A fuzzy rule-based meta-scheduler with evolutionary learning for grid computing

Engineering Applications of Artificial Intelligence

Volumn 23, Issue 7, 2010, Pages 1072-1082

  Prado, R P ^a   Garca Galn, S ^a   Yuste, A J ^a   Muoz Expsito, J E ^a  

^a University of Jan   (Spain)

Author keywords

Evolutionary algorithms; Fuzzy rule based systems; Genetic fuzzy systems; Grid computing; Scheduling

Indexed keywords

COMPLEX SEARCH SPACES; COMPUTATIONAL EFFORT; COMPUTATIONAL FRAMEWORK; DYNAMIC NATURE; EVOLUTIONARY LEARNING; FUZZY RULE BASIS; FUZZY RULE-BASED SYSTEMS; GENETIC FUZZY SYSTEMS; HIGH POTENTIAL; HIGH QUALITY; KNOWLEDGE BASIS; LARGE-SCALE PROBLEM; LEARNING STRATEGY; META-SCHEDULERS; MICHIGAN; NEAR-OPTIMAL SOLUTIONS; NEW STRATEGY; PITTSBURGH APPROACH; SCHEDULING RESEARCH; SCHEDULING STRATEGIES; SCHEDULING SYSTEMS; SCIENCE , ENGINEERING AND TECHNOLOGIES;

CONVERGENCE OF NUMERICAL METHODS; EVOLUTIONARY ALGORITHMS; FUZZY LOGIC; FUZZY RULES; FUZZY SETS; FUZZY SYSTEMS; KNOWLEDGE ACQUISITION; KNOWLEDGE BASED SYSTEMS; SCHEDULING ALGORITHMS;

GRID COMPUTING;

EID: 77957865649     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2010.07.002     Document Type: Article

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