Overview and Opportunities ofOperations Research (OR/MS) inSustainability and the Environment
Alexander Engau, Ph.D.Mathematical and Statistical SciencesUniversity 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
What’s In A Name Image taken from http://www.flickr.com/photos/westius/3285419823/
Wordle image of the most popular words in Australia’s Defence Scienceand 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
Operations Research and Management Science (OR/MS)
“OR/MS seeks to provide decision and policy makers withmathematical 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
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
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Computation and The Curse of Dimensionality
“The execution, analysis, or solution of many stochastic anddeterministic 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
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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
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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
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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 prioritrade-offs that reduce computational and decisional requirements.
• Use decomposition techniques to facilitate trade offs and preferencearticulation 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-disciplinarysystem-of-systems framework
• every discipline has its ownobjectives and decision criteria
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Challenges of MDO (and Project or Operations Management in General)
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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
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One-Page Summaries of Other Projects
• Operations Management:volunteer assignment andscheduling for Denver B-CycleBike-Sharing Program
• Process Engineering/OM: optimalcollision avoidance of operationalspacecraft in near-real time
• Energy Systems/SustainabilityEngineering: optimization of ahybrid wind/solar generationsystem for lifespan extension
• Sustainability Engineering/ES/PE/OM: oil load dispatch and haulingoptimization at the WattenbergField/Denver-Julesburg Basin
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Volunteer Assignment and Scheduling for Denver B-Cycle Bike SharingJoint work with Matt Kaspari, Kaspo Inc., and Piep Van Heuven, Denver B-Cycle
The Problem
• volunteers were critical inearly phases of Denver BC
• assignments must considerall preferences and conflicts
Approach and Methods
• developed survey to collectall relevant volunteer data
• used goal programming forfeasible/optimal scheduling
Results and Impact
• fast and fair assignment• simulation model was used
to analyze long-term effectAlexander Engau | Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment | 11 of 16
Optimization of Wind/Solar Generation Systems for Lifespan ExtensionJoint Work with Daniel Mejía and Fernando Mancilla-David (both EE, UC Denver)
The Problem
• smart grid operation anddesign are non-trivial tasks
• disturbances damage andshorten equipment lifespan
Approach and Methods
• minimize (nonlinear) windgenerator harmonics andcharging profile deviations
• decompose full optimizationinto single subcomponents
Results and Impact
• scenario-based simulationvalidates optimal solutions
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Optimal Collision Avoidance of Operational Spacecraft in Near-Real TimeSpring 2011 UC Denver Math Clinic sponsored by SpaceNav LLC., Boulder, CO
The Problem
• debris (space junk) posesthreat to space operations
• critical need for collisionrisk management tools
Approach and Methods
• prediction of conjunctionevents and collision risks
• optimization of maneuversfor safe collision avoidance
Results and Impact
• prototype software for riskanalysis and optimization
• student continued as internAlexander Engau | Mathematical and Statistical Sciences, UC Denver OR/MS in Sustainability and the Environment | 13 of 16
Oil Load Dispatch and Hauling Optimization at Denver-Julesburg BasinSpring 2012 UC Denver Math Clinic sponsored by Noble Energy Inc., Houston, TX
The Problem
• Noble plans to invest $8billion over the next fiveyears in the DJ Basin
• need enhanced tools toplan and support theiroperational decisions
Approach and Methods
• use a network flow modelfor transportation problem
• handle uncertainties usingsimulation 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
Improving Water Release Policies on the Delaware River Through ORThe Delaware River Basin Commission, INFORMS 2010 Edelman Award Finalist
. . . recognizes outstanding examples of innovative OR thatimproves [. . . ] 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 andboating income, plus economic benefits due to flood loss reduction.
Go to live podcast: https://live.blueskybroadcast.com/bsb/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
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 MeetingBeijing, China, June 24-27, 2012OR/MS for a Sustainable World
http://greenor.wordpress.com
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