An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method

By Marco Laumanns, Lothar Thiele, Eckart Zitzler. European Journal of Operational Research, 2006

410 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms (2014, methodology): “These techniques group many different MOEA strategies: independent sampling (Srigiriraju 2000), criterion selection—Vector Evaluated Genetic Algorithm (VEGA) and extensions (Kursawe 1991; Hajela and Lin 1992), aggregation selection—weighted sums, constraint and objective combinations or hybrid searc”
An exact epsilon-constraint method for bi-objective combinatorial optimization problems: Application to the Traveling Salesman Problem with Profits (2009, methodology): “This issue has recently been addressed for the general mult i-objective case in [21], but it remains an important drawback of the ǫ-constraint method.”
A survey of variants and extensions of the location-routing problem (2015, methodology): “To deal with the multi-objective nature of the problem, the adaptive epsilon-constraint algorithm of Laumanns et al. (2006), which is based on solving a sequence of single-objective problems, is applied.”