@inproceedings{3a8573fd990d45c6a644e6a06bbae363,
title = "An evolutionary multi-objective crowding algorithm (EMOCA): Benchmark test function results",
abstract = "A new evohitionaiy multi-objective crowding algorithm (EMOCA) is evaluated using nine benchmark multi-objective optimization problems, and shown to produce non-dominated solutions with significant diversity, outperforming state- of-the-art multi-objective evolutionary algorithms viz.. Non-dominated Sorting Genetic Algorithm - II (NSGA-II). Strength Pareto Evolutionary algorithm II (SPEA-II) and Pareto Archived Evolution Strategy (PAES) on most of the test problems. The key new approach in EMOCA is to use a diversity-emphasizing probabilistic approach in determining whether an offspring individual is considered in the replacement selection phase, along with the use of a non-domination ranking scheme. This approach appears to provide a useful compromise between the two concerns of dominance and diversity in the evolving population.",
author = "Ramesh Rajagopalan and Mohan, {Chilukuri K.} and Mehrotra, {Kishan G.} and Varshney, {Pramod K.}",
year = "2005",
language = "English (US)",
isbn = "0972741216",
series = "Proceedings of the 2nd Indian International Conference on Artificial Intelligence, IICAI 2005",
pages = "1488--1506",
booktitle = "Proceedings of the 2nd Indian International Conference on Artificial Intelligence, IICAI 2005",
note = "2nd Indian International Conference on Artificial Intelligence, IICAI 2005 ; Conference date: 20-12-2005 Through 22-12-2005",
}