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Operations Research and Project Management Papers

2020 Papers

• Optimizing Supply Chain Robustness through Simulation and Machine Learning
  Bahar Biller and Jinxin Yi; SAS Institute, Inc. 2019

  This paper introduces a supply chain simulator that has been built using SAS® Simulation Studio. The key features of the SAS simulation technology, which enable the development of digital supply chains and the analysis of thousands of scenarios to perform risk-and-return tradeoff, are discussed. The paper concludes with a description of how computational efficiencies can be achieved through an integrated use of SAS Simulation Studio and SAS Visual Data Mining and Machine Learning.

2019 Papers

• Optimizing Product Assortment with Total Unduplicated Reach and Frequency Analysis in SAS/OR
  Laramore, Jay; SAS Institute, Inc. 2019

  An accurate and commercially viable approach to TURF analysis can be constructed as a mixed-integer linear programming (MILP) problem using SAS/OR software. This paper details the modeling approach, data requirements, desired output, scenario analysis, and stationarity considerations.

• The Science of Workflow Management: Modeling Business Processes in SAS Simulation Studio
  Manet, Dave; SAS Institute, Inc. 2019

  In this paper, we use SAS Simulation Studio to conduct experiments of how changes in work volume and resource availability impact process efficiency and capacity of an essential business process.

2018 Papers

• Looking Beyond the Model with SAS Simulation Studio: Data Input, Collection, and Analysis
  Hughes, Ed; SAS Institute, Inc. 2018

  SAS Simulation Studio is a component of SAS/OR software that provides an interactive, graphical environment for building, running, and analyzing discrete-event simulation models. In a broader sense, it is also an integral part of the SAS analytic platform. This paper illustrates how SAS Simulation Studio enables you to tackle discrete-event simulation challenges.

• Using SAS/OR to Optimize Scheduling and Routing of Service Vehicles
  Pratt, Rob; SAS Institute, Inc. 2018

  An oil company has a set of wells and a set of well operators. Each well has an established amount of time required for servicing. For a given planning horizon, the company wants to determine which operator should perform service on which wells, on which days, and in which order, with the goal of minimizing service time plus travel time. A frequency constraint for each well restricts the number of days between visits. The solution approach that is presented in this paper uses several features in the OPTMODEL procedure in SAS/OR software. A simple idea and a small change in the code reduced the run time from one hour to one minute.

2017 Papers

• Change Management: Best Practices for Implementing SAS Prescriptive Analytics
  Shuler, Scott; SAS Institute, Inc. 2017

  This paper provides guidelines and best practices in change management that the SAS Advanced Analytics Division uses with customers when it implements prescriptive analytics solutions (provided by SAS/OR software).

• Solving Business Problems with SAS Analytics and OPTMODEL - Fall 2017
  Hughes, Ed; Pratt, Rob; Xu, Yan; Cay, Pelin; SAS Institute, Inc. 2017

  This presentation demonstrates OPTMODEL’s power and versatility in building and solving optimization models, noting the significant improvements resulting from recently added features. Emphasizes integration with SAS data, analytic, and reporting capabilities, largely focusing on case studies drawn from our successful work with customers across a broad range of industries.

• Solving Business Problems with SAS Analytics and OPTMODEL - Spring 2017
  Pratt, Rob; Tutunchi, Golbarg; SAS Institute, Inc. 2017

  This presentation demonstrates how you can use the OPTMODEL procedure's power and versatility to build and solve optimization models in a variety of settings. Includes a survey of recent consulting projects, highlighting our transportation optimization work with Boston Public Schools.

2016 Papers

• Solving Business Problems with SAS Analytics and OPTMODEL - Fall 2016
  Hughes, Ed; Pratt, Rob; Tutunchi, Golbarg; SAS Institute, Inc. 2016

  Classical and practical examples demonstrate OPTMODEL's power and versatility in building and solving optimization models in a variety of settings. Includes a survey of recent consulting projects, highlighting our transportation optimization work with Boston Public Schools.

• Solving Business Problems with SAS Analytics and OPTMODEL - Spring 2016
  Hughes, Ed; Pratt, Rob; Shuler, Scott; Koch, Patrick; SAS Institute, Inc. 2016

  This presentation explores practical applications of building and solving mathematical optimization models with PROC OPTMODEL, and also describes how optimization methods are being used to improve predictive machine learning models.

