ACM SIGSIM PADS 2013 Keynote Speech
Challenges in Stochastic
Modeling of Complex Service Systems
for Simulation and Optimization
Canada Research Chair in Stochastic Simulation and Optimization
Département d'Informatique et de Recherche Opérationnelle
Université de Montréal
C.P. 6128, Succ. Centre-Ville, Montréal, H3C 3J7, Canada
Large complex systems that involve humans (such as health-care systems, call centers, emergency systems, transportation networks, supply chains, communication systems, etc.) are difficult to manage because they are complex and involve significant uncertainty. This uncertainty itself is often quite difficult to model in a realistic way. For example, call arrivals in call centers follow stochastic processes whose rates depends significantly on the time of the day, type of day (holiday, day of the week), period of the year, weather, other external events, etc., and this rate is itself stochastic. The arrival processes of different call types may also be strongly dependent. Call durations (service times) have distributions that depend on the call type and on the particular agent who handles the call, are often time-dependent (the effectiveness of agents depends on their experience, base qualities, motivation, fatigue, etc.). Similar complications occur in other systems mentioned above. These properties imply that valid and reliable stochastic models for these systems are hard to build and maintain, and require continuous learning and adaptation based on incoming data that reflects system evolution. This in turns require powerful statistical methods which in many cases are not yet available.
The main reason why one would like to simulate these systems realistically is to construct good decision-making policies for their management. In a typical call center with multiple call types and multiple agent types (who can handle subsets of call types), one must decide how many agents to hire and train, for what call types, construct work schedules for these agents that respect union agreements, specify dynamic routing rules for arriving calls and for agents that become available, while meeting certain (stochastic) constraints on the quality of service of the systems (e.g., on the distributions of waiting times and call abandonments), and do this at the least possible cost. Solving such stochastic optimization problems via simulation, both for long- and medium-term planning (days or months in advance) and for short-term decision making and recourse to face unexpected situations, are very challenging tasks.
We will illustrate these kinds of modeling and optimization problems with concrete examples and data, and will review some solutions paths and ideas.
Pierre L'Ecuyer holds the Canada Research Chair in Stochastic Simulation and Optimization, in the Département d'Informatique et de Recherche Opérationnelle at the Université de Montréal. He obtained the Steacie Fellowship from the Natural Sciences and Engineering Research Council of Canada (NSERC) in 1995-97, a Killam Research Fellowship in 2001-03, the Urgel-Archambault Prize from ACFAS in 2002, twice the INFORMS Simulation Society Outstanding Research Publication Award, in 1999 and 2009, the Distinguished Service Award in 2011, and was elected INFORMS Fellow in 2006.
He has published over 230 scientific articles and book chapters in various areas, including random number generation, quasi-Monte Carlo methods, efficiency improvement in simulation, sensitivity analysis and optimization for discrete-event simulation models, simulation software, stochastic dynamic programming, and applications in finance, manufacturing, telecommunications, reliability, and service center management. He also developed software libraries and systems for the theoretical and empirical analysis of random number generators and quasi-Monte Carlo point sets, and for general discrete-event simulation. His work impinges on the areas of mathematics, statistics, operations research, economics, and computer science.
He is currently Editor-in-Chief for the ACM Transactions on Modeling and Computer Simulation, and Associate Editor for ACM Transactions on Mathematical Software, Statistics and Computing, Cryptography and Communications, and International Transactions in Operational Research. He has been a referee for over 120 different scientific journals.
He was a professor in the Département d'Informatique at Université Laval (Québec) from 1983 to 1990 and is at the Université de Montréal since then. He is a member of the CIRRELT and GERAD research centers, in Montréal. His recent research articles are available online from his web page: http://www.iro.umontreal.ca/~lecuyer.