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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Oussama Alaya Taiseer Alhaj Ali Benedikt Jahn Hendrik Lens Faculty 4 IFK Power Generation and Automatic Control Group University of Stuttgart

ISBN: (数字)9798350390421

ISBN: (纸本)9798350390438

The transition to a carbon-neutral power system requires replacing conventional generation with distributed renewable energy (RE) sources. This poses challenges related to reduced system inertia and large and long-distance power transmission in the system. This paper presents a novel generation expansion planning (GEP) methodology called inertia-aware clustered generation expansion planning (I-CGEP). The I-CGEP approach integrates spatial clustering and generator clustering to optimize discrete generation expansion options while avoiding overestimation of system inertia. The model incorporates advanced Rate of Change of Frequency (RoCoF) constraints that, in addition to standard constraints following predefined outages, also account for the expected power imbalance resulting from large disturbance scenarios such as regional islanding. The entire problem is formulated as a mixed-integer linear programming (MILP) problem. The proof of concept of the methodology is demonstrated using the open European transmission system model PyPSA-Eur. The results show its suitability for maintaining the required RoCoF under different scenarios.

关键词： Renewable energy sources Islanding Europe Power transmission Generators Planning Smart grids Safety mixed integer linear programming Standards

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Decomposition of the Location Problem in a Hybrid Clustering-Location Model

Decomposition of the Location Problem in a Hybrid Clustering...

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International Conference on Computers & Industrial Engineering (CIE)

作者： Arnaldo Rabello de Aguiar Vallim Filho Computer Science Department Mackenzie Presbyterian University Brazil

Operations research is usually employed to solve the facility location problem, mainly using mixed integer linear programming (MILP). Meanwhile, some MILP models were not originally designed to solve a large class of location problems, corresponding to those where customers are served in a routing operation. In this case location and routing decisions are strongly interrelated. Moreover, this modeling approach has the difficult of facing a NP-hard problem situation, which means a very high algorithm complexity. Therefore, for large-scale problems the computational times are practically infeasible. This paper has developed an alternative method using a hybrid approach to solve the location problem, taking into account these two aspects: the NP- hard situation and the routing operation. The suggestion is to decompose the problem through a clustering procedure applied to the demand points, followed by the application of an optimization model to each cluster. The proposal appeared to be effective when applied to a set of test problems used on a conducted experiment designed to validate the method.

关键词： Polynomials Operations research Routing mixed integer linear programming NP-hard problem Large-scale systems Proposals Logistics Genetic algorithms Computer science

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Integrated Infrastructure Strategy for Sustainable Electrical Vehicles Charging Stations and Transportation Networks

Integrated Infrastructure Strategy for Sustainable Electrica...

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IEEE Power India Conference

作者： Digambar Singh Govind Manoj Fozdar Department of Electrical Engineering Malaviya National Institute of Technology Jaipur India

ISBN: (数字)9798350367065

ISBN: (纸本)9798350367072

The adoption of Electric Vehicles(EVs) is growing because of their environment-friendly properties and more efficient, With the increasing shift toward EVs, the need for a robust and well-coordinated charging infrastructure has become critical. The current lack of sufficient Fast Charging Stations (FCS) poses a significant challenge to supporting widespread EV usage. Proper planning of charging stations, both in terms of location and capacity, is essential to accommodate rising EV demand. Complicating this process is the interdependence between Transportation Networks (TN) and Power Distribution Networks (PDN), which requires a unified approach for efficient large-scale EV integration. This paper introduces a coordinated planning approach for integrating EV charging stations within both TN and PDN frameworks. A detailed optimization model is presented to identify the optimal locations and capacities for charging stations based on EV traffic patterns and power network capabilities. The traffic flow across the transportation network is modelled using an unconstrained traffic assignment method, while the PDN is represented through a linearized power flow model. To capture the complex interactions between TN and PDN, the model employs a mixed-integer linear programming (MILP) framework that incorporates constraints from both networks. Through simulations on coupled traffic and power networks, the proposed approach demonstrates its effectiveness in optimizing EV charging infrastructure, facilitating a smoother transition to electric mobility.

关键词： Optimization models Transportation Traffic control Probabilistic logic Electric vehicle charging Planning Power systems mixed integer linear programming Reliability Traffic congestion

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ISO's optimal strategies for scheduling the hourly demand response in day-ahead markets

ISO's optimal strategies for scheduling the hourly demand re...

