User profiles for Jürgen Branke
Juergen BrankeProfessor of Operational Research and Systems, Warwick Business School Verified email at wbs.ac.uk Cited by 20692 |
[BOOK][B] Multiobjective optimization: Interactive and evolutionary approaches
J Branke - 2008 - books.google.com
Multiobjective optimization deals with solving problems having not only one, but multiple,
often conflicting, criteria. Such problems can arise in practically every field of science, …
often conflicting, criteria. Such problems can arise in practically every field of science, …
[BOOK][B] Evolutionary optimization in dynamic environments
J Branke - 2012 - books.google.com
Evolutionary Algorithms (EAs) have grown into a mature field of research in optimization,
and have proven to be effective and robust problem solvers for a broad range of static real-…
and have proven to be effective and robust problem solvers for a broad range of static real-…
A multi-population approach to dynamic optimization problems
Time-dependent optimization problems pose a new challenge to evolutionary algorithms,
since they not only require a search for the optimum, but also a continuous tracking of the …
since they not only require a search for the optimum, but also a continuous tracking of the …
Integrating user preferences into evolutionary multi-objective optimization
Many real-world optimization problems involve multiple, typically conflicting objectives. Often,
it is very difficult to weigh the different criteria exactly before alternatives are known. …
it is very difficult to weigh the different criteria exactly before alternatives are known. …
Learning value functions in interactive evolutionary multiobjective optimization
This paper proposes an interactive multiobjective evolutionary algorithm (MOEA) that attempts
to learn a value function capturing the users' true preferences. At regular intervals, the …
to learn a value function capturing the users' true preferences. At regular intervals, the …
Evolutionary optimization in uncertain environments-a survey
Evolutionary algorithms often have to solve optimization problems in the presence of a wide
range of uncertainties. Generally, uncertainties in evolutionary computation can be divided …
range of uncertainties. Generally, uncertainties in evolutionary computation can be divided …
Memory enhanced evolutionary algorithms for changing optimization problems
J Branke - Proceedings of the 1999 Congress on Evolutionary …, 1999 - ieeexplore.ieee.org
Recently, there has been increased interest in evolutionary computation applied to changing
optimization problems. The paper surveys a number of approaches that extend the …
optimization problems. The paper surveys a number of approaches that extend the …
Finding knees in multi-objective optimization
Many real-world optimization problems have several, usually conflicting objectives. Evolutionary
multi-objective optimization usually solves this predicament by searching for the whole …
multi-objective optimization usually solves this predicament by searching for the whole …
Multiswarms, exclusion, and anti-convergence in dynamic environments
T Blackwell, J Branke - IEEE transactions on evolutionary …, 2006 - ieeexplore.ieee.org
Many real-world problems are dynamic, requiring an optimization algorithm which is able to
continuously track a changing optimum over time. In this paper, we explore new variants of …
continuously track a changing optimum over time. In this paper, we explore new variants of …
Multi-swarm optimization in dynamic environments
T Blackwell, J Branke - Workshops on applications of evolutionary …, 2004 - Springer
Many real-world problems are dynamic, requiring an optimization algorithm which is able to
continuously track a changing optimum over time. In this paper, we present new variants of …
continuously track a changing optimum over time. In this paper, we present new variants of …