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Introducing approximate well dynamics into production optimization for operations scheduling

COMPUTERS & CHEMICAL ENGINEERING 2020年 136卷 106773-000页

作者： Hulse, Eduardo Otte Silva, Thiago Lima Camponogara, Eduardo Rosa, Vinicius Ramos Vieira, Bruno Ferreira Teixeira, Alex Furtado Univ Fed Santa Catarina Dept Automat & Syst Engn CxP 476 BR-88040900 Florianopolis SC Brazil NTNU Dept Geosci & Petr N-7031 Trondheim Norway Petroleo Brasileiro SA BR-20031912 Rio De Janeiro RJ Brazil Petrobras Res Ctr BR-21949900 Rio De Janeiro RJ Brazil

Most of the literature on short-term production optimization concerns the computation of optimal system settings for steady-state operations. Such methodologies are applicable when the scales of time are faster than reservoir dynamics, and slower than the dynamics of top-side equipment. Effectively static problems are solved over time in response to changes in the prevailing conditions, which will remain persistent for long periods. However, when platform conditions change frequently or suddenly possibly due to reduced processing capacity, the dynamics of wells should not be neglected and well operations should be scheduled over time. To this end, this paper proposes a novel mathematical formulation for production optimization when dynamics matters, specifically when wells are shut-in (due to processing capacity drops) and restarted later as the normal conditions are recovered. The effectiveness of the methodology to schedule well operations is assessed by simulation of synthetic and field cases involving an offshore production platform. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Short-term production optimization Startup well operation Approximate well dynamics mixed-integer programming

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The Commute Trip-Sharing Problem

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TRANSPORTATION SCIENCE 2020年第6期54卷 1640-1675页

作者： Hasan, Mohd Hafiz Van Hentenryck, Pascal Legrain, Antoine Univ Michigan Coll Engn Ann Arbor MI 48109 USA Georgia Inst Technol Coll Engn Atlanta GA 30332 USA Polytech Montreal Dept Math & Ind Engn Montreal PQ H3T 1J4 Canada

Parking pressure has been steadily increasing in cities as well as on university and corporate campuses. To relieve this pressure, this paper studies a carpooling platform that would match riders and drivers while guaranteeing a ride back and exploiting spatial and temporal locality. In particular, the paper formalizes the commute trip-sharing problem (CTSP) to find a routing plan that maximizes ride sharing for a set of commute trips. The CTSP is a generalization of the vehicle routing problem with routes that satisfy time-window, capacity, pairing, precedence, ride-duration, and driver constraints. The paper introduces two exact algorithms for the CTSP: a route-enumeration algorithm and a branch-and-price algorithm. Experimental results show that on a high-fidelity real-world data set of commute trips from a midsize city, both algorithms optimally solve small and medium-sized problems and produce high-quality solutions for larger problem instances. The results show that carpooling, if widely adopted, has the potential to reduce vehicle usage by up to 57% and decrease vehicle miles traveled by up to 46% while incurring only a 22% increase in average ride time per commuter for the trips considered.

关键词： ride sharing vehicle routing with time windows column generation branch and price mixed-integer programming

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A polyhedral study of event-based models for the resource-constrained project scheduling problem

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JOURNAL OF SCHEDULING 2020年第2期23卷 233-251页

作者： Tesch, Alexander ZIB Takustr 7 D-14195 Berlin Germany

In this paper, we study event-based mixed-integer programming (MIP) formulations for the resource-constrained project scheduling problem (RCPSP) that represent an alternative to the more common time-indexed model (DDT) (Pritsker et al. in Manag Sci 16(1):93-108, 1969;Christofides et al. in Eur J Oper Res 29(3):262-273, 1987) for the case when the scheduling horizon is large. In contrast to time-indexed models, the size of event-based models does not depend on the time horizon. For two event-based models OOE and SEE introduced by Kone et al. (Comput Oper Res 38(1):3-13, 2011), we first present new valid inequalities that strengthen the original formulation. Furthermore, we state a new event-based model, the Interval Event-Based Model (IEE), and deduce natural linear transformations between all three models. Those transformations yield the strict domination order IEE > SEE > OOE for their respective linear programming relaxations, meaning that the new IEE model has the strongest linear relaxation among all known event-based models. In addition, we show that DDT can be retrieved from IEE by subsequent expansion and projection of the underlying solution space. This yields a unified polyhedral view on a complete branch of MIP models for the RCPSP. Finally, we also compare the computational performance between all models on common test instances of the PSPLIB (Kolisch and Sprecher in Eur J Oper Res 96(1):205-216, 1997).

