First, a caveat: This article is based on the best available information from people still working through what needs to be done (see acknowledgments). Circumstances can change during the next few months.

Transportation


The DNC Committee (DNCC) is responsible for transporting delegates and media personnel between hotels and the Pepsi Center where the convention will be held. The DNC Host Committee (DNCH) is responsible for transporting delegates and media personnel between Denver International Airport and hotels and between hotels and selected special-event locations. The DNCC and the DNCH will have a fleet of buses and a motor pool (with volunteer drivers). The DNCH has reserved 94 hotels, some as far as 20 miles from the Pepsi Center. In addition, the "Greening the DNC" initiative will provide bikes and ushered walkways. The bikes will be provided at no cost, using a check-in/check-out system that enables delegates and media to use the bikes without responsibility for keeping them. One could bike to the Pepsi Center and take a bus back to the hotel.

The primary goal of any transportation system is to maximize service by minimizing delays and travel time. Specific forms of transportation (bus vs. bike vs. pedi-cabs) will be addressed separately.

The DNCC wants to know:

• how to schedule buses and assign routes with two objectives: maximize service and minimize carbon emissions; and
  
  
• how to manage the motor pool (cars with volunteer drivers).

The DNCH wants to know:

• how to schedule buses for selected special events;
  
  
• how to schedule buses between DIA and hotels; and
  
  
• how many bikes to have on hand, and where.

The design of bus routes and schedules to transport people between their hotels and the Pepsi Center is called a vehicle routing problem (VRP). This is a hard problem, but it has been studied for decades, so there are useful results in the literature. Our situation is non-standard, partly due to the Green initiative, so we have an opportunity to formulate a new VRP model and exploit what has been done to solve it.

Transportation between the airport and hotels is another VRP, but with other non-standard elements. For example, we may want to identify locations for buses to pick up volunteers to greet the arrivals. Some of those volunteers may remain at the airport and some may return with that load of passengers.

Besides moving people, transportation challenges could include moving recycled materials. One needs to specify depots and routes for waste management to pick up the recycled materials. Recycle bins could be at multiple locations inside every hotel, and volunteers would move them to a depot.

Pepsi Center Parking Lot Layout


Many challenges are associated with the design of the Media Center that must be built in the Pepsi Center parking lot. One challenge is the layout of the entire parking lot, which has two parts. The Pepsi Center is 20,000 square feet on 46 acres. A layout challenge is to determine bus accommodation with parking specifications and lanes as well as drop-off/pick-up points outside the Pepsi Center main entrance. A goal is to make effective use of the area — accommodate a specified number of buses and understand how that number affects service.

Bike Inventory Management


The DNCH expects to have an inventory of bikes for delegates and media to use during the convention. These will be picked up at one depot and dropped off at another. We need to decide where to locate the depots, how many bikes to put into each one, and when to move bikes from one depot to another. For example, suppose we have a depot at the Market Street Bus Terminal. Someone may pick up a bike there and drop it off at the Pepsi Center. Many who do that may choose to take a bus back to their hotel, leaving the bike at the Pepsi Center. In time, there will be a lot of bikes at the Pepsi Center and none at the Market Street depot. One challenge is to determine when and where to move bikes to satisfy demands.

Every depot will have a path to the Pepsi Center, and some distant path could pass another depot to allow the rider to drop it off if there is a problem. Depots can also be located at the light rail Pepsi Center stop, allowing some to ride a short distance to the center's entrance.

Volunteers will service the depots and transfer bikes from one depot to another, as needed. The bike inventory challenge is to determine how many bikes to transfer from one depot to another at the end of each shift. One goal is to minimize shortages for a given number of volunteers. Another is to minimize the number of volunteers needed to ensure no shortages (assuming there are enough bikes).

We could consider combining bike depots with recycle depots, setting up multi-service green stops. This enables multi-tasking — e.g., volunteers can bring recycle bins from a hotel to a green stop, then transfer bikes that need to go to another stop (with greater demand). The Mathematics Clinic can examine where to locate the green stops and specify the pickup schedule and routes.