• Using the OPTMODEL Procedure in SAS/OR to Find the k Best Solutions
  Pratt, Rob; SAS Institute, Inc. 2016

  This paper uses various techniques for finding the k best solutions to the linear assignment problem in order to illustrate several features recently added to the OPTMODEL procedure in SAS/OR software.

• Using SAS Simulation Studio to Test and Validate SAS/OR Optimization Models
  Hughes, Ed; Lada, Emily; Lopes, Leo; Pólik, Imre ; SAS Institute, Inc. 2016

  This paper begins with a look at both optimization modeling and discrete-event simulation modeling, and explores how they can most effectively work together to create additional analytic value. It then considers two examples of a combined optimization and simulation approach and discusses the resulting benefits.

2015 Papers

• Make Better Decisions with Optimization
  Duling, David; SAS Institute, Inc. 2015

  This paper demonstrates how to build business rules and then optimize the rule parameters to maximize the effectiveness of those rules.

• Practical Applications of SAS Simulation Studio
  Hughes, Ed; Lada, Emily; SAS Institute, Inc. 2015

  This paper looks at some discrete-event simulation modeling needs that arise in specific settings and some that have broader applicability, and it considers the ways in which SAS Simulation Studio modeling can meet those needs.

• Using SAS/OR to Optimize the Layout of Wind Farm Turbines
  Xu, Sherry; Yi, Jinxin; Gardner, Steven; Griffin, Joshua; Kacar, Baris ; SAS Institute, Inc. 2015

  This paper describes the use of the OPTMODEL and OPTLSO procedures on the SAS High-Performance Analytics infrastructure together with the FCMP procedure to model and solve this highly nonlinear optimization problem.

• Using the OPTMODEL Procedure in SAS/OR to Solve Complex Problems
  Pratt, Rob; SAS Institute, Inc. 2015

  This paper illustrates PROC OPTMODEL’s power and versatility in building and solving optimization models and describes the significant improvements that result from PROC OPTMODEL’s many new features.

2014 Papers

• Solving Business Problems with SAS Analytics and OPTMODEL - Fall 2014
  Hughes, Ed; Pratt, Rob; Liang, Fang SAS Institute, Inc. 2014

  This presentation surveys several of the optimization modeling and solution features of PROC OPTMODEL in SAS/OR, featuring applications to textbook and practical resource and planning problems. The presentation includes a sampling of recent optimization consulting engagements.

• Solving Business Problems with SAS Analytics and OPTMODEL - Spring 2014
  Hughes, Ed; Pratt, Rob SAS; Liang, Fang; Institute, Inc. 2014

  This presentation provides an introduction to the optimization modeling capabilities of the OPTMODEL procedure in SAS/OR and its application to classical and practical optimization problems. A survey of recent operations research consulting engagements is included.

• New Features in SAS/OR 13.1
  Hughes, Ed; Pratt, Rob; SAS Institute, Inc. 2014

  This paper surveys the enhancements and new features that are included in SAS/OR 13.1 and SAS Simulation Studio 13.1.

• The Traveling Baseball Fan Problem and the OPTMODEL Procedure
  Chapman, Tonya; Galati, Matt; Pratt, Rob; SAS Institute, Inc. 2014

  This paper uses the SAS/OR OPTMODEL procedure to formulate and solve the traveling baseball fan problem, which complicates the traveling salesman problem by incorporating scheduling constraints: a baseball fan must visit each of the 30 Major League ballparks exactly once, and each visit must include watching a scheduled Major League game.

• Work Area Optimization at a Major European Utility Company
  Yi, Jinxin; Lada, Emily; Smith, Anne; Gray, Colin; SAS Institute, Inc. 2014

  This paper describes the use of SAS/OR optimization procedures to model an efficiency problem and configure optimal work areas, and the use of SAS Simulation Studio to simulate how the optimal configurations might satisfy the customer service requirements.

• Using the OPTMODEL Procedure in SAS/OR to Solve Complex Problems
  Rob Pratt; SAS Institute, Inc. 2014

  This presentation illustrates PROC OPTMODEL's power and versatility in building and solving optimization models and describes the significant improvements that result from PROC OPTMODEL's many new features. Highlights include the recently added support for the network solver, the constraint programming solver and the COFOR statement, which allows parallel execution of independent solver calls. Best practices for complex problems that require access to more than one solver are also demonstrated.