关键词： Scheduling Resource-constrained project scheduling mixed-integer programming Polyhedral study Event-based models Affine transformations

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Assessing the trade-offs between timber supply and wildlife protection goals in boreal landscapes

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CANADIAN JOURNAL OF FOREST RESEARCH 2020年第3期50卷 243-258页

作者： Yemshanov, Denys Haight, Robert G. Liu, Ning Parisien, Marc-Andre Barber, Quinn Koch, Frank H. Burton, Cole Mansuy, Nicolas Campioni, Fabio Choudhury, Salimur Nat Resources Canada Canadian Forest Serv Great Lakes Forestry Ctr Sault Ste Marie ON P6A 2E5 Canada Forest Serv USDA Northern Res Stn St Paul MN 55108 USA Nat Resources Canada Canadian Forest Serv Northern Forestry Ctr Edmonton AB T6H 3S5 Canada Forest Serv USDA Southern Res Stn Eastern Forest Environm Threat Assessment Ctr Res Triangle Pk NC 27709 USA Univ British Columbia Dept Forest Resources Management Vancouver BC V6T 1Z4 Canada Lakehead Univ Dept Comp Sci Thunder Bay ON P7B 5E8 Canada

Protecting wildlife within areas of resource extraction often involves reducing habitat fragmentation. In Canada, protecting threatened woodland caribou (Rangifer tarandus caribou (Gmelin, 1788)) populations requires preserving large areas of intact forest habitat, with some restrictions on industrial forestry activities. We present a linear programming model that assesses the trade-off between achieving an objective of habitat protection for caribou populations while maintaining desired levels of harvest in forest landscapes. The habitat-protection objective maximizes the amount of connected habitat that is accessible by caribou, and the forestry objective maximizes net revenues from timber harvest subject to even harvest flow, a harvest target, and environmental sustainability constraints. We applied the model to explore the habitat protection and harvesting scenarios in the Cold Lake caribou range, a 6726 km(2) area of prime caribou habitat in Alberta, Canada. We evaluated harvest scenarios ranging from 0.1 Mm(3).year(-1) to maximum sustainable harvest levels over 0.7 Mm(3).year(-1) and assessed the impact of habitat protection measures on timber supply costs. Protecting caribou habitat by deferring or reallocating harvest increases the timber unit cost by Can$1.1-2.0 m(-3). However, this impact can be partially mediated by extending the harvest to areas of oil and gas extraction to offset forgone harvest in areas of prime caribou habitat.

关键词： caribou recovery network flow model mixed-integer programming Steiner network landscape connectivity harvestc scheduling model I wildlife habitat protection Canada

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Resilience through multicast - An optimization model for multi-hop wireless sensor networks

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AD HOC NETWORKS 2020年 107卷 102239-102239页

作者： Ostrowski, Bartlomiej Pioro, Michal Tomaszewski, Artur Fitzgerald, Emma Warsaw Univ Technol Inst Telecommun Warsaw Poland Lund Univ Dept Elect & Informat Technol Lund Sweden

In this paper we study resilience of TDMA-based wireless sensor networks to node failures. We investigate exploiting mutlicast routing for providing redundancy in the number of gateways used by data streams, so as to protect them against gateway failures. To do this, we develop an optimization model aiming at packet traffic throughput maximization composed of three mixed-integer programming problem formulations and corresponding solution algorithms. The first formulation assumes predefined multicast routing trees and fixed gateway locations, and optimizes the TDMA frame composition. The second one adds routing trees optimization, while the third formulation additionally includes optimization of gateway locations. We present a numerical study illustrating effectiveness of our model, including efficiency of the solution algorithms. Our results show that substantial gains in traffic throughput can be obtained by including routing trees optimization and optimal gateways selection, especially for high levels of redundancy. (c) 2020 Elsevier B.V. All rights reserved.

关键词： Wirelesssensornetworks Resilience Traffic throughput Multicast mixed-integer programming IoT

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A Distributed Framework for Solving and Benchmarking Security Constrained Unit Commitment With Warm Start

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IEEE TRANSACTIONS ON POWER SYSTEMS 2020年第1期35卷 711-720页

作者： Chen, Yonghong Wang, Fengyu Ma, Yaming Yao, Yiyun Midcontinent Independent Syst Operator Inc Carmel IN 46032 USA IIT Dept Elect & Comp Engn Chicago IL 60616 USA

This paper discusses several methods to improve commercial optimization solver performance on day-ahead security constrained unit commitment through warm start and lazy constraint settings. Data analytics is performed to greatly improve the quality of the initial commitment solution and lazy constraint setting. A distributed optimization framework is proposed to take advantage of the diversity from prevalent solvers (GUROBI and CPLEX) and different warm start strategies. A systematic distribution profile based benchmarking method is also proposed.

