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Use of Optimization Modeling to Assess the Effect of Timber and Carbon Pricing on Harvest Scheduling, Carbon Sequestration, and Net Present Value of Eucalyptus Plantations

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FORESTS 2021年第6期12卷 651页

作者： Hirigoyen, Andres Acuna, Mauricio Rachid-Casnati, Cecilia Franco, Jorge Navarro-Cerrillo, Rafael Inst Nacl Invest Agopecuaria INIA Tacuarembo Ruta 5 Km 386 Tacuarembo 60000 Uruguay Univ Sunshine Coast Forest Res Inst Locked Bag 4 Maroochydore Qld 4558 Australia Univ Republ Fac Agron Paysandu 60000 Uruguay Univ Cordoba Dept Forestry Engn Dendrochronol & Climate Change Lab Silviculture DendrodatLab ERSAF Campus RabanalesCrta 4Km 396 E-14071 Cordoba Spain

Quantifying the impact of carbon (C) and timber prices on harvest scheduling and economic returns is essential to define strategies for the sustainable management of short-rotation plantations so that they can provide timber products and contribute to C sequestration. In this paper, we present a mixed-integer linear programming model that optimizes harvest scheduling at the forest level, C sequestration, and Net Present Value (NPV) over a planning period of up to 15 years. The model included revenue from the sale of timber (pulplogs) and credits from the net C sequestered during the life of the stands. In addition, plantation establishment, management, harvesting, and transportation costs were included in the analysis. The study area comprised 88 Eucalyptus grandis W. Hill and Eucalyptus dunnii Maiden stands located in Uruguay, totaling a forest area of nearly 1882 ha. The study investigated the impact of C and timber prices on NPV, harvest schedules, stands' harvest age, timber flows to customers, and C sequestered per period. The maximum NPV among all the scenarios evaluated (USD 7.53 M) was calculated for a C price of 30 USD t(-1), an interest rate of 6%, and a timber price of 75 USD m(-3). This was USD 2.14 M higher than the scenario with the same parameters but that included only revenue from timber. C prices also impacted stands' harvest age, C sequestration, and timber flows delivered to end customers. On average, in scenarios that included C prices, timber flows and C sequestration increased by 15.4 and 12.1%, respectively, when C price increased from 5 to 30 USD t(-1). These results demonstrate that harvest scheduling, harvest age, and NPV are very sensitive to C and timber, and that the best economic returns are obtained when the stands are managed to maximize timber production and C sequestration.

关键词： timber harvest scheduling mixed-integer programming harvest age carbon sequestration

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Service operation vessels for offshore wind farm maintenance: Optimal stock levels

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2021年 146卷 111158-111158页

作者： Neves-Moreira, Fabio Veldman, Jasper Teunter, Ruud H. Univ Groningen POB 800 NL-9700 AV Groningen Netherlands

Service operation vessels are becoming the dominant mode for the maintenance of most offshore wind farms. To minimize turbine downtime, it is essential to bring the right components to the wind farm, while budget and volume constraints prohibit having excess inventories on board. This setting can be interpreted as a repair kit problem, which seeks to define a set of components that may be necessary for on-site maintenance operations in a given time period during which emergency resupply is costly. Current repair kit problem approaches however, do not cater sufficiently for some of the characteristics of offshore wind farm maintenance, including weather dependent deterioration and the possibility to perform emergency resupplies. We propose mixed-integer programming models both to determine (tactical model) and validate (operational model) repair kits when maintenance operations are performed under different weather conditions. The models are flexible enough to be used with real world data considering multiple turbines composed of different deteriorating components, service operation vessels characteristics (speed and volumetric capacity), different weather conditions, and emergency resupplies. An important feature of this approach is its ability to consider detailed maintenance and vessel routing operations to test and validate repair kits in realistic wind farm environments. We provide valuable insights on the composition of repair kits and on relevant business indicators for a set of different scenarios. The practical implications are that repair kits should be adapted depending on weather forecasts and that considerable downtime reductions can be achieved by allowing emergency resupplies.

