A multiobjective approach to cost effective long-term groundwater monitoring using an elitist nondominated sorted genetic algorithm with historical data

By Patrick M. Reed, Barbara S. Minsker, David E. Goldberg. 2001

100 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Ocean Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/dd7c56ec1ece2a31d58144ed2eefba83a0465e48

How researchers see this paper

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

In Computational Theory and Mathematics

1. Patrick M. Reed
2. Joshua B. Kollat
3. David Hadka
4. Kalyanmoy Deb
5. Himanshu Jain

In Ocean Engineering

1. Patrick M. Reed
2. Joshua B. Kollat
3. David Hadka

In Water Science and Technology

1. Joshua B. Kollat
2. Patrick M. Reed

Citations in the corpus

• Comparing state-of-the-art evolutionary multi-objective algorithms for long-term groundwater monitoring design (2005, methodology): “More formally, from evolutionary algorithm theory [19,59], the population size required by MOEAs to solve multi-objective problems is directly related to the size of the Pareto-optimal set.”