Overview and Opportunities of Operations Research (OR/MS) in Sustainability and the Environment
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1 Overview and Opportunities of Operations Research (OR/MS) in Sustainability and the Environment Alexander Engau, Ph.D. Mathematical and Statistical Sciences University of Colorado Denver CSIS SEMINAR, FEBRUARY 7, 2012 Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 0 of 16
2 What s In A Name Image taken from Wordle image of the most popular words in Australia s Defence Science and Technology Organisation s (DSTO) OR Code of Best Practices Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 1 of 16
3 Operations Research and Management Science (OR/MS) OR/MS seeks to provide decision and policy makers with mathematical models and analytic tools to increase efficiencies and help make better decisions. Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 2 of 16
4 Operations Research Models and Methods Super Simulation (Stochastic MMs) uses and designs random experiments to model uncertainties powerful tool to study stochastic and highly complex phenomena also includes stochastic processes, Markov chains, queueing theory Global Optimization (Deterministic MMs) formulates decision problems using objectives and constraints determines best (maximum and minimum) values of alternatives also includes stochastic optimization, optimal control, game theory Prices, Probabilities & Predictions (Statistical MMs) data analysis bridges between stochastic and deterministic MMs uses data mining and forecasting to provide insight and predictions estimates, measures, quantifies, and analyzes uncertainties and risk Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 3 of 16
5 Computation and The Curse of Dimensionality The execution, analysis, or solution of many stochastic and deterministic models is subject to the curse of dimensionality. Let a computer evaluate and compare 1 million alternatives/second. Now use it to solve problems by enumerating all possible outcomes. Example 1: Shortest Path Problems Given a set of points in the plane, find the shortest path from A to B. 10 points: computation takes less than a second 20 points: computation takes over 39,000 years Example 2: Portfolio Selection Problems Given 100 stocks, find the best portfolios by evaluating risk and return with 5 stocks: 1.25 minutes with 10 stocks: 200 days with 15 stocks: 8,000 years with 16 stocks: 42,000 years Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 4 of 16
6 Research Focus on Algorithms and Mathematical Programming A major part of my research is the development, analysis, implementation, and testing of new efficient algorithms. dynamic, integer, (non)linear, stochastic programming (max/min)imize f (x) subject to g(x) 0, h(x) = 0 Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 5 of 16
7 Multiobjective (Criteria) Programming/Optimization/Decision-Making Optimization is the best possible achievement of (one or multiple) objectives or goals by making decisions on available alternatives. Optimization is part of decision making (aid, analysis, support) Best depends on preferences and trade offs between criteria Example 1: Portfolio Selection maximize return (expected rate) minimize risk (stand. deviation) Example 2: Vehicle Design maximize performance maximize (fuel) efficiency Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 6 of 16
8 Research Focus on Trade-Off Models and Decomposition Methods When there are multiple objectives (almost always in practice), there may be infinitely many efficient solutions to choose from. Use social choice and utility theory from economics to model a priori trade-offs that reduce computational and decisional requirements. Use decomposition techniques to facilitate trade offs and preference articulation before integrating partial decisions into overall solution. Application to Multidisciplinary Design Optimization (MDO) multi-scale project with modeling and simulation groups of U.S. Army developed a multi-disciplinary system-of-systems framework every discipline has its own objectives and decision criteria Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 7 of 16
9 Challenges of MDO (and Project or Operations Management in General) Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 8 of 16
10 Possible Connections to Current CSIS/SEIS Research Themes From the Social-Ecological-Infrastructural Systems (SEIS) framework: Environmental Footprint Research statistical or stochastic simulation modeling optimization modeling / methods / number crunching? Multi-Scale Risk and Vulnerabilities statistical or stochastic MMs for risk evaluation and integration multicriteria MMs for analyzing and compromising risk-chance trade offs Spatial Infrastructure Modeling (environment - industry - city - home) multi-disciplinary decompositions and system-of-systems approaches simultaneous consideration of multiple objectives and decision criteria Social Actors and Governance preferences and trade-off models in multiple-criteria decision-making study of decision behaviors in groups based on multi-player game theory Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 9 of 16
11 One-Page Summaries of Other Projects Operations Management: volunteer assignment and scheduling for Denver B-Cycle Bike-Sharing Program Process Engineering/OM: optimal collision avoidance of operational spacecraft in near-real time Energy Systems/Sustainability Engineering: optimization of a hybrid wind/solar generation system for lifespan extension Sustainability Engineering/ES/PE/ OM: oil load dispatch and hauling optimization at the Wattenberg Field/Denver-Julesburg Basin Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 10 of 16
12 Volunteer Assignment and Scheduling for Denver B-Cycle Bike Sharing Joint work with Matt Kaspari, Kaspo Inc., and Piep Van Heuven, Denver B-Cycle The Problem volunteers were critical in early phases of Denver BC assignments must consider all preferences and conflicts Approach and Methods developed survey to collect all relevant volunteer data used goal programming for feasible/optimal scheduling Results and Impact fast and fair assignment simulation model was used to analyze long-term effect Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 11 of 16
13 Optimization of Wind/Solar Generation Systems for Lifespan Extension Joint Work with Daniel Mejía and Fernando Mancilla-David (both EE, UC Denver) The Problem smart grid operation and design are non-trivial tasks disturbances damage and shorten equipment lifespan Approach and Methods minimize (nonlinear) wind generator harmonics and charging profile deviations decompose full optimization into single subcomponents Results and Impact scenario-based simulation validates optimal solutions Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 12 of 16
14 Optimal Collision Avoidance of Operational Spacecraft in Near-Real Time Spring 2011 UC Denver Math Clinic sponsored by SpaceNav LLC., Boulder, CO The Problem debris (space junk) poses threat to space operations critical need for collision risk management tools Approach and Methods prediction of conjunction events and collision risks optimization of maneuvers for safe collision avoidance Results and Impact prototype software for risk analysis and optimization student continued as intern Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 13 of 16
15 Oil Load Dispatch and Hauling Optimization at Denver-Julesburg Basin Spring 2012 UC Denver Math Clinic sponsored by Noble Energy Inc., Houston, TX The Problem Noble plans to invest $8 billion over the next five years in the DJ Basin need enhanced tools to plan and support their operational decisions Approach and Methods use a network flow model for transportation problem handle uncertainties using simulation and stochastics Results and Impact none yet (work in progress) Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 14 of 16
16 Improving Water Release Policies on the Delaware River Through OR The Delaware River Basin Commission, INFORMS 2010 Edelman Award Finalist... recognizes outstanding examples of innovative OR that improves [... ] organizations and the people that it serves. The Problem: How much water can be released from river reservoirs to sustain wild trout and American shad populations; to ensure sufficient reserves in the case of a drought; to better protect local residents against future flooding? OR Solution: A new Flexible Flow Management Program (FFMP) optimizes multiple, competing uses under limited storage capacities; releases water based on level and season (adaptive inventory control); devises water release policies based on cost-benefit trade-off analyses. Impact: an estimated $163 million annual increase in fishing and boating income, plus economic benefits due to flood loss reduction. Go to live podcast: client/cl_default.asp?client=569807&pcat=2053&cat=2130 Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 15 of 16
17 Questions and Room for Discussion Are you doing operations research? Do you model, analyze, compute,...? Do you think in terms of optimal solutions? Do you think in terms of trade offs? How do you handle uncertainty? INFORMS International Meeting Beijing, China, June 24-27, 2012 OR/MS for a Sustainable World Alexander Engau Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment 16 of 16
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