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SUMMARY:Models for Optimization of Industrial Research Management 
DTSTART:20110614T111500
DTSTAMP:20260526T225024Z
UID:173c52f0e936e8892e2dc8217cdaa1ce12488b98568a87ee3e929639
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr Debasis Mitra\, Bell Labs Lucent Technologies\nWe describe 
 work on modeling of industrial laboratories and the use of the models for 
 optimization and control of management processes. The industrial laborator
 y is viewed as being analogous to a knowledge factory\, where research is 
 done at the first stage and is followed by development stages\, which term
 inate with hand-off to the market or other organizations. Uncertainty is p
 ervasive in this framework. There is randomness in the processing time at 
 each stage. Also\, stochastic processes govern the evolution of project va
 lues through the stages. Management is two-fold\, project and investment. 
 Option value is the methodology for project management. It relies on infra
 structure support that enables information on project values to be collect
 ed after each stage. Such information allows calculations to be made of th
 e option value\, which is the expected terminal value of a project that ta
 kes into account future decisions. This allows mid-course decisions to be 
 made on whether to allow projects to continue or be terminated\, which occ
 urs if its option value drops to zero. Investment optimization concerns al
 location of given budgets to the resources in the various stages. Yet anot
 her important management mechanism that is considered is controlled access
  to resources and servers in the development stages. Projects with higher 
 option values are given priority in accessing resources. For the special c
 ase of two stages\, research and development\, we consider a combined mode
 l of investment optimization in the presence of optimal project and resour
 ce management. For this case results from an asymptotic analysis provide i
 nsights on optimal management decisions. Finally\, time permitting\, we wi
 ll descrbe preliminary results of an endogeneous growth model in a slow ti
 me scale. Throughout the talk we give numerical examples to illustrate con
 cepts.  Prof. Mitra's homepage
LOCATION:BC 01 https://plan.epfl.ch/?room==BC%2001
STATUS:CONFIRMED
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