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GECCO
2007
Springer

SNDL-MOEA: stored non-domination level MOEA

9 years 7 months ago
SNDL-MOEA: stored non-domination level MOEA
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -MOEA. However, they lack an archive population sorted into levels of non-domination, making them unsuitable for construction problems where some type of backtracking to earlier intermediate solutions is required. In this paper we introduce our Stored Non-Domination Level (SNDL) MOEA for solving such construction problems. SNDL-MOEA combines some of the best features of NSGA-II and -MOEA with the ability to store and recall intermediate solutions necessary for construction problems. We present results for applying SNDL-MOEA to the Tight Single Change Covering Design (TSCCD) construction problem, demonstrating its applicability. Furthermore, we show with a detailed performance comparison between SNDL-MOEA, NSGA-II, and -MOEA on two standard test series that SNDL-MOEA is capable of outperforming NSGA-II and is co...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilkerson
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