can be obtained. The applicability of the proposed modeling framework is demonstrated through a small-scale illustrative example and a case study of Marcellus shale gas supply chain. Comparisons with alternative optimization models, including the deterministic and stochastic programming counterparts, are investigated as well. (c) 2018 American Institute of Chemical Engineers AIChE J, 65: 947-963, 2019

关键词： data-driven distributionally robust optimization shale gas supply chain uncertainty mixed-integer linear programming

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Optimal Operation of Unbalanced Three-Phase Islanded Droop-Based Microgrids

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IEEE TRANSACTIONS ON SMART GRID 2019年第1期10卷 928-940页

作者： Vergara, Pedro P. Lopez, Juan C. Rider, Marcos J. da Silva, Luiz C. P. Univ Estadual Campinas Dept Syst & Energy BR-13083852 Campinas SP Brazil

This paper presents a new mixed-integer nonlinear programming (MINLP) model for the optimal operation of unbalanced three-phase droop-based microgrids. The proposed MINLP model can be seen as an extension of an optimal power flow for microgrids operating in islanded mode, that aims to minimize the total amount of unsupplied demand and the total distributed generator (DG) generation cost. Since the slack bus concept is not longer valid, the proposed model considers the frequency and voltage magnitude reference as variables. In this case, DCs units operate with droop control to balance the system and provide a frequency and voltage magnitude reference. Additionally, a set of efficient linearizations are introduced in order to approximate the original MINLP problem into a mixed-integer linear programming (MILP) model that can be solved using commercial solvers. The proposed model has been tested in a 25-bus unbalanced three-phase microgrid and a large 124-node grid, considering different operational and time-coupling constraints for the DGs and the battery systems (BSs). Load curtailment and different modes of operation for the wind turbines have also been tested. Finally, an error assessment between the original MINLP and the approximated MILP model has been conducted.

关键词： Droop control islanded microgrid mixed-integer linear programming three-phase optimal power flow

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