• Introduction to SAS Simulation Studio
  Hughes, Ed; Lada, Emily; Meanor, Phillip; Hong, Chen; SAS Institute, Inc. 2014

  This paper explores the features of SAS Simulation Studio 13.1 and SAS Simulation Studio 13.2. Discussed topics include resource modeling, data input, collection, and analysis, and model execution.

• Creating a SimNICU: Using SAS Simulation Studio to Model Staffing Needs in Clinical Environments
  DiRienzo, Chris; Tanaka, David; Duke University Medical Center: Lada, Emily; SAS Institute, Inc. 2014

  This paper describes a project that uses SAS Simulation Studio to model the flow of patients through a hospital’s neonatal intensive care unit (NICU) over a one-year period. The model is used to predict the number of staff nurses needed per shift and to project patient outcomes in different scenarios.

2013 Papers

• Solving Business Problems with SAS Analytics and OPTMODEL
  Hughes, Ed; Pratt, Rob; Viktorovna, Natalia; SAS Institute, Inc. 2013

  This presentation uses sample problems and case studies to demonstrate OPTMODEL’s ability to build and solve a wide range of optimization models. Integration with other SAS analytics and new features from releases 12.1 through 13.1 are highlighted.

• Advanced Project Management beyond Microsoft Project, Using PROC CPM, PROC GANTT, and Advanced Graphics
  Sloan, Stephen, Accenture; Puryear, Lindsey, SAS Institute 2013

  This paper outlines how to use the SAS/OR CPM, SAS/OR GANTT, and PRINT procedures to create a Project Optimizer that allows projects sharing a single resource pool to be scheduled.

• The Hospital Game: Optimizing Surgery Schedules to Save Resources, and to Save Lives
  Pease, Andrew; Peker, Aysegul; SAS Institute 2013

  This paper briefly reviews some of the academic research that is available for a data-driven, operations research approach to solving this challenge, which is dubbed the “Hospital Game” in some of this literature. The paper then proposes an optimization-based approach that uses the OPTMODEL procedure to derive the best surgery schedule for a major European hospital.

• Parallel Multistart Nonlinear Optimization with PROC OPTMODEL
  Hughes, Ed; Huang, Tao; Xu, Yan; SAS Institute 2013

  In SAS/OR 12.1, the multistart feature adds parallel execution. This paper explores the multistart feature and its parallel optimization feature, illustrating with examples drawn from research and industry.

• Smarter Grid Operations with SAS/OR
  de Castro, Arnie; Link, Greg ; Wu, Xinmin; SAS Institute 2013

  This paper discusses the use of SAS/OR to control device switching to optimize the operations of the electrical distribution system.

• Solving Business Problems with SAS Analytics and OPTMODEL
  Hughes, Ed; Peker, Aysegul; Pratt, Rob SAS Institute, Inc. 2013

  This presentation demonstrates OPTMODEL’s power and versatility in building and solving optimization models, especially noting the significant improvements resulting from recently added optimization features.

• Earned Value Management with SAS/OR
  Hughes, Ed; SAS Institute, Inc. 2013

  This is a presentation on Earned Value Management, which is a facet of the project management capabilities of SAS/OR.

• Introduction to SAS Simulation Studio
  Hughes, Ed; Lada, Emily; Meanor, Phillip; Hong, Chen; SAS Institute, Inc. 2013

  This paper surveys the capabilities of SAS Simulation Studio 12.3, including mobile and stationary resource modeling, input data management, output data collection, storage, and analysis, input analysis, and the design of simulation experiments.

• Projecting Prison Populations with SAS Simulation Studio
  Hevener, Ginny; Finchum, Tamara; North Carolina Sentencing and Policy Advisory Commission
  Lada, Emily; Day, Jeff; Aral, Bahadir; SAS Institute, Inc. 2013

  This paper discusses the use of SAS Simulation Studio to model and project the prison population over a ten-year period, accounting for the effects of many detailed factors including sentence length, offender history, and legislative changes.

2012 Papers

• Solving Business Problems with SAS Analytics and OPTMODEL
  Hughes, Ed; Peker, Aysegul; Pratt, Rob SAS Institute, Inc. 2012

  This presentation illustrates the OPTMODEL procedure’s modeling and solution capabilities, with an emphasis on the significant improvements created by a range of new features.

• New Features in SAS/OR 12.1
  Hughes, Ed; Chari, Manoj; SAS Institute, Inc. 2012

  SAS/OR 12.1 debuts a broad range of new capabilities and enhanced features in operations research. This paper surveys these additions, emphasizing their benefits and their application to business problems, and especially to large business problems.

