| Budget Amount *help |
¥18,850,000 (Direct Cost: ¥14,500,000、Indirect Cost: ¥4,350,000)
Fiscal Year 2011: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2010: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2009: ¥2,730,000 (Direct Cost: ¥2,100,000、Indirect Cost: ¥630,000)
Fiscal Year 2008: ¥7,930,000 (Direct Cost: ¥6,100,000、Indirect Cost: ¥1,830,000)
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| Research Abstract |
In this paper, we examined the ability of evolutionary multiobjective optimization(EMO) algorithms to efficiently search for Pareto-optimal solutions of many-objective problems with a large number of conflicting objectives. We also examined the relation between the search ability of EMO algorithms and the dependency among objectives of many-objective problems. Based on these examinations, we proposed a new crossover operator for diversity maintenance, an approximation method for efficient hypervolume calculation, and the use of multiple scalarizing functions for efficient multiobjective search.
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