Bayesian Study on When to Restart Heuristic Search
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F17%3A00316547" target="_blank" >RIV/68407700:21340/17:00316547 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Bayesian Study on When to Restart Heuristic Search
Original language description
Heuristic algorithm performance measures assess the quality of a search process by statistically analyzing its performance data, typically the number of objec- tive function evaluations before optimal or acceptable solution is found. Such criteria are not only intended to provide the verdict on which algorithm is better for what task, but also to help make the best possible use of a given algorithm on a given task. This target may be achieved by an appropriate restart strategy of the search process. In our paper we formulate axiomatic approach which also describes existing performance measures. Novelty of this paper consist in performance measure analysis via Marko- vian chain calculation and its direct Bayesian estimation based on Monte Carlo sim- ulations. Practical results are demonstrated on combinatorial optimization problems and are applicable e.g. to NP-hard problems from the field of operational research.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Mathematical Methods in Economics MME 2017
ISBN
978-80-7435-678-0
ISSN
—
e-ISSN
—
Number of pages
6
Pages from-to
480-485
Publisher name
Univerzita Hradec Králové
Place of publication
Hradec Králové
Event location
Hradec Králové
Event date
Sep 13, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—