In this paper a new approach to solve constrained multi-objective problems by way of evolutionary multi-objective optimization is introduced. In contrast to former evolutionary ap...
Multiobjective optimization in general aims at learning about the problem at hand. Usually the focus lies on objective space properties such as the front shape and the distributio...
Abstract. In this paper, we elaborate how decision space diversity can be integrated into indicator-based multiobjective search. We introduce DIOP, the diversity integrating multio...
Exponential increases in architectural design complexity threaten to make traditional processor design optimization techniques intractable. Genetically programmed response surface...
Designing custom solutions has been central to meeting a range of stringent and specialized needs of embedded computing, along such dimensions as physical size, power consumption, ...
Krishna V. Palem, Lakshmi N. Chakrapani, Sudhakar ...