关键词： Offshore wind energy Repair kit problem Weather conditions mixed-integer programming Matheuristic Managerial insights

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Stochastic Convex Cone programming for Joint Optimal BESS Operation and Q-Placement in Net-Zero Microgrids

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ENERGIES 2024年第17期17卷 4292页

作者： Mohammadyari, Milad Eskandari, Mohsen Univ Tehran Dept Elect Engn Tehran *** Iran Univ New South Wales Sydney Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

Microgrids have emerged as a pivotal solution in the quest for efficient, resilient, and sustainable energy systems. Comprising diverse distributed energy resources, microgrids present a compelling opportunity to revolutionize how we generate, store, and distribute electricity, while simultaneously reducing carbon footprints. This paper proposes an optimal battery energy storage system (BESS) management scheme, along with capacitor placement for reactive power (Q)-compensation, and scheduling for the purpose of a renewable-based microgrid's loss minimization. The proposed model evaluates the impact of BESS management on energy efficiency and analyzes how optimal scheduling of BESS influences system losses. Furthermore, it investigates the coordinated planning and operation of active assets within the microgrid, such as controllable capacitor banks, in enhancing overall efficiency. The model is formulated as a mixed-integer second-order cone programming (MISOCP) problem which is solved for both deterministic and stochastic generation and consumption data. The proposed model is tested on a 21-bus microgrid comprising photovoltaic and hydropower energy resources, and the efficacy of the model is approved by several case studies. The simulation results show that the proposed method can reduce microgrid energy losses by approximately 12 percent using the deterministic approach and around 14 percent with the stochastic approach.

关键词： battery energy storage system (BESS) cone programming microgrid mixed-integer programming power losses renewable energy resources (RESs) stochastic optimization

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An Integrated Predictive Maintenance and Operations Scheduling Framework for Power Systems Under Failure Uncertainty

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INFORMS JOURNAL ON COMPUTING 2024年第5期36卷 1335-1358页

作者： Okumusoglu, Bahar Cennet Basciftci, Beste Kocuk, Burak Sabanci Univ Ind Engn Program TR-34956 Istanbul Turkiye Univ Iowa Tippie Coll Business Dept Business Analyt Iowa City IA 52242 USA

Maintenance planning plays a key role in power system operations under uncertainty as it helps providers and operators ensure a reliable and secure power grid. This paper studies a short-term condition -based integrated maintenance planning with operations scheduling problem while considering the possible unexpected failure of generators as well as transmission lines. We formulate this problem as a two -stage stochastic mixedinteger program with failure scenarios sampled from the sensor -driven remaining lifetime distributions of the individual system elements whereas a joint chance constraint consisting of Poisson Binomial random variables is introduced to account for failure risks. Because of its intractability, we develop a cutting -plane method to obtain an exact reformulation of the joint chance constraint by proposing a separation subroutine and deriving stronger cuts as part of this procedure. We also derive a second -order cone programming -based safe approximation of this constraint to solve large-scale instances. Furthermore, we propose a decomposition algorithm implemented in parallel fashion for solving the resulting stochastic program, which exploits the features of the integer L-shaped method and the special structure of the maintenance and operations scheduling problem to derive valid and stronger sets of optimality cuts. We further present preprocessing steps over transmission line flow constraints to identify redundancies. To illustrate the computational performance and efficiency of our algorithm compared with more conventional maintenance approaches, we design a computational study focusing on a weekly plan with daily maintenance and hourly operational decisions involving detailed unit commitment subproblems. Our computational results on various IEEE instances demonstrate the computational efficiency of the proposed approach with reliable and cost-effective maintenance and operational schedules.

关键词： mixed-integer programming joint chance constraints condition-based maintenance unit commitment power systems stochastic programming

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A chance-constrained dial-a-ride problem with utility-maximising demand and multiple pricing structures

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2022年第0期158卷 102601-102601页

作者： Dong, Xiaotong Chow, Joseph Y. J. Waller, S. Travis Rey, David UNSW Sch Civil & Environm Engn Sydne NSW 2052 Australia NYU Tandon Sch Engn C2SMART Univ Transportat Ctr Brooklyn NY USA Univ Cote Azur SKEMA Business Sch Sophia Antipolis Campus Sophia Antipolis Campus Nice France

