Oded Berman (University of Toronto, Canada)

Short Biography

Oded Berman is professor of Operations Research / Management Science at the University of Toronto . Presently, he detains the Sydney C. Cooper Chair in Business and Technology, Joseph L. Rotman School of Management, University of Toronto. His research interest follows on the areas of Operations Management, Operations Management in the Service Industry, Management Science Models and Statistics. Research includes Logistics, Operations Management in the Service Industry, Workforce Management, and Software Reliability. He is author of 165 scientific articles in these fields. He has received several honors and awards namely the Roger Martin and Nancy Lang Award for Excellence in Research, Joseph L. Rotman School of Management (2000), Principal's Research Award, University of Toronto at Scarborough (1997). He has been associated editor of some of the top most scientific journals in Operations research, namely Operations Research, Transportation Science, Management Science, the Canadian Journal of Administrative Sciences and Computers and Operations Research.

Lecture to be presented in EWI 2007

Title

Stochastic Facility Location and Capacity Problems

Abstract

We discuss location problems of fixed facilities with congestion. Congestion occurs when requests for service occur in a probabilistic fashion and when the service facilities do not have sufficient capacity to respond immediately to the requests. Since facilities are fixed customers travel to the closest facilities to obtain service.
The most general problem is to simultaneously optimize three sets of decision variables: (i) the number of facilities; (ii) the location of the facilities; and (iii) the service capacity of the facilities. The optimization is subject to two types of service level constraints: (1) upper bound constraint on the travel distance of customers to facilities; and (2) upper bound constraint on the waiting times of customers at the facilities.
We first present several location problems that deal with only two of the three possible sets of decision variables and conclude with a discussion of the most general problem.

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