OR
2010
Springer
13 years 9 months ago
2010
Springer
Abstract With potential application to a variety of industries, fleet sizing problems present a prevalent and significant challenge for engineers and managers. This is especially t...
GECCO
2010
Springer
14 years 25 days ago
2010
Springer
Evolutionary multi-objective optimization deals with the task of computing a minimal set of search points according to a given set of objective functions. The task has been made e...
COR
2010
14 years 2 months ago
2010
Abstract -- Open zero-buffer multi-server general queueing networks occur throughout a number of physical systems in the semi-process and process industries. In this paper, we eval...
GECCO
2008
Springer
14 years 3 months ago
2008
Springer
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
CEC
2009
IEEE
14 years 5 months ago
2009
IEEE
— The urban transit routing problem (UTRP) for public transport systems involves finding a set of efficient transit routes to meet customer demands. The UTRP is an NPHard, high...
GECCO
2006
Springer
14 years 6 months ago
2006
Springer
The field of Differential Evolution (DE) has demonstrated important advantages in single objective optimization. To date, no previous research has explored how the unique characte...
GECCO
2006
Springer
14 years 6 months ago
2006
Springer
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 s...
EVOW
2004
Springer
14 years 6 months ago
2004
Springer
A novel approach for sensor planning, which incorporates multi-objective optimization principals into the autonomous design of sensing strategies, is presented. The study addresses...
PPSN
1998
Springer
14 years 6 months ago
1998
Springer
This paper presents a novel evolutionary approach of approximating the shape of the Pareto-optimal set of multi-objective optimization problems. The evolutionary algorithm (EA) use...
EMO
2001
Springer
14 years 6 months ago
2001
Springer
One common characterization of how simple hill-climbing optimization methods can fail is that they become trapped in local optima - a state where no small modi cation of the curren...