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
Emphasis of the grade for the final grade: Please check regulations of the study programme
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
Literature (compulsory reading, recommended literature):
tba
Further information:
Registration in Moodle Viadrina required.