EMO
2001
Springer
14 years 5 months ago
2001
Springer
Abstract. Topology design of enterprise networks is a hard combinatorial optimization problem. It has numerous constraints, several objectives, and a very noisy solution space. Bes...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, t...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
Abstract The performance of stochastic optimisers can be assessed experimentally on given problems by performing multiple optimisation runs, and analysing the results. Since an opt...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
When we try to implement a multi-objective genetic algorithm (MOGA) with variable weights for finding a set of Pareto optimal solutions, one difficulty lies in determining appropri...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
We compare two multiobjective evolutionary algorithms, with deterministic gradient based optimization methods for the dose optimization problem in high-dose rate (HDR) brachythera...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
This paper studies the influence of what are recognized as key issues in evolutionary multi-objective optimization: archiving (to keep track of the current non-dominated solutions...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
This paper examines the road train concept as a new alternative in long-distance freight traffic. The design of such a system is a difficult task since many different and conflicti...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
In High Dose Rate (HDR) brachytherapy the conventional dose optimization algorithms consider the multiple objectives in form of an aggregate function which combines individual obj...
EMO
2001
Springer
14 years 5 months ago
2001
Springer
EMO
2001
Springer
14 years 5 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...