The classic Dial-A-Ride Problem (DARP) aims at designing the minimum-cost routing that accommodates a set of user requests under constraints at an operations planning level, where users' preferences and revenue management are often overlooked. In this paper, we present a mechanism for accepting/rejecting user requests in a Demand Responsive Transportation (DRT) context based on the representative utilities of alternative transportation modes. We consider utility-maximising users and propose a mixed-integer programming formulation for a Chance Constrained DARP (CC-DARP), that captures users' preferences via a Logit model. We further introduce class-based user groups and consider various pricing structures for DRT services. A customised local search based heuristic and a matheuristic are developed to solve the proposed CC-DARP. We report numerical results for both DARP benchmarking instances and a realistic case study based on New York City yellow taxi trip data. Computational experiments performed on 105 benchmarking instances with up to 96 nodes yield average profit gaps of 2.59% and 0.17% using the proposed local search heuristic and matheuristic, respectively. The results obtained on the realistic case study reveal that a zonal fare structure is the best strategy in terms of optimising revenue and ridership. The proposed CC-DARP formulation provides a new decision-support tool to inform on revenue and fleet management for DRT systems on a strategic planning level.

关键词： Dial-a-ride problem Demand-responsive transportation Chance constraint mixed-integer programming Local search Matheuristic

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Optimization of the Sino-Europe Transport Networks Under Uncertain Demand

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ASIA-PACIFIC JOURNAL OF OPERATIONAL RESEARCH 2021年第3期38卷 2140019-2140019页

作者： Nie, Qing Liu, Songyun Qian, Qiyuan Tan, Zheyi Wang, Huiwen Shanghai Univ Sch Management Shanghai Peoples R China

This paper studies a consolidation center selection and cargo transportation optimization problem of the Sino-Europe railway express. It takes account of demand uncertainty and multiple cost factors, such as transportation cost, time cost, waiting cost before consolidation, penalty cost of not full load after distribution, track changing cost, and customs clearance fee. A complicated mixed-integer programming (MIP) model is presented to describe the problem. Then a solution method based on binary particle swarm optimization (BPSO) is designed to solve the model of different scales of cases. Extensive numerical experiments generated from real-world data are conducted to validate the effectiveness of the proposed model. Moreover, we compare the efficiency of the solution method with a commercial solver and a heuristic algorithm based on variable neighborhood search (VNS). Results show that our solution method can optimally solve the problem in small-scale cases and get near-optimal solutions for large-scale problem instances. The proposed mathematical model and the calculation results may provide valuable insights for both business owners and government.

关键词： Sino-Europe railway express consolidation centers mixed-integer programming binary particle swarm optimization

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Solution of algebraic systems of disjunctive equations

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COMPUTERS & CHEMICAL ENGINEERING 1996年第Sup1期20卷 S339-S344页

作者： Grossmann, IE Turkay, M Department of Chemical Engineering Carnegie Mellon University Pittsburgh PA 15213 USA

This paper considers the solution of systems of equations that are expressed by the two sets: a global rectangular system of equations involving more variables than equations, and a set of conditional equations that are expressed as disjunctions. The set of disjunctions are given by equations and inequalities, where the latter define the domain of validity of the equations. In this way the solution of such a system is defined by variables x satisfying the rectangular equations, and exactly one set of equations for each of the disjunctions. This paper focuses mainly in the solution of systems of linear disjunctive equations. Using a convex hull representation of the disjunctions, the disjunctive system of equations is converted into an MILP problem. A sufficient condition is presented under which the model is shown to be solvable as an LP problem. The extension of the proposed method to nonlinear disjunctive equations is also discussed. The application of the proposed algorithms are illustrated with several examples.

关键词： disjunctive programming mixed-integer programming

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A Bayesian framework for molecular strain identification from mixed diagnostic samples

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INVERSE PROBLEMS 2018年第10期34卷 105009-105009页

作者： Mustonen, Lauri Gao, Xiangxi Santana, Asteroide Mitchell, Rebecca Vigfusson, Ymir Ruthotto, Lars Emory Univ Dept Math & Comp Sci 400 Dowman Dr Atlanta GA 30322 USA Georgia Inst Technol Sch Ind & Syst Engn 755 Ferst Dr Atlanta GA 30318 USA Emory Univ Nell Hodgson Woodruff Sch Nursing 1520 Clifton Rd Atlanta GA 30322 USA Reykjavik Univ Sch Comp Sci Menntavegi 1 IS-101 Reykjavik Iceland

