overview and opportunities of operations research (or/ms) in

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

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Wordle image of the most popular words in Australia’s Defence Scienceand Technology Organisation’s (DSTO) “OR Code of Best Practices”


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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.”


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


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


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


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


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


Challenges of MDO (and Project or Operations Management in General)


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


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


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


• minimize (nonlinear) windgenerator harmonics andcharging profile deviations

• decompose full optimizationinto single subcomponents

Results and Impact

• scenario-based simulationvalidates optimal solutions


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


• 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


• 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


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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


http://greenor.wordpress.com

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