• The Traveling Salesman Traverses the Genome: Using SAS Optimization in JMP Genomics to Build Genetic Maps
  Miclaus, Kelci; Pratt, Rob; Galati, Matthew; SAS Institute, Inc. 2012

  This paper highlights new tools available in JMP Genomics software to construct genetic linkage maps through a graphical user interface from which biologists can access powerful optimization routines implemented with SAS/OR procedures such as PROC OPTMODEL.

• Bringing Optimization to the Business: Interfacing SAS/OR with SAS Stored Process, Microsoft Excel, SAS Enterprise Guide, SAS Forecast Studio, and Microsoft Project
  Pease, Andrew, SAS Institute, Inc. 2012

  This paper presents the necessary steps for developing interfaces to SAS/OR programs for use by business users.

2011 Papers

• Solving Business Problems with SAS Analytics and OPTMODEL
  Ed Hughes, Jeff Day, Maarten Oosten, Mike Gilliland, and Evan Stubbs; SAS Institute 2011

  This presentation highlights the OPTMODEL procedure's power and versatility in modeling and in creating solution algorithms.

• Linear Optimization in SAS/OR Software: Migrating to the OPTMODEL Procedure
  Rob Pratt and Ed Hughes; SAS Institute 2011

  This paper uses several examples to illustrate how to migrate to PROC OPTMODEL from the INTPOINT, LP, and NETFLOW procedures for linear optimization.

• Using SAS to Model and Forecast Greenhouse Gas Abatement Cost Curves
  Lorry M. Hardt and Keith Renison; SAS Institute 2011

  This paper discusses the challenges surrounding greenhouse gas abatement cost curves and provides examples of how a combination of SAS portfolio optimization modeling and energy and emissions forecasting techniques can help make the right decisions, and improve both environmental and economic performance.

• New Features in SAS/OR 9.3
  Ed Hughes and Manoj Chari; SAS Institute 2011

  This paper surveys new and enhanced operations research capabilities of SAS/OR 9.3.

• Introduction to SAS Simulation Studio
  Hughes, Ed; Lada, Emily; SAS Institute, Inc. 2011

  This paper presents an overview of SAS Simulation Studio 1.6, a discrete-event simulation application. Topics include resource modeling, preemption, data management, input analysis, and experimental design.

• An Application of SAS® Simulation Studio: The Microsimulation of a Computer Assisted Telephone Interviewing System
  Belanger, Yves; Couture, Kristen; Neusy, Elisabeth; Statistics Canada 2011

  This paper shows how SAS Simulation Studio was used in a microsimulation of a telephone interviewing system. Findings helped determine cost reduction strategies for the system, which surveys Canadian citizens.

2010 Papers

• Solving Business Problems with OPTMODEL and SAS
  Edward P. Hughes, Rob Pratt, Ivan Oliveira, SAS Institute 2010

  This presentation focuses on the OPTMODEL procedure’s power and versatility in modeling and in creating solution algorithms.

• Nonlinear Optimization in SAS/OR Software: Migrating from PROC NLP to PROC OPTMODEL
  Tao Huang and Edward P. Hughes; SAS Institute, 2010

  This paper uses several examples to illustrate how to migrate from PROC NLP to PROC OPTMODEL and highlight the benefits of doing so.

• Modeling Systems and Resources with SAS Simulation Studio: An Introduction
  Edward P. Hughes; SAS Institute, 2010

  This paper surveys the resource modeling capabilities of SAS Simulation Studio.

• Resource Management in SAS Simulation Studio
  Chen, Hong; Lada, Emily; SAS Institute, 2010

  This paper surveys the resource management capabilities of SAS Simulation Studio. Stationary and mobile resources, resource usage patterns, resource scheduling, and resource preemption are discussed.

• Modeling Systems and Resources with SAS® Simulation Studio: An Introduction
  Hughes, Ed; SAS Institute, 2010

  This paper introduces SAS Simulation Studio, a graphical application for discrete-event simulation. The focus is on the modeling of resources, including both stationary and mobile resources, and on the collection of resource statistics.

