#### Filter Results:

- Full text PDF available (212)

#### Publication Year

1996

2017

- This year (9)
- Last 5 years (74)
- Last 10 years (166)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Key Phrases

#### Method

Learn More

- Günther R. Raidl, Bryant A. Julstrom
- IEEE Trans. Evolutionary Computation
- 2003

The fundamental design choices in an evolutionary algorithm are its representation of candidate solutions and the operators that will act on that representation. We propose representing spanning trees in evolutionary algorithms for network design problems directly as sets of their edges, and we describe initialization, recombination, and mutation operators… (More)

- Günther R. Raidl
- 1998

This paper presents an improved hybrid Genetic Algorithm (GA) for solving the Multiconstrained 0–1 Knapsack Problem (MKP). Based on the solution of the LP-relaxed MKP, an efficient pre-optimization of the initial population is suggested. Furthermore, the GA uses sophisticated repair and local improvement operators which are applied to each newly generated… (More)

- Jakob Puchinger, Günther R. Raidl
- IWINAC
- 2005

In this survey we discuss different state-of-the-art approaches of combining exact algorithms and metaheuristics to solve combinatorial optimization problems. Some of these hybrids mainly aim at providing optimal solutions in shorter time, while others primarily focus on getting better heuristic solutions. The two main categories in which we divide the… (More)

- Günther R. Raidl, Jens Gottlieb
- Evolutionary Computation
- 2005

Our main aim is to provide guidelines and practical help for the design of appropriate representations and operators for evolutionary algorithms (EAs). For this purpose, we propose techniques to obtain a better understanding of various effects in the interplay of the representation and the operators. We study six different representations and associated… (More)

- Günther R. Raidl, Bryant A. Julstrom
- SAC
- 2003

Given a connected, weighted, undirected graph <i>G</i> and a bound <i>D</i>, the bounded-diameter minimum spanning tree problem seeks a spanning tree on <i>G</i> of lowest weight in which no path between two vertices contains more than <i>D</i> edges. This problem is NP-hard for 4 < <i>D</i> < <i>n</i> - 1, where n is the number of vertices in… (More)

- Christian Blum, Jakob Puchinger, Günther R. Raidl, Andrea Roli
- Appl. Soft Comput.
- 2011

Research inmetaheuristics for combinatorial optimizationproblemshas lately experienced anoteworthy shift towards the hybridization of metaheuristics with other techniques for optimization. At the same time, the focus of research has changed from being rather algorithm-oriented to being more problemoriented. Nowadays the focus is on solving the problem at… (More)

- Günther R. Raidl
- Hybrid Metaheuristics
- 2006

Manifold possibilities of hybridizing individual metaheuristics with each other and/or with algorithms from other fields exist. A large number of publications documents the benefits and great success of such hybrids. This article overviews several popular hybridization approaches and classifies them based on various characteristics. In particular with… (More)

- Günther R. Raidl
- 2000

The representation of candidate solutions and the variation operators are fundamental design choices in an evolutionary algorithm (EA). This paper proposes a novel representation technique and suitable variation operators for the degree-constrained minimum spanning tree problem. For a weighted, undirected graph G(V, E), this problem seeks to identify the… (More)

- Jennifer Hetzl, Andrea Maria Foerster, Günther R. Raidl, Ortrun Mittelsten Scheid
- The Plant journal : for cell and molecular…
- 2007

Cytosine methylation is a hallmark of epigenetic information in the DNA of many fungi, vertebrates and plants. The technique of bisulphite genomic sequencing reveals the methylation state of every individual cytosine in a sequence, and thereby provides high-resolution data on epigenetic diversity; however, the manual evaluation and documentation of large… (More)

- Günther R. Raidl
- 2002

This paper presents different variants of weight-coding in a genetic algorithm (GA) for solving the multiconstraint knapsack problem (MKP). In this coding, a chromosome is a vector of weights associated with the items of the MKP. The phenotype is obtained by using the weights to generate a modified version of the original problem and applying a decoding… (More)