@inproceedings{Deb2006d,
abstract = {Nadir point plays an important role in multi-objective optimization because of its importance in estimating the range of objective values corresponding to desired Pareto-optimal solutions and also in using many classical interactive optimization techniques. Since this point corresponds to the worst Pareto-optimal solution of each objective, the task of estimating the nadir point necessitates information about the whole Pareto optimal frontier and is reported to be a difficult task using classical means. In this paper, for the first time, we have proposed a couple of modifications to an existing evolutionary multi-objective optimization procedure to focus its search towards the extreme objective values frontwise. On up to 20-objective optimization problems, both proposed procedures are found to be capable of finding a near nadir point quickly and reliably. Simulation results are interesting and should encourage further studies and applications in estimating the nadir point, a process which should lead to a better interactive procedure of finding and arriving at a desired Pareto-optimal solution. Copyright 2006 ACM.},
author = {Deb, Kalyanmoy and Chaudhuri, Shamik and Miettinen, Kaisa},
booktitle = {GECCO 2006 - Genetic and Evolutionary Computation Conference},
doi = {10.1145/1143997.1144113},
isbn = {1595931864},
keywords = {Evolutionary multi-objective optimization (EMO),Ideal point,Multi-objective optimization,Nadir objective vector,Nadir point,Non-dominated sorting GA},
pages = {643--650},
publisher = {Association for Computing Machinery (ACM)},
title = {{Towards estimating nadir objective vector using evolutionary approaches}},
volume = {1},
year = {2006}
}