TY - GEN
T1 - Recent developed evolutionary algorithms for the multi-objective optimization of design allocation problems
AU - Taboada, Heidi A.
AU - Coit, David W.
AU - Wattanapongsakorn, Naruemon
PY - 2008
Y1 - 2008
N2 - This paper presents an overview of a collection of recent developed evolutionary algorithms for solving different types of allocation problems under the consideration of several conflicting objectives. These algorithms are: MOEA-DAP, MOMS-GA and the Multi-Task Multi-State MOEA. MOEA-DAP is a custom multiple objective evolutionary algorithm for solving design allocation problems. MOEA-DAP considers binarystate reliability. In contrast, MOMS-GA, which is a natural extension of MOEA-DAP, works under the assumption that both, the system and its components, experience more than two possible states of performance. The last algorithm presented in the paper is the Multi-Task Multi-State MOEA, which is a multiple objective algorithm designed to determine optimal configurations of multi-state, multi-task production systems based on availability analysis. These three algorithms are novel approaches that offer distinct advantages to current existing MOEAs. copy; 2008 ICQR.
AB - This paper presents an overview of a collection of recent developed evolutionary algorithms for solving different types of allocation problems under the consideration of several conflicting objectives. These algorithms are: MOEA-DAP, MOMS-GA and the Multi-Task Multi-State MOEA. MOEA-DAP is a custom multiple objective evolutionary algorithm for solving design allocation problems. MOEA-DAP considers binarystate reliability. In contrast, MOMS-GA, which is a natural extension of MOEA-DAP, works under the assumption that both, the system and its components, experience more than two possible states of performance. The last algorithm presented in the paper is the Multi-Task Multi-State MOEA, which is a multiple objective algorithm designed to determine optimal configurations of multi-state, multi-task production systems based on availability analysis. These three algorithms are novel approaches that offer distinct advantages to current existing MOEAs. copy; 2008 ICQR.
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M3 - Conference contribution
AN - SCOPUS:84906998296
SN - 9789810594046
T3 - ICQR 2007 - Proceedings of the 5th International Conference on Quality and Reliability
SP - 337
EP - 342
BT - ICQR 2007 - Proceedings of the 5th International Conference on Quality and Reliability
PB - Research Publishing Services
T2 - 5th International Conference on Quality and Reliability, ICQR 2007
Y2 - 5 November 2007 through 7 November 2007
ER -