PA184 Heuristic Methods for Search and Optimization

Fakulta informatiky
jaro 2010
Rozsah
2/0/0. 2 kr. (plus ukončení). Ukončení: zk.
Vyučující
Dario Landa-Silva, BEng, MSc, PhD (přednášející)
doc. Mgr. Hana Rudová, Ph.D. (přednášející)
Garance
prof. RNDr. Václav Matyáš, M.Sc., Ph.D.
Katedra počítačových systémů a komunikací - Fakulta informatiky
Kontaktní osoba: doc. Mgr. Hana Rudová, Ph.D.
Rozvrh
Po 26. 4. 8:00–9:50 B011, 14:00–17:50 B011, Út 27. 4. 8:00–9:50 B011, 12:00–13:50 B011, St 28. 4. 8:00–9:50 B410, Čt 29. 4. 8:00–9:50 B011, 16:00–17:50 C511, Pá 30. 4. 10:00–11:50 B003, 13:00–16:50 B003
Omezení zápisu do předmětu
Předmět je nabízen i studentům mimo mateřské obory.
Mateřské obory/plány
předmět má 36 mateřských oborů, zobrazit
Cíle předmětu
This course explores selected state-of-the-art heuristic search methods and their application to find solutions for complex optimisation and other search problems. The methods studied are selected from the latest specialised research literature. Students will achieve awareness of the latest advances in heuristic search methods research and will also implement some of these methods to solve a given problem. This course provides the knowledge and skills to design and implement solution procedures to solve a range of complex problems in industry and business.
Osnova
  • Introduction: overview of the course, an insight into heuristics.
  • Principles of heuristic search: traditional techniques, motivation for heuristic search, basic concepts in heuristic search.
  • Local search: neighbourhood search, iterative improvement, escaping local optima.
  • Meta-heuristics: motivation for meta-heuristics, threshold acceptance, great deluge, simulated annealing.
  • Evolutionary algorithms: basic concepts, design of EAs, types of EAs.
  • Constraint handling: general considerations, rejecting infeasibility, repairing solutions, penalising infeasibility, enforcing feasibility, constraints as objectives.
  • Evaluating heuristic performance: fitness landscapes, empirical analysis of landscapes, experiments with heuristic search.
  • Hybrid heuristics: hybrids of SA, TS and GA, types of hybrid heuristics, examples of hybrids.
  • Software libraries for heuristics: programming frameworks, modelling languages, other development toolkits.
  • New ideas and future research.
Literatura
  • Search methodologies : introductory tutorials in optimization and decision support techniques. Edited by Edmund Burke - Graham Kendall. New York: Springer, 2005. vi, 620. ISBN 0387234608. info
  • HOOS, Holger H. a Thomas STÜTZLE. Stochastic Local Search: Foundations and Applications. Morgan Kaufmann / Elsevier, 2004. info
Výukové metody
Course is taught in a block of lectures during one or two weeks of the semester. Classical lectures are accompanied by workshops where students work hands-on putting in practice (programming) the techniques learned.
Metody hodnocení
Examination consists of the final written exam evaluated by 70 points and course work evaluated by 30 points. Completion of the course requires 55 points at least (A: 100-90, B 89-80, C 79-70, D 69-60, E59-55). The written exam includes: key concepts, description of algorithms, analysis and comparison of algorithms, constraint handling techniques. The coursework includes: implementation of algorithm(s) for a given problem, report and presentation.
Vyučovací jazyk
Angličtina
Informace učitele

Aktualizovaný rozvrh:
  • Po 26.4.2010 8:00- 9:50 B011
  • Po 26.4.2010 14:00-17:50 B011
  • Ut 27.4.2010 8:00-9:50 B011
  • Ut 27.4.2010 12:00-13:50 B011
  • St 28.4.2010 8:00- 9:50 B410
  • Ct 29.4.2010 8:00- 9:50 B011
  • Ct 29.4.2010 16:00-17:50 C511
  • Pa 30.4.2010 10:00-11:50 B003
  • Pa 30.4.2010 13:00-16:50 B003
Další komentáře
Studijní materiály
Předmět je vyučován jednorázově.

  • Statistika zápisu (nejnovější)
  • Permalink: https://is.muni.cz/predmet/fi/jaro2010/PA184