关键词： MISO communication Security Data analysis Optimization Production Load modeling Benchmark testing mixed-integer programming performance benchmark security-constrained unit commitment tight formulation

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On the Derivation of Continuous Piecewise Linear Approximating Functions

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INFORMS JOURNAL ON COMPUTING 2020年第3期32卷 531-546页

作者： Kong, Lingxun Maravelias, Christos T. Univ Wisconsin Dept Chem & Biol Engn Madison WI 53706 USA

We propose mixed-integer programming models for fitting univariate discrete data points with continuous piecewise linear (PWL) functions. The number of approximating function segments and the locations of break points are optimized simultaneously. The proposed models include linear constraints and convex objective function and, thus, are computationally more efficient than previously proposed mixed-integer nonlinear programming models. We also show how the proposed models can be extended to approximate univariate functions with PWL functions with the minimum number of segments subject to bounds on the pointwise error.

关键词： mixed-integer programming data fitting large-scale

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Minimizing a sum of clipped convex functions

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OPTIMIZATION LETTERS 2020年第8期14卷 2443-2459页

作者： Barratt, Shane Angeris, Guillermo Boyd, Stephen Stanford Univ Dept Elect Engn Stanford CA 94305 USA

We consider the problem of minimizing a sum of clipped convex functions. Applications of this problem include clipped empirical risk minimization and clipped control. While the problem of minimizing the sum of clipped convex functions is NP-hard, we present some heuristics for approximately solving instances of these problems. These heuristics can be used to find good, if not global, solutions, and appear to work well in practice. We also describe an alternative formulation, based on the perspective transformation, that makes the problem amenable to mixed-integer convex programming and yields computationally tractable lower bounds. We illustrate our heuristic methods by applying them to various examples and use the perspective transformation to certify that the solutions are relatively close to the global optimum. This paper is accompanied by an open-source implementation.

关键词： Convex optimization mixed-integer programming Robust statistics

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Impact of battery technological progress on electricity arbitrage: An application to the Iberian market

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APPLIED ENERGY 2020年第0期260卷 114273-000页

作者： Arcos-Vargas, Angel Canca, David Nunez, Fernando Univ Seville Sch Engn Dept Ind Engn & Management Sci Seville Spain

Recent technological advances in power electronics and electrical storage have increased interest in the arbitrage business based on Battery Energy Storage Systems. With this objective, the present work develops a mixed-integer Linear programming model for obtaining optimal electricity sale\purchase strategies with batteries. For each configuration (battery size /inverter size), the model provides an optimal trading strategy. Using this strategy for different configurations and with the current market prices, some financial indicators are calculated in order to select the optimal configuration. Finally, our analysis considers the significant technological progress that has occurred in recent years, the effects on profitability of a reduction in the battery cost, and of an improvement both in the round-trip efficiency and in the battery's lifetime (in terms of the number of cycles). The results indicate that, with current technology, the optimal inverter size for a 10 MWh battery is 3 MW, although, if technological progress continues at the current rate, the arbitrage of electricity by using batteries is expected to be viable from 2024 onwards. Additionally, the effects that different technological improvements (cost, useful life and losses) will have on profitability are calculated,;for example, it is observed that an improvement of 1.6% of the round-trip efficiency and an increase of 1000 life cycles will provide an average increase of 16,000 (sic) and 75,000 (sic), respectively, in terms of Net Present Value.

关键词： Electricity markets Arbitrage business BESS mixed-integer programming Technological progress

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Blocking Cyclic Job-Shop Scheduling Problems

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ALGORITHMS 2022年第10期15卷 375-375页

作者： Elmi, Atabak Thiruvady, Dhananjay R. Ernst, Andreas T. Deakin Univ Sch Informat Technol Fac Sci Engn & Built Environm Geelong Vic 3125 Australia Monash Univ Fac Sci Sch Math Melbourne Vic 3800 Australia

Cyclic scheduling is of vital importance in a repetitive discrete manufacturing environment. We investigate scheduling in the context of general cyclic job shops with blocking where there are no intermediate buffers between the machines. We also consider sequence-dependent setups (anticipatory and nonanticipatory), which commonly appear in different manufacturing environments. The choice of blocking condition, that is whether the sequence-dependent setups are anticipatory or not, significantly impacts the optimal schedules. We provide a novel mixed-integer programming (MIP) model for the above problem, namely blocking cyclic job-shop scheduling. Furthermore, we study the impact of sequence-dependent setups in this research. The problem is analysed in detail with respect to anticipatory and nonanticipatory setups and the efficiency of the proposed model is investigated via a computational study that is conducted on a set of randomly generated problem instances. The proposed MIP models are capable of solving small-to-medium-sized problems. Moreover, the analysis presented demonstrates that anticipatory setups directly affect blocking conditions, since intermediate buffers between the machines are not present. Hence, in systems with anticipatory setups, cycle times increase to a greater extent compared to systems with nonanticipatory setups.

关键词： cyclic scheduling job-shop scheduling sequence-dependent setups blocking conditions mixed-integer programming

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