DMI715 Optimization Methods in Logistics

Code DMI715
Name Optimization Methods in Logistics
Status Compulsory/Courses of Limited Choice
Level and type Post-graduate Studies, Academic
Field of study Computer Science
Faculty Department of Modelling and Simulation
Academic staff Gaļina Merkurjeva
Credit points 2.0 (3.0 ECTS)
Parts 1
Annotation The course starts with an overview of different optimization methods and techniques applied in logistics, and software review. The following optimization methods are considered in the course: Mathematical Programming (Linear Programming (LP), Integer Programming (IP), and Dynamic Programming); Numeric Optimization (Tree/Graph Search methods – Branch & Bound); Heuristic Optimization and Metaheuristics (Greedy, Tabu, Simulated Annealing, Genetic Algorithms, Evolutionary Strategy); Constraint Programming and Simulation-based Optimization. In the practical part of the course different optimization algorithms are applied to benchmark optimization problems in logistics by using the heuristic optimization environments and simulation-based optimization software tools, and a case study in logistics optimization is developed in groups..
Goals and objectives
of the course in terms
of competences and skills
Competences and skills demonstrated: know of different optimization methods, techniques, software and their application aspects; identify the problem to be optimized and select an appropriate optimization method; apply optimization software to solve practical tasks in logistics optimization.
Learning outcomes
and assessment
To be able to use different optimization methods to benchmark optimization problems. - Successfully performed practical assignments in the course.
To be able to identify and formalize the problem to be optimized, and select an appropriate optimization method to solve the problem. - Demonstrated abilities to identify the problem to be optimized, mathematically formulate its structure and select an appropriate optimization method for problem solving. (A case study).
To be able to apply optimization techniques and software tools to solve practical tasks in logistics optimization. - Demonstrated abilities to use optimization techniques and software tools to solve practical tasks in logistics optimization (A case study).
To be able to describe and interpret optimization methods and techniques, and their application aspects to optimization problem solving in logistics. - Demonstrated ability to identify a specific subject and provide an augmented explanation (Course exam).
Course prerequisites Mathematics

[Extended course information PDF]