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Operations Research - Period 4
Social Sciences & Humanities Program
Amsterdam, Netherlands
Dates: 1/31/20 - 5/30/20
Operations Research - Period 4
OVERVIEW
CEA CAPA Partner Institution: Vrije Universiteit Amsterdam
Location: Amsterdam, Netherlands
Primary Subject Area: Mathematics
Instruction in: English
Course Code: X_400618
Transcript Source: Partner Institution
Course Details: Level 100
Recommended Semester Credits: 3
Contact Hours: 84
DESCRIPTION
The course is a first introduction to optimization. Given a large number of decisions to be made, subject to certain constraints on what combination of these decisions are allowed, what choices will lead to the best possible outcome (such as maximum profit)?
We will discuss the modelling of verbally-described practical problems using appropriate mathematical formulations - in particular, linear optimization and integer linear optimization models. Extremely powerful software tools for solving such models, and they are widely used in industry. We will see the basic algorithmic principles upon which these software tools are based: in particular, the simplex method for linear optimization, and building on this, the branch-and-bound method for integer linear optimization.
Many problems have specific structure that can be exploited to obtain much faster algorithms. We will see this in two contexts:
- Network optimization problems. What is the shortest way to get between two nodes in a network? Or the cheapest way to build a road network between a given collection of cities so that all cities are connected? We will develop efficient algorithms for these (and similar) problems.
- Dynamic programming. This is a fundamental technique in computer science. Determining whether and in which way this technique can be applied to a given problem is challenging, but it can provide extremely fast algorithms.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA?s recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.
We will discuss the modelling of verbally-described practical problems using appropriate mathematical formulations - in particular, linear optimization and integer linear optimization models. Extremely powerful software tools for solving such models, and they are widely used in industry. We will see the basic algorithmic principles upon which these software tools are based: in particular, the simplex method for linear optimization, and building on this, the branch-and-bound method for integer linear optimization.
Many problems have specific structure that can be exploited to obtain much faster algorithms. We will see this in two contexts:
- Network optimization problems. What is the shortest way to get between two nodes in a network? Or the cheapest way to build a road network between a given collection of cities so that all cities are connected? We will develop efficient algorithms for these (and similar) problems.
- Dynamic programming. This is a fundamental technique in computer science. Determining whether and in which way this technique can be applied to a given problem is challenging, but it can provide extremely fast algorithms.
Vrije Universiteit Amsterdam (VU Amsterdam) awards credits based on the ECTS system. Contact hours listed under a course description may vary due to the combination of lecture-based and independent work required for each course therefore, CEA?s recommended credits are based on the ECTS credits assigned by VU Amsterdam. 1 ECTS equals 28 contact hours assigned by VU Amsterdam.