2009 Papers

• Using the SAS/OR OPTMODEL Procedure to Assign Students to Schools In the Wake County Public School System
  Ivan Oliveira, Rob Pratt; SAS Institute; Charles Dulaney, Wake County Public School System, 2009

  This presentation explores the formulation and solutions to the problem of of assigning students to schools, using multiyear student population forecasts. Using the SAS/OR OPTMODEL procedure, an optimization engine was developed to solve this problem. SAS® Grid Manager was used to generate multiple solutions for analysis and SAS/GIS® to visualize the recommended assignments on county geographical maps. Throughout the analysis, JMP® was used for design of experiments and visualization of optimization results.

• New Features in Optimization with SAS/OR Software
  Edward P. Hughes and Trevor D. Kearney, SAS Institute, 2009

  This paper describes the nature and purpose of optimization and considers the various types of optimization problems that can be solved with SAS/OR software.

• Exploring System Performance with SAS® Simulation Studio
  Hughes, Ed; Chen, Hong; Lada, Emily; Meanor, Phil; SAS Institute, 2009

  This paper discusses the major features and functions of SAS Simulation Studio and provides background information on discrete-event simulation. The graphical interface, experimental design, and integration with SAS and JMP analytics are covered.

2008 Paper

• SAS/OR: Introducing SAS Simulation Studio
  Hughes, Ed; Chen, Hong; Lada, Emily; Meanor, Phil; SAS Institute, 2008

  This paper discusses the major features and functions of SAS Simulation Studio and provides background information on discrete-event simulation, covering model building, experimental design, model execution, and analysis of results. An appendix shows how to build, run, and collect statistics for a simple queueing model.

2007 Paper

• Optimization with SAS/OR: What it is, what's new, and how it adds value
  Edward P. Hughes and Trevor D. Kearney, SAS Institute, 2007

  This paper provides background information on the role of optimization and surveys the new SAS/OR® optimization advances, highlighting their importance for organizations facing larger and more diverse problems in resource allocation, supply chain planning, and many other domains in which optimization plays a key role.

2003 Paper

• Optimization with the SAS System: What It Is, What's New, and Why You Should Be Using It
  Hughes, Edward P.; Kearney, Trevor D.; SAS Institute, 2003

  This paper presents an introduction to optimization and an overview of SAS® capabilities in optimization, with a focus on mathematical optimization with SAS/OR software.

2001 Paper

• Cycle Down to Launch: Streamlining Production at Lockheed Martin
  Dave Jennings (Lockheed Martin) and Radhika Kulkarni, SUGI Proceedings, 2001

  This paper describes several Web-based applications that were developed using SAS/OR and SAS/IntrNet software to allow users access to production data and to enable managers to make effective decisions regarding the status of the project.

1999 and Earlier Papers

• Advances in Mathematical Programming and Optimization in the SAS System
  Trevor Kearney, SUGI Proceedings, 1999

  This presentation gives an overview of the optimization capabilities in the SAS System, how they are changing with the availability of important new techniques, and where they will be in future releases.

• W-O-W: Data Warehouse, SAS and the WEB
  Art Rerecich, SUGI Proceedings, 1998

  This paper describes how a Data Warehouse was designed using the SAS system, running in a Client/Server configuration (UNIX & Windows 95), SAS/OR, with output distributed across the World Wide Web.

• Multiproject Scheduling using SAS/OR Software
  Gehan Corea, SUGI Proceedings, 1996

  This paper presents an overview of the multiproject capabilities in SAS/OR software.

• QSIM Application, Discrete Event Queueing Simulation
  Marc-david Cohen and Phil Meanor, Handout, 1996

  The QSIM application is a SAS application for modeling and analyzing queueing systems using discrete event simulation.

• Exploiting the Scheduling Algorithms in SAS/OR Software
  Radhika Kulkarni, SUGI Proceedings, 1994

  This paper illustrates how to compute some of the standard measures of performance of a schedule using the SAS System and how to implement some of the job shop and flow shop scheduling algorithms using PROC CPM.

• SAS/OR Optimization Procedures, with Applications to the Gas and Oil Industry
  Marc-david Cohen and Trevor D. Kearney, SUGI Proceedings, 1994

  This paper presents an introduction to optimization and an overview of SAS capabilities in optimization, with a focus on mathematical optimization with SAS/OR software.

• Using the Project Management Tools in the SAS System
  Radhika Kulkarni and Gehan Corea, SUGI Proceedings, 1992

  The major focus of the paper is to describe and illustrate some of the more advanced scheduling features of the CPM procedure.

Papers are in Portable Document Format (PDF) and can be viewed with the free Adobe Acrobat Reader.

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Powerpoint presentations and SAS programs can be downloaded as zip files.