MMO5008 Applied Approach to Tools of Optimization and Simulation
Course description for academic year 2018/2019
Contents and structure
Operations research helps in solving problems in different environments that needs decisions. The module covers tradition topics of Operational research (OR) that include: linear programming, Transportation, Assignment. But this is not only limited to business problems, also technical problems have to optimized, for example weight and strength of a construction, resistance of a vessel by variating the shiphull. In these cases heuristic optimisation approach know as artificial intelligence are used. At least but not at last many processes are probilistic hence the optimum has to be found for unsure situation. For all of this a kind of simulation model is needed. These can be analytic ones but often they are a kind of discrete / numerical simulation model.
Analytic techniques and computer packages will be used to solve problems facing business managers in decision environments.
- Introduction to Operations Research (OR)
- Introduction to Foundation mathematics and statistics
- Linear Programming (LP), LP and allocation of resources, LP definition, Linearity requirement
- Maximization Then Minimization problems.
- Graphical LP Minimization solution, Introduction, Simplex method definition, formulating the Simplex model.
- Linear Programming ¿ Simplex Method for Maximizing.
- Simplex maximizing example for similar limitations, Mixed limitations
- Example containing mixed constraints, Minimization example for similar limitations.
- Introduction to Genetic Algorithms and Neural Networks
- Introduction to simulated aneeling and branch and bound methods
- Using an optimisation algorithm on a maritime challenge (Logistic, resistance, strength, ...)
- Probability concepts and simulation, Monte Carlo Methods
This module aims to introduce students to use quantitive methods and techniques for effective decisions¿making; model formulation and applications that are used in solving business decision problems.
- has knowledge about OR science and its models and methods
- has knowledge about the fundamentals of artificial intelligence its background and application possibilities
- has an understanding of the limits of the different optimization methods.
- has knowledge about probability concept, understand the theory of statistics and can use it on practical problems
- has knowledge how to interprete optimisation results
- can solve analytic optimization problems using popular tools
- can program the basics of a numerical optimization method
- can use software for optimizing a real world maritime problem
- can analyze and structure a problem to extract the main parameters of a problem and describe the objects for optimization
- can plan, conduct and evaluate a the problem in an interdisciplinary framework
Recommended previous knowledge
The course contains lectures, supervision, net discussions, net based resources and work with portfolio elements. Lecturers and students will collaborate and communicate through the Internet-based system for teaching and learning; Moodle.
Compulsory learning activities
Yes, (will be specified in the course plan by semester start)
Portfolio (thesis paper, exercises, short written test)
Grading scale 1-5
Examination support material
Will be declared during the lectures.More about examination support material