@conference {12,
	title = {Finding Multiple Global Optima Exploiting Differential Evolution{\textquoteright}s Niching Capability},
	booktitle = {IEEE Symposium on Differential Evolution, 2011. SDE 2011. (IEEE Symposium Series on Computational Intelligence)},
	year = {2011},
	month = {April},
	address = {Paris, France},
	abstract = {Handling multimodal functions is a very important and challenging task in evolutionary computation community, since most of the real-world applications exhibit highly multi-modal landscapes. Motivated by the dynamics and the proximity characteristics of Differential Evolution{\textquoteright}s mutation strategies tending to distribute the individuals of the population to the vicinity of the problem{\textquoteright}s minima, we introduce two new Differential Evolution mutation strategies. The new mutation strategies incorporate spatial information about the neighborhood of each potential solution and exhibit a niching formation, without incorporating any additional parameter. Experimental results on eight well known multimodal functions and comparisons with some state-of-the-art algorithms indicate that the proposed mutation strategies are competitive and very promising, since they are able to reliably locate and maintain many global optima throughout the evolution process.},
	doi = {10.1109/SDE.2011.5952058},
	author = {M. G. Epitropakis and V. P. Plagianakos and M. N. Vrahatis}
}
