Smarter Natural Resources - Natural Resources Optimization under Uncertainty
The mission of the Natural Resources Optimization group is to develop both theoretical and applied research in the area of mathematical optimization so as to enable companies and enterprises whose business activities rely on the discovery and exploration of natural resources to be more efficient, productive and informed regarding potential sources of risks while ensuring environmental sustainability.
Across the world, the discovery and exploration of natural resources are at the heart of business activities conducted by several companies and enterprises that, over the years, have experienced increasing pressures in terms of declining margins, complex technical challenges and ever-changing social, environmental and economic requirements. In this context, optimization provides mathematical techniques that are capable of supporting decision-making processes related to business problems by determining optimal solutions from a huge number of potential alternatives that would otherwise remain unexplored.
The Natural Resources Optimization area focuses its theoretical research on the development of modeling frameworks, methods and algorithms for linear, nonlinear and integer programming. Applied research aims at combining and extending the powerful tools provided by mathematical optimization in order to address specific challenges faced by companies and enterprises when dealing with business problems such as the asset allocation, operational scheduling and investment planning.
A fundamental aspect of real-world decision-making processes that motivates and is at the core of the research conducted by the Natural Resources Optimization group is the correct characterization and incorporation of relevant sources of uncertainty into the mathematical optimization models developed to tackle particular business problems. Uncertainty is a key element that pervades business decisions along operational, tactical and strategic levels, though it is often either neglected or treated in manners which do not correctly capture potential threats and opportunities. In this sense, research interests within the Natural Resources Optimization group include the development of solution algorithms for stochastic programming and optimization, robust optimization, scenario generation techniques, etc. Also in the same direction, there is significant interest on leveraging the capabilities of High Performance Computing to solve very-large-scale problems that may arise when dealing with complex and detailed applications.
Impacts and benefits
The application of mathematical optimization models and methods to business problems – possibly coupled with a wide range of techniques from diverse knowledge areas such as statistics, machine learning, weather modeling, geo-sciences, computational mechanics and finance, for example – lead to consistent and superior strategies that achieve, for example, cost minimization, more efficient asset utilization and/or risk-constrained profit maximization. As possible examples, the subsections below present a non-extensive list of applications encountered across various domains.
Oil and gas: production strategy optimization, offshore logistics, field development, manpower scheduling, project portfolio optimization.
Renewable energy sources: design of wind farms, energy trading and risk management, operations planning and scheduling.
Agriculture: precision agriculture, crop scheduling, water / fertilizer / pesticide application, trading and hedging strategies for commodities and future markets.
Mining: operational planning, production strategy optimization, supply chain and logistics operations, mine evaluation.
Water: design of transportation infrastructure, maintenance scheduling.
Achieving Excellence in Offshore Logistics – Dirk Claesses, Jose Favilla, Ulisses Mello, Bruno Flach – SPE Intelligent Energy Conference, 2012.
A Multistage Linear Stochastic Programming Model for Optimal Corporate Debt Management – Davi Valladão, Álvaro Veiga, Geraldo Veiga – XVI CLAIO / XLIV SBPO, 2012.
Network Resiliency and Reinforcement Decisions in Disaster-Prone Areas – Bruno Flach, Marcus Poggi de Aragão – XVI CLAIO / XLIV SBPO, 2012.
Time consistent risk averse dynamic decision models: an economic interpretation – Birgit Rudloff, Alexandre Street, Davi Valladão – XVI CLAIO / XLIV SBPO, 2012.
A Linear Stochastic Programming Model for Optimal Leveraged Portfolio Selection – Davi Valladão, Álvaro Veiga, Alexandre Street – XVI CLAIO / XLIV SBPO, 2012.
“Hydro-Thermal Scheduling under CO2 Emission Constraints” –Rebennack, S., Flach, B., Pereira, M., Pardalos, P. – Aceito para publicação no jornal IEEE Transactions on Power Systems – 2011.
Time consistency and risk averse dynamic decision models: Interpretation and practical consequences – Birgit Rudloff, Alexandre Street, Davi Valladão – Optimization Online, 2011.
“Optimal Expansion of CO2 Emission Constrained Hydro-dominated Power Systems” – Rebennack, S., Flach, B., Pereira, M. – International Conference on Operations Research – 2011.
“Integrated electricity-gas operations planning in long-term hydroscheduling based on stochastic models” – Barroso, L., Bezerra, B., Flach, B., Kelman, R., Lattore, M., Campodonico, N., Pereira, M. – Power Systems Handbook, eds. Pardalos, P, Rebennack, S., Iliadis, N., Pereira, M. – 2010.
Equity Valuation and Debt Selection via Stochastic Programming – Davi Valladão, Álvaro Veiga, Geraldo Veiga – INFORMS, 2010.
“Long Term Optimal Allocation of Hydro Generation for a Price-Maker Company in a Competitive Market: Latest Developments and a SDDP approach” – Flach, B., Barroso, L. e Pereira, M. – IET Generation, Transmission & Distribution – 2010.
Corporate Cash Holding, Production and Investments Applied to the Agribusiness Sector – Astrid Prajogo, John Mulvey, Davi Valladão, INFORMS, 2010.
“On a class of stochastic programs with endogenous uncertainty: theory, algorithm and application” – Flach, B., Poggi, M. – Monografias em Ciência da Computação, PUC-Rio – 2010.
“Risk Constrained Portfolio Selection of Renewable Sources in Hydrothermal Electricity Markets” – Street, A., Barroso, L., Flach, B., Pereira, M., Granville, S. – IEEE Transactions on Power Systems – 2009.
Optimum Allocation and Risk Measure in an Asset Liability Management Model for a Pension Fund Via Multistage Stochastic Programming and Bootstrap – Davi Valladão, Álvaro Veiga – XVI International Conference on Forecasting Financial Markets: Advances for Exchanges Rates and Interest Rates, 2009.
“Stochastic Programming with Endogenous Uncertainty: an Application in Humanitarian Logistics” – Stochastic Programming School – Itália, 2009.
Corporate Asset Liability Management (ALM) via Stochastic Programming – Davi Valladão, Álvaro Veiga – The 20th International Symposium of Mathematical Programming (ISMP), 2009.
Optimum Allocation and Risk Measure in an Asset Liability Management Model for a Pension Fund Via Multi-stage Stochastic Programming and Bootstrap Davi Valladão, Álvaro Veiga – SMAI-MODE, 2008.
“Optimization of linehaul network operations for less-than-truckload carriers” with Cunha, P., Aragao, M.V.P – XXXVIII Annual Conference of the Italian Operations Research Society – Itália, 2007.
A stochastic programming model for ALM of a pension fund in Brazilian context Davi Valladão, &Aatildelvaro Veiga, Ana T. Vasconcellos, Camila Spinassé 11th International Congress on Insurance: Mathematics and Economics, 2007.
“Integrated Electricity-Gas Operations Planning in Hydrothermal Systems” – Barroso, L., Bezerra, B., Flach, B., Kelman, R., Pereira, M., Latorre, M., Campodónico, N. – X Simpósio de Especialistas em Planejamento da Operação e Expansão Elétrica – Brasil, 2006.
“Integrated Electricity and Gas Adequacy Planning in Brazil: Technical and Economical Aspects” – Barroso, L., Bezerra, B., Flach, B., Kelman, R., Binato, S., Bressane, J.M., Pereira, M. – IEEE Power Engineering Society General Meeting – EUA, 2005.