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Combinatorial Optimization and Computational Complexity

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Part of the Natural Computing Series book series (NCS)

Abstract

Combinatorial optimization problems arise in several applications. Examples are the task of finding the shortest path from Paris to Rome in the road network of Europe or scheduling exams for given courses at a university. In this chapter, we give a basic introduction to the field of combinatorial optimization. Later on, we discuss how to measure the computational complexity of algorithms applied to these problems and point out some general limitations for solving difficult problems.

Keywords

  • Polynomial Time
  • Pareto Front
  • Approximation Ratio
  • Minimum Span Tree
  • Combinatorial Optimization Problem

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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  • DOI: 10.1007/978-3-642-16544-3_2
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Correspondence to Carsten Witt .

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© 2010 Springer-Verlag Berlin Heidelberg

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Neumann, F., Witt, C. (2010). Combinatorial Optimization and Computational Complexity. In: Bioinspired Computation in Combinatorial Optimization. Natural Computing Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16544-3_2

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  • DOI: https://doi.org/10.1007/978-3-642-16544-3_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16543-6

  • Online ISBN: 978-3-642-16544-3

  • eBook Packages: Computer ScienceComputer Science (R0)