Green Performance Evaluation


The challenges of the Green initiative create opportunities for analyzing various ways to reduce the carbon footprint, such as in planning the transportation. When the DNC is over, how do we know how much that footprint was reduced? That is a challenging question itself.

We can (approximately) measure the carbon footprint of transportation, and that will be considered in selecting bus routes and schedules. We also want to estimate the Green initiative's impact on the hospitality industry and individual behavior. Perfect information would be to know each carbon footprint with and without the initiative. This is not practical, but we could use sampling techniques to estimate the aggregate impact of the Green initiative. Part of the sampling could be interviews with randomly selected attendees. Another type of sampling could be random monitoring of bike and walkway usage, and this would be converted to carbon reduction compared to using a bus. Similarly, we could sample people in the hospitality industry to get their estimates of differences; volunteers could randomly sample hotels and restaurants to record their green practices. Again, we would need to translate those differences into carbon reduction.

A goal is to measure net benefits for possible future application beyond the DNC. The Mathematics Clinic can consider the design of the sampling process and write a guide for the volunteers to implement it. If time permits, this would be accompanied by a guide to perform the analysis that gives the final estimate.

Volunteer Assignments


At least 10,000 volunteers are expected to help with many tasks during the convention. Each task requires some minimum number of qualified volunteers to be performed. The shear number of volunteers and the variety of tasks render managing the assignment of volunteers to tasks a great challenge. The goal is to make the best use of the volunteers and the skills they bring, while respecting the preferences of the volunteers for the jobs they do and when they do them.

Each task is defined by its key requirements: location, duration and number of volunteers in each skill category. Most of the volunteers will be assigned to tasks before the convention begins (some are working now). Each volunteer signs up for a block of shifts, which are generally four hours each, and the start-end times could overlap.

The Mathematics Clinic can consider a pre-assignment model that assigns volunteers to tasks based on what is known about volunteer availability and task requirements. A first version can assume perfect information and seek to fulfill each task while maximizing volunteer preferences. A goal of the pre-assignment model is to provide at least one "reasonable" initial assignment, which can be adjusted as situations change.

Once the convention begins, real-time adjustments are likely to be needed, and this challenge has different characteristics than the pre-assignment model. Requests for volunteers arrive at a central service, manned by volunteers with office skills. The arrivals are mostly by phone, but eventually all requests are entered into the computer. A goal of the real-time adjustment model is to provide immediate response to fulfill new tasks or complete some in progress. There is a trade-off between changing some assignments versus the use of standbys. Each has its pros and cons to be considered in a goal-directed objective.

Venue Allocation


The DNC will host about 1,500 events, some for delegations and some for corporate sponsors. There are many facets to plan an event: location, catering, entertainment, rentals, decoration, cleanup and transportation. One challenge for the Mathematics Clinic to consider is decision-support for venue allocation, run by DNCH (with early help from the Denver Metro Convention & Visitor Bureau. Examples of venues are Coors Field, Invesco Field, museums and restaurants.

Requests for venues are submitted electronically, and they are put on hold until a committee (which meets weekly) decides to deny or grant the request. A denial may be accompanied by a suggested alternative having about the same size and location. The decision to grant a venue (and deny competing requests) is based on several factors. (Venue managers voluntarily cooperate with the DNCH, but they are free to contract their venues directly.) The goal is to maximize request satisfaction.

The Mathematics Clinic could develop a model to rank competing requests, taking into account alternatives. This could cascade — e.g., there could be many second-best allocations that satisfy all concerned versus another allocation that satisfies one requestor a little more than OK while dissatisfying many other requestors. Such tradeoffs are inherent in a decision model, and highly subjective factors can be handled outside the model's scope. The model could list candidate allocations, based on factor values, and provide sensitivity analysis to changing some of those allocations. A model could answer such questions as, "What requestors are highly dissatisfied if I allocate a particular venue to some requestor?" and "Is there a compromise allocation that does not greatly dissatisfy anyone and satisfies certain specifications?"

