Optimization in Services - Coping with Uncertainty and Different Interest Groups
The speaker:
Abstract:
Service industry is constantly growing and services attract increasing importance
for example in combination with industrial products. Typical characteristics of
services are intangibility, customer integration, non-transportability,
non-stockability and the promise of future performance. This results in
complexity, uncertainty and involvement of different interest groups to be handled
with when services are planned and provided. Mathematical optimization methods
are perfectly suited to determine best solutions for complex situations.
Several extensions allow finding ideal compromises for different interests and appropriate
solutions in uncertain situations.
After plenty of successful applications of optimization in industry, health
care management increasingly uses optimization models to improve performance
and quality or to reduce costs. In this presentation the focus is on providing
services with scarce resources within a short period of time. This is of prime
importance for fire fighters and emergency medical services and highly depends
on the best location of respective departments and equipment. Decisions on
operating room schedules also influence customer satisfaction by treating as
many patients as possible during their preferred time. Often, time and capacity
needed for a service are not precisely known in advance. Then stochastic or
robust optimization models are used to find admissible and best solutions. Several
examples from health care management and logistics demonstrate how different
optimization methods cope with uncertainty and multi-criteria and determine
optimal solutions for services in different application areas.