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IEEE General Meeting Power& Energy Society

作者： Masood Parvania Mahmud Fotuhi-Firuzabad Mohammad Shahidehpour University of California Davis Davis CA US

Summary from only given. This paper presents a hierarchical demand response (DR) bidding framework in the day-ahead energy markets which integrates customer DR preferences and characteristics in the ISO's market clearing process. In the proposed framework, load aggregators submit aggregated DR offers to the ISO which would centrally optimize final decisions on aggregators' DR contributions in wholesale markets. The hourly load reduction strategies include load shifting and curtailment and the use of onsite generation and energy storage systems. The ISO applies mixed-integer linear programming (MILP) to the solution of the proposed DR model in the day-ahead market clearing problem. The proposed model is implemented using a 6-bus system and the IEEE-RTS, and several studies are conducted to demonstrate the merits of the proposed DR model.

关键词： Load management ISO Load modeling Processor scheduling Computers Energy storage mixed integer linear programming

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Rebalancing in bike sharing systems: Application to the Lisbon case study

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CASE STUDIES ON TRANSPORT POLICY 2023年 13卷

作者： Chastre, Miguel R. Andrade, Antonio R. Univ Lisbon IDMEC Inst Super Tecn Lisbon Portugal

This work presents a mathematical programming formulation for the static Bike Rebalancing Problem to meet the practical constraints faced by the operators of Bike Sharing Systems. Adaptating a mixed integer linear programming formulation, it now includes different types of vehicles and bicycles, the autonomy of each vehicle, the duration of its route and the stations that require inspection actions. An intermediate station is introduced to temporarily store bicycles, relaxing the restrictions imposed by the vehicles' capacity. After incorporating different acceleration procedures, a Branch-and-Cut scheme is run for 30 min to find optimized routes for the reposition vehicle on five real instances of the Lisbon Bike Sharing System. The computed routes resulted in a 30% to 75% decrease in total length, when compared to the real routes. This decrease is mainly attributed to the integration of all the mentioned factors in one global model, encouraging its future implementation.

关键词： Bike Sharing System Bike Rebalancing Problem Repositioning mixed integer linear programming Branch-and-Cut

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Scheduling with a weight-modifying activity to minimize the total weighted completion time

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Omega (United Kingdom) 2024年 128卷

作者： Lin, Bertrand M.T. Liu, Shu-Wei Mosheiov, Gur Institute of Information Management National Yang Ming Chiao Tung University Hsinchu Taiwan Syntec Technology Co. Ltd. Hsinchu Taiwan School of Business Administration The Hebrew University Jerusalem Israel

This paper considers a single-machine scheduling problem to minimize the total weighted completion time with a weight modifying activity, after which the job weights are discounted by a given factor. The problem is known to be ordinary NP-hard. We propose two mixed integer linear programs (MILPs) and a dynamic programming algorithm to optimally solve the problem. Optimality properties are established and then formulated as pruning constraints to improve the problem-solving efficiency of the MILPs. Special cases are discussed and shown to be solvable by polynomial time algorithms. Complexity status of the studied problem with several instance characteristics is shown. Computational experiments indicate that the optimality properties can reduce the computing efforts and that one of the proposed MILPs can solve instances of 200 jobs in a few seconds. © 2024 Elsevier Ltd

关键词： Dynamic programming mixed integer linear programming Single-machine scheduling Weight modifying activity

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An integrated production-distribution optimization model for multinational manufacturing corporations

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INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING MANAGEMENT 2024年第1期19卷 29-45页

作者： Bhutta, M. Khurrum S. Alhawari, Omar I. I. Mohamed, Zubair M. M. Ohio Univ Coll Business Athens OH USA Ohio Univ Ind & Syst Engn Dept Athens OH 45701 USA Bowling Green State Univ Schmidthorst Coll Business Bowling Green OH USA

In proposing an integrated production-distribution model for multinational corporations (MNC), the current research undertakes a novel, simultaneous consideration of facility location, capacity acquisition/disposal, labor, manufacturing, purchasing, exchange rates, tariffs, and container and/or individual shipping factors. Unlike prior studies that examined some such factors. Based on real-world data from a window manufacturing MNC, a mixed integer linear programming model is developed and solved using CPLEX Solver. It reveals how the different features affect the base solution. Specifically, increased demand pushes more manufacturing to US and UK facilities rather than (low-cost) Chinese facilities;it helps meets some of China's demand and leads to reduced total tariff costs. Decreased demand instead favors the Chinese facility, and the increase in tariff costs can be offset by savings in manufacturing and transportation costs. Changes to the factors have insignificant effects on the production and distribution mix, with little to no impact on total profits, because these costs are lower than capacity costs. The comprehensive proposed model provides firms with a framework for obtaining meaningful insights into how they can maintain their operations in sustainable, profitable ways. This research also should assist policymakers in making informed decisions regarding regulations on production and distribution strategies.