Prior Work


Surprisingly, none of the four presidential conventions in 2000 and 2004 used operations research for any of the planning challenges. (I contacted O.R. people in the host cities: Philadelphia, New York, Los Angeles and Boston. I was unable to find anyone who heard of any application of O.R. to any of the planning. I also searched the literature and could not find anything. Of course, the absence of findings does not prove that O.R. has not been applied.) Other large conventions, such as the Olympics, were also planned without any report of using O.R. It seems to have some of the same challenges, and we may use some studies to guide some of our modeling — for example, [2, 9]. Other sporting events have also raised challenges for venue allocation [7], though the underlying issues seem different.

We shall begin our efforts with a review of prior work, relevant to the challenges we shall address. Some seem generic, such as the VRP [1] as a transportation model; however, there are variations that do not appear to have been explicitly studied. Some challenges are new, such as the Green initiative.

Also surprising is the scarcity of quantitative approaches to assigning volunteers, particularly large-scale. I found only two articles that use O.R. [4,8], despite the vast literature on volunteer management.

Our review will consider any publications that use mathematical methods and any relevant software, even if designed for more general applications. Our goal is to produce a report that may help by analyzing some of the many challenges with mathematical models and computer algorithms, aimed at supporting decision processes.

In conclusion, the convention business is huge, and I have so far identified only a few of the opportunities for O.R. I plan to report our final results in May. Meanwhile, I welcome any information or advice.

Acknowledgment: My thanks to members of the DNCH — Parry Burnap, Paul Lhevine, Chantal Unfug and Sondra Williams — and to members of the DNCC — Andrew Ballard and Nicholas Swett. They shared their time to help me understand the challenges and opportunities in preparing for the DNC. For the same reasons, my thanks to leaders in the private sector: Paul Jeppsen, Keystone Resort; Steven Kinsley, Kinsley & Associates; Nicole Marsh, Arrangers; and Mike Wolf, Destination Services. I also thank Vikki Kelly and Harry Emerson, DMCVB, for much clarification of their operations. Thanks also to Dan Connolly, University of Denver, for discussing a wide range of challenges in preparing for the DNC.

1. B. D. Díaz, 2007, The VRP Web, University of Málaga, http://neo.lcc.uma.es/radi-aeb/WebVRP/.
2. M. S. Friedman, K. E. Powell, L. Hutwagner, L. M. Graham, and W. G. Teague, 2001, "Impact of changes in transportation and commuting behaviors during the 1996 Summer Olympic Games in Atlanta on air quality and childhood asthma, The Journal of the American Medical Association, Vol. 285, No. 7, pp. 899-905,
3. J. Goldblatt, 2002, "Special Events: Twenty-first Century Global Event Management," New York, N.Y., third edition.
4. L. Gordon and E. Erkut, 2004, "Improving volunteer scheduling for the Edmonton Folk Festival," Interfaces, Vol. 34, No. 5, pp. 367-376.
5. C. F. Gray and E. W. Larson, 2006, "Project Management: The Managerial Process," New York, N.Y., third edition.
6. "Keystone Resort Environmental Policy and Key Initiatives," 2007, fact sheet, Vail Resorts, Keystone, Colo.
7. R. A. Russell and T. L. Urban, 2006, "A constraint programming approach to the multiple-venue, sport-scheduling problem," Computers & Operations Research, Vol. 33, No. 7, pp. 895-906.
8. S. E. Sampson, 2006, "Optimization of volunteer labor assignments," Journal of Operations Management, Vol. 24, No. 4, pp. 363-377.
9. E. Teramoto, M. Baba, H. Mori, H. Kitaoka, I. Tnahashi, Y. Nishimura, T. Saito, Y. Takizawa, T. Sawa, and H. Ooe, 1998, "Prediction of Traffic Conditions for the Nagano Olympic Winter Games Using Traffic Simulator: NETSTREAM," in Proceedings of 5th World Congress on Intelligent Transport Systems.

Table of Contents

OR/MS Today Home Page


OR/MS Today copyright © 2008 by the Institute for Operations Research and the Management Sciences. All rights reserved.


Lionheart Publishing, Inc.
506 Roswell Rd., Suite 220, Marietta, GA 30060 USA
Phone: 770-431-0867 | Fax: 770-432-6969
E-mail: lpi@lionhrtpub.com
URL: http://www.lionhrtpub.com


Web Site © Copyright 2008 by Lionheart Publishing, Inc. All rights reserved.