We provide a mathematical formulation and develop a computational framework for identifying multiple strains of microorganisms from mixed samples of DNA. Our method is applicable in public health domains where efficient identification of pathogens is paramount, e.g. for the monitoring of disease outbreaks. We formulate strain identification as an inverse problem that aims at simultaneously estimating a binary matrix (encoding presence or absence of mutations in each strain) and a real-valued vector (representing the mixture of strains) such that their product is approximately equal to the measured data vector. The problem at hand has a similar structure to blind deconvolution, except for the presence of binary constraints, which we enforce in our approach. Following a Bayesian approach, we derive a posterior density. We present two computational methods for solving the non-convex maximum a posteriori estimation problem. The first one is a local optimization method that is made efficient and scalable by decoupling the problem into smaller independent subproblems, whereas the second one yields a global minimizer by converting the problem into a convex mixed-integer quadratic programming problem. The decoupling approach also provides an efficient way to integrate over the posterior. This provides useful information about the ambiguity of the underdetermined problem and, thus, the uncertainty associated with numerical solutions. We evaluate the potential and limitations of our framework in silico using synthetic and experimental data with available ground truths.

关键词： Bayesian inverse problems mixed-integer programming molecular biology

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Strip based compact formulation for two-dimensional guillotine cutting problems

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COMPUTERS & OPERATIONS RESEARCH 2023年 149卷

作者： Rodrigues, Carlos Diego Cherri, Adriana Cristina Araujo, Silvio Alexandre de Univ Fed Ceara Ctr Ciencias Campus PiciBloco 910 BR-60440900 Fortaleza CE Brazil Univ State Sao Paulo UNESP Fac Ciencias Ave Eng Luis Edmundo Carrijo Coube 14-01 Vargem L BR-17033360 Bauru SP Brazil Univ State Sao Paulo UNESP Inst Biociencias Letras & Ciencias Exatas R Cristovao Colombo 2265 Jardim Nazareth BR-15054000 Sao Jose Do Rio Preto SP Brazil

In this paper, we present a new mixed integer programming formulation for two-dimensional guillotine cutting and packing problems based on a strip decomposition of the rectangular spaces. The formulation covers most of the main related problems in the literature by setting parameters accordingly. The strip concept commonly used for problems with a limited number of stages (two or three stages) has been, in this study, extended to a general concept that can cover an arbitrary number of stages. Due to the easy adaptation of the proposed formulation, which is presented in both heuristic and exact version, an extensive set of computational experiments was performed with instances for the two-dimensional guillotine knapsack, cutting stock and bin packing problems. The experiments, which involve existing benchmark instances and randomly generated instances from the literature, showed that our proposed formulation, considering its heuristic version, can output competitive results both in terms of computational time and percentage of optimally solved instances.

关键词： mixed-integer programming Two-dimensional cutting problems Guillotine cuts Mathematical modeling

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Benchmarking Procurement Cost Saving Strategies for Wood Supply Chains

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FORESTS 2021年第8期12卷 1086页

作者： Kogler, Christoph Schimpfhuber, Sophie Eichberger, Clemens Rauch, Peter Univ Nat Resources & Life Sci Inst Prod & Logist A-1180 Vienna Austria Karl Franzens Univ Graz Inst Prod & Operat Management A-8010 Graz Austria

Intense international competition pushes the actors of wood supply chains to implement efficient wood supply chain management incorporating coordinated cost-saving strategies to remain competitive. In order to observe the effects of individual and coordinated decision making, mixed-integer programming models for forestry, round-wood transport, and the wood-based industry were developed and integrated. The models deal with operational planning issues regarding production, harvest, and transport and are solved sequentially for individual cost optimization of each wood supply chain actor as well as simultaneously by a combined model representing joint cost optimization in an integrated wood supply chain. This allows for the first time, benchmarking relative cost-saving potential of the wood procurement strategies coordinated transports, integrated supply chains, satellite stockyards, and higher truck payloads within a single case study setting. Based on case study data from southern Austria, results show the advantages of an integrated supply chain with a cost-saving potential of up to 24%. Higher truck payloads reinforce this potential and enable up to 40% savings compared to the predominant wood procurement situation in Central Europe. Wood supply chain integration for Central European circumstances seems to be feasible only for a limited consortium of a few companies, for example when restricted to a wood-buying syndicate supplying several industry plants or a few large forest enterprises, especially as both groups are commonly steering wood transport on their own. Consequently, further research on the challenging task of implementing integrated supply chains using the opportunities of digitalization to realize existing cost savings potential by deepening cooperation and intensifying information exchange is needed.

关键词： wood supply chain management optimization mixed-integer programming decision support wood-based industry logistics supply chain integration coordinated round-wood transport truck payload satellite stockyards

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