Choice-Based Optimization
Summary and study goals
Demand is an important quantity in many optimization problems such as revenue management and supply chain management. Demand usually depends on “supply” (price and availability of products, f. e.), which in turn is decided on in the optimization model. Hence, demand is endogenous to the optimization problem. Choice-based optimization (CBO) merges discrete choice models with math programs. Discrete choice models (DCM) have been applied by both practitioners and researchers for more than four decades in various fields. DCM describe the choice probabilities of individuals selecting an alternative from a set of available alternatives. CBO determines (i) the availability of the alternatives and/or (ii) the attributes of the alternatives, i.e., the decision variables determine the availability of alternatives and/or the shape of the attributes. We present CBO applications to location planning, supply chain management, assortment and revenue management.
Course Content
Students will learn how to develop and use predictive models (discrete choice models) in the software R and how to introduce such models in mathematical models for decision-making (i.e., mixed integer programs) to consider demand as an auxiliary variable. The models will be implemented in a modeling environment (GAMS). Case studies will be used for practicing purposes.
Date of Event
- – 26. September 2024
Location
Universität Hamburg
Fakultät für Betriebswirtschaft
Moorweidenstraße 18
EG, Raum 0005.1
20148 Hamburg
Language:
English
Lecturer:
Univ.-Prof. Dr. habil. Knut Haase
Universität Hamburg
www.bwl.uni-hamburg.de/vw/personen/prof-knut-haase
Univ.-Prof. Dr. habil. Sven Müller
RWTH Aachen University
https://www.business-school.rwth-aachen.de/dozierende/prof-dr-sven-mueller/
Registration:
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