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mixed-integer linear programming for scheduling unconventional oil field development

OPTIMIZATION AND ENGINEERING 2021年第3期22卷 1459-1489页

作者： Soni, Akhilesh Linderoth, Jeff Luedtke, James Rigterink, Fabian Univ Wisconsin Dept Ind & Syst Engn Madison WI 53706 USA ExxonMobil Upstream Integrated Solut Irving TX USA

The scheduling of drilling and hydraulic fracturing of wells in an unconventional oil field plays an important role in the profitability of the field. A key challenge arising in this problem is the requirement that neither drilling nor oil production can be done at wells within a specified neighborhood of a well being fractured. We propose a novel mixed-integer linear programming (MILP) formulation for determining a schedule for drilling and fracturing wells in an unconventional oil field. We also derive an alternative formulation which provides stronger relaxations. In order to apply the MILP model for scheduling large fields, we derive a rolling horizon approach that solves a sequence of coarse time-scale MILP instances to obtain a solution at the daily time scale. We benchmark our MILP-based rolling horizon approach against a baseline scheduling algorithm in which wells are developed in the order of their discounted production revenue. Our experiments on synthetically generated instances demonstrate that our MILP-based rolling horizon approach can improve profitability of a field by 4-6%.

关键词： mixed-integer programming Rolling horizon Production scheduling Shale oil Hydraulic fracturing

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mixed-integer quadratic programming for automatic walking footstep placement, duration, and rotation

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OPTIMAL CONTROL APPLICATIONS & METHODS 2020年第6期41卷 1928-1963页

作者： Maximo, Marcos R. O. A. Afonso, Rubens J. M. Aeronaut Inst Technol Comp Sci Div Autonomous Computat Syst Lab Sao Paulo Brazil Aeronaut Inst Technol Elect Engn Div Sao Paulo Brazil Tech Univ Munich Inst Flight Syst Dynam Bayern Germany

This paper presents a mixed-integer model predictive controller for walking. In the proposed scheme, mixed-integer quadratic programs (MIQP) are solved online to simultaneously decide center of mass jerks, footsteps positions, durations, and rotations while respecting actuation, geometry, and contact constraints. Most walking controllers require preplanned footstep rotations to avoid dealing with the nonlinearity introduced by foot rotation decision. The main contribution of this work is an optimization formulation where feet rotations are automatically planned to attain a reference speed rotation. Finally, simulation results are shown to present and discuss the capabilities of the proposed formulation.

关键词： humanoid robot walking hybrid dynamics mixed-integer programming model predictive control

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Safe bounds in linear and mixed-integer linear programming

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MATHEMATICAL programming 2004年第2期99卷 283-296页

作者： Neumaier, A Shcherbina, O Univ Vienna Inst Math A-1090 Vienna Austria

Current mixed-integer linear programming solvers are based on linear programming routines that use floating-point arithmetic. Occasionally, this leads to wrong solutions, even for problems where all coefficients and all solution components are small integers. An example is given where many state-of-the-art MILP solvers fail. It is then shown how, using directed rounding and interval arithmetic, cheap pre- and postprocessing of the linear programs arising in a branch-and-cut framework can guarantee that no solution is lost, at least for mixed-integer programs in which all variables can be bounded rigorously by bounds of reasonable size.

关键词： linear programming mixed-integer programming rounding errors directed rounding interval arithmetic branch-and-cut lower bounds mixed-integer rounding generalized Gomory cut safe cuts safe presolve certificate of infeasibility

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mixed integer programming of generalized hydro-thermal self-scheduling of generating units

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ELECTRICAL ENGINEERING 2013年第2期95卷 109-125页

作者： Aghaei, J. Ahmadi, A. Shayanfar, H. A. Rabiee, A. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Iran Univ Sci & Technol Ctr Excellence Power Syst Automat & Operat Dept Elect Engn Tehran Iran Shahrekord Univ Fac Engn & Technol Dept Elect Engn Shahrekord Iran

This paper presents the application of mixed-integer programming (MIP) approach for solving the hydrothermal self scheduling (HTSS) problem of generating units. In the deregulated environment, the generation companies schedule their generators to maximize their profit while satisfying loads is not an obligation. The HTSS is a high dimensional mixed-integer optimization problem. Therefore, in the large-scale power systems, solving the HTSS is very difficult. In this paper, MIP formulation is adopted for precise modeling of dynamic ramp rate limits, prohibited operating zones, operating services, valve loading effects, variable fuel cost, non-linear start-up cost functions of thermal units, fuel and emission limits of thermal units, multi head power-discharge characteristics of hydro plants and spillage of reservoir. The modified IEEE 118-bus system is used to demonstrate the performance of the proposed method.