关键词： Multinational corporation optimization integrated modeling mixed integer linear programming container shipment supply chain network

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A branch-and-bound algorithm for two-machine flow-shop scheduling problems with batch delivery costs

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International Journal of Systems Science: Operations and Logistics 2014年第2期1卷 94-104页

作者： Mazdeh, Mohammad Mahdavi Rostami, Mohammad Department of Industrial Engineering Iran University of Science & Technology Tehran Iran

Manufacturers often dispatch jobs in batches to reduce delivery costs. However, this technique can have a negative effect on other scheduling-related objective functions such as minimising maximum tardiness. This paper aims to minimise the maximum tardiness and the sum of delivery costs of a two-machine flow-shop problem in a batch delivery system. It is proven in the literature that this problem is NP-complete. We present a mixed integer linear programming (MILP) model to solve the problem. As this is an MILP model, the commercial solver (the GAMS software using CPLEX solver) is not guaranteed to find the optimal solution for large-size problems at a logical CPU run time. Therefore, a branch-and-bound (B&B) algorithm is proposed for obtaining the optimum solution. Additionally, an upper bound (UB) heuristic with a quick processing time is presented. These methods are evaluated using randomly generated instances and the results indicate the efficiency of the B&B and UB heuristic algorithms. © 2014, © 2014 Taylor & Francis.

关键词： batched delivery system branch-and-bound algorithm maximum tardiness mixed integer linear programming two-machine flow-shop scheduling

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Optimising nurse schedules at a community health centre

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OPERATIONS RESEARCH FOR HEALTH CARE 2021年 30卷 100308-100308页

作者： Zimmerman, Samantha L. Bi, Alan Dallow, Trevor Rutherford, Alexander R. Stephen, Tamon Bye, Cameron Hall, David Day, Andrew Latham, Nicole Vasarhelyi, Krisztina Simon Fraser Univ Dept Math 8888 Univ Dr Burnaby BC V5A 1S6 Canada Simon Fraser Univ SFU Big Data 8888 Univ Dr Burnaby BC V5A 1S6 Canada Simon Fraser Univ Fac Hlth Sci 8888 Univ Dr Burnaby BC V5A 1S6 Canada Vancouver Coastal Hlth 520 W 6th Ave Vancouver BC V5Z 4H5 Canada

We present a new scheduling approach to improve access to care at an inner-city community health centre in Vancouver, Canada, serving marginalised clients with complex biopsychosocial needs. In order to meet the specific care needs of clients, the centre provides a range of services on a booked and walk-in basis, and it is important that clients are seen in a timely manner. To align schedules with client demand, we developed a schedule optimisation model that maximises time nurses spend with clients. This new objective function allows for a simple mixed integer linear programming structure that directly incorporates carryover demand. Client-centred key performance indicators were evaluated using a discrete event simulation model. Optimisation aligns schedules to demand, leading to fewer clients who leave without being seen due to an extended wait. This increases the number of clients receiving care by up to 9 per week, without compromising wait times. Furthermore, our approach addresses service delivery concerns, including baseline nurse coverage for triage and weekly variability in total nurse hours. Strategically aligning nurse shifts to demand is an effective approach to better meet client needs without increasing total nurse staffing levels in a community health centre context. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Nurse schedule optimisation Primary health care Access to care Health equity mixed integer linear programming Discrete event simulation

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On the Performance of the Subtour Elimination Constraints Approach for the p-Regions Problem: A Computational Study

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GEOGRAPHICAL ANALYSIS 2018年第1期50卷 32-52页

作者： Carlos Duque, Juan Velez-Gallego, Mario C. Catalina Echeverri, Laura Univ EAFIT Sch Econ & Finance RiSE Medellin Colombia Univ EAFIT Dept Prod Engn Medellin Colombia

The p-regions is a mixed integer programming (MIP) model for the exhaustive clustering of a set of n geographic areas into p spatially contiguous regions while minimizing measures of intraregional heterogeneity. This is an NP-hard problem that requires a constant research of strategies to increase the size of instances that can be solved using exact optimization techniques. In this article, we explore the benefits of an iterative process that begins by solving the relaxed version of the p-regions that removes the constraints that guarantee the spatial contiguity of the regions. Then, additional constraints are incorporated iteratively to solve spatial discontinuities in the regions. In particular we explore the relationship between the level of spatial autocorrelation of the aggregation variable and the benefits obtained from this iterative process. The results show that high levels of spatial autocorrelation reduce computational times because the spatial patterns tend to create spatially contiguous regions. However, we found that the greatest benefits are obtained in two situations: (1) when n/p >= 3;and (2) when the parameter p is close to the number of clusters in the spatial pattern of the aggregation variable.

关键词： GEOGRAPHY -- Mathematical models CONSTRAINT algorithms mixed integer linear programming AUTOCORRELATION (Statistics) AGGREGATION (Statistics) ITERATIVE methods (Mathematics)

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