Prescriptive Analytics

Exam number: 6816

Semester: from 1st semester

Duration of the module: One semester

Form of the module (i.e. obligatory, elective etc.): Elective

Frequency of module offer: Summer semester 2019

Prerequisites: The course builds on the knowledge of the course "Prescriptive Analytics" held in the first block of the semester.

Applicability of module for other study programmes:
Obligatory or elective in other study programmes. For further information check regulations of the study programme.

Person responsible for module: Prof. Dr. Sven Müller

Name of the professor: Prof. Dr. Sven Müller

Language of teaching: English

ECTS-Credits (based on the workload): 6

Workload and its composition (self-study, contact time):
Contact time (Lecture, tutorial etc.): 30 h; self-study: 150 h

Contact hours (per week in semester): 2

Methods and duration of examination:
tba

Aim of the module (expected learning outcomes and competencies to be acquired):
Students learn how to use predictive models (discrete choice models) in mathematical models (i.e., mixed integer programs) to consider demand as an auxiliary variable. The models are implemented in a modeling environment and case studies are used for practicing purposes.

Contents of the module:
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) are 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, product portfolio planning, and revenue management.

Teaching and learning methods:
tba