关键词： Hydro-thermal self scheduling mixed-integer programming Dynamic ramp rate Prohibited operating zones Valve loading effect

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REPRESENTABILITY IN mixed integer programming .1. CHARACTERIZATION RESULTS

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DISCRETE APPLIED MATHEMATICS 1987年第3期17卷 223-243页

作者： JEROSLOW, RG College of Management Georgia Institute of Technology Atlanta GA 30332-0520 USA

We define the concept of a representation of a set of either linear constraints in bounded integers, or convex constraints in bounded integers. A regularity condition plays a crucial role in the convex case. Then we characterize the representable sets (Theorem 2.1) and provide several examples of our representations. A consequence of our characterization is that the only representable sets are those from ‘either/or’ constraints. This latter case can be treated by generalizations of techniques from the disjunctive methods of cutting-plane theory (e.g. [2] and [30]). The representations given here are intended for use as part of the constraints of a larger optimization problem, where they often can serve to tighten the (linear or convex) relaxation. The study of representations was initiated by Meyer and in the linear case we continue the development in [35].

关键词： Disjunctive methods linear relaxation mixed-integer programming modeling

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An outer approximation algorithm for generating the Edgeworth-Pareto hull of multi-objective mixed-integer linear programming problems

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MATHEMATICAL METHODS OF OPERATIONS RESEARCH 2024年第1期100卷 263-290页

作者： Boekler, Fritz Parragh, Sophie N. Sinnl, Markus Tricoire, Fabien Osnabruck Univ Inst Comp Sci Osnabruck Germany Johannes Kepler Univ Linz Inst Prod & Logist Management JKU Business Sch Linz Austria Johannes Kepler Univ Linz Inst Business Analyt & Technol Transformat JKU Business Sch Linz Austria Vienna Univ Econ & Business Inst Transport & Logist Management Vienna Austria

In this paper, we present an outer approximation algorithm for computing the Edgeworth-Pareto hull of multi-objective mixed-integer linear programming problems (MOMILPs). It produces the extreme points (i.e., the vertices) as well as the facets of the Edgeworth-Pareto hull. We note that these extreme points are the extreme supported non-dominated points of a MOMILP. We also show how to extend the concept of geometric duality for multi-objective linear programming problems to the Edgeworth-Pareto hull of MOMILPs and use this extension to develop the algorithm. The algorithm relies on a novel oracle that solves single-objective weighted-sum problems and we show that the required number of oracle calls is polynomial in the number of facets of the convex hull of the extreme supported non-dominated points in the case of MOMILPs. Thus, for MOMILPs for which the weighted-sum problem is solvable in polynomial time, the facets can be computed with incremental-polynomial delay-a result that was formerly only known for the computation of extreme supported non-dominated points. Our algorithm can be an attractive option to compute lower bound sets within multi-objective branch-and-bound algorithms for solving MOMILPs. This is for several reasons as (i) the algorithm starts from a trivial valid lower bound set then iteratively improves it, thus at any iteration of the algorithm a lower bound set is available;(ii) the algorithm also produces efficient solutions (i.e., solutions in the decision space);(iii) in any iteration of the algorithm, a relaxation of the MOMILP can be solved, and the obtained points and facets still provide a valid lower bound set. Moreover, for the special case of multi-objective linear programming problems, the algorithm solves the problem to global optimality. A computational study on a set of benchmark instances from the literature is provided.

关键词： Multi-objective optimization Outer approximation mixed-integer programming

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Spreading code optimization for low-earth orbit satellites via mixed-integer convex programming

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2024年第1期2024卷 67页

作者： Yang, Alan Mina, Tara Gao, Grace Stanford Univ Dept Elect Engn 350 Jane Stanford Way Stanford CA 94305 USA Stanford Univ Dept Aeronaut & Astronaut 496 Lomita Mall Stanford CA 94305 USA

Optimizing the correlation properties of spreading codes is critical for minimizing inter-channel interference in satellite navigation systems. By improving the codes' correlation sidelobes, we can enhance navigation performance while minimizing the required spreading code lengths. In the case of low-earth orbit (LEO) satellite navigation, shorter code lengths (on the order of a hundred) are preferred due to their ability to achieve fast signal acquisition. Additionally, the relatively high signal-to-noise ratio in LEO systems reduces the need for longer spreading codes to mitigate inter-channel interference. In this work, we propose a two-stage block coordinate descent (BCD) method which optimizes the codes' correlation properties while enforcing the autocorrelation sidelobe zero property. In each iteration of the BCD method, we solve a mixed-integer convex program over a block of 25 binary variables. Our method is applicable to spreading code families of arbitrary sizes and lengths, and we demonstrate its effectiveness for a problem with 66 length-127 codes and a problem with 130 length-257 codes.

关键词： Spreading code optimization Pseudorandom noise codes Low-earth orbit mixed-integer programming Code-division multiple access

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mixed-integer linear programming models and algorithms for generation and transmission expansion planning of power systems

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第3期297卷 1071-1082页

作者： Li, Can Conejo, Antonio J. Liu, Peng Omell, Benjamin P. Siirola, John D. Grossmann, Ignacio E. Carnegie Mellon Univ Dept Chem Engn 5000 Forbes Ave Pittsburgh PA 15213 USA Ohio State Univ Dept Integrated Syst Engn 1971 Neil Ave Columbus OH 43210 USA Ohio State Univ Dept Elect & Comp Engn 2015 Neil Ave Columbus OH 43210 USA Natl Energy Technol Lab Pittsburgh PA 15236 USA Sandia Natl Labs Ctr Comp Res PO 5800 Albuquerque NM 87185 USA

With the increasing penetration of renewable generating units, especially in remote areas not well connected with load demand, there are growing interests to co-optimize generation and transmission expansion planning (GTEP) in power systems. Due to the volatility in renewable generation, a planner needs to include the operating decisions into the planning model to guarantee feasibility. However, solving the GTEP problem with hourly operating decisions throughout the planning horizon is computationally intractable. Therefore, we propose several spatial and temporal simplifications to the problem. Built on the generation expansion planning (GEP) formulation of Lara et al. (2018), we propose a mixed-integer linear programming formulation for the GTEP problem. Three different formulations, i.e., a big-M formulation, a hull formulation, and an alternative big-M formulation, are reported for transmission expansion. We theoretically compare the tightness of the LP relaxations of the three formulations. The proposed MILP GTEP model typically involves millions or tens of millions of variables, which makes the model not directly solvable by the commercial solvers. To address this computational challenge, we propose a nested Benders decomposition algorithm and a tailored Benders decomposition algorithm that exploit the structure of the GTEP problem. Using a case study from Electric Reliability Council of Texas (ERCOT), we are able to show that the proposed tailored Benders decomposition outperforms the nested Benders decomposition. The coordination in the optimal generation and transmission expansion decisions from the ERCOT study implies that there is an additional value in solving GEP and TEP simultaneously. (c) 2021 Elsevier B.V. All rights reserved.

关键词： OR in energy Power systems Generation transmission expansion mixed-integer programming Decomposition algorithm

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Decoupling Network Optimization in High Speed Systems by mixed-integer programming

Decoupling Network Optimization in High Speed Systems by Mix...

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IEEE International Symposium on Circuits and Systems

作者： Jai Narayan Tripathi Ashutosh Mahajan Jayanta Mukherjee Raj Kumar Nagpal Rakesh Malik Nitin Gupta Department of Electrical Engineering IIT Bombay Mumbai INDIA Industrial Engineering & Operations Research IIT Bombay Mumbai INDIA TR&D STMicroelectronics Pvt. Ltd. Greater Noida India

ISBN: (纸本)9781479934331

Power Integrity is maintained in a high speed system by designing an efficient decoupling network. This paper provides a generic formulation for decoupling capacitor selection and placement problem which is solved by mixed-integer programming. A real-world example is presented for the same. The minimum number of capacitors that could achieve the target impedance over the desired frequency range are found along with their optimal locations. In order to solve an industrial problem, the s-parameters data of power plane geometry and capacitors are used for the accurate analysis including bulk capacitors and VRM.

关键词： Power Integrity Power Delivery Networks Decoupling Capacitors S-parameters mixed-integer programming

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Selection of postharvest technology routes by mixed-integer linear programming

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INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS 1997年第2期49卷 85-90页

作者： Maia, LOA Lago, RA Qassim, RY National Center for Food Technology Research — EMBRAPA Brazil School of Engineering and COPPE Federal University of Rio de Janeiro Brazil

A mixed-integer linear programming model is proposed for the selection of technology routes for fruit and vegetable crops between harvest and market. The objective is to optimize capital investment in food preservation facilities under uncertainties? based on alternative routes and a set of crop and market scenarios. A case-study illustrates the application of the model.

关键词： agribusiness mixed-integer programming facility planning

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