I. Wegener

发表

Search Problems

Rudolf Ahlswede, Ingo Wegener, R. Ahlswede, 1987 .

Combinatorics, Probability and Computing

B. Bollobás, N. Alon, I. Wegener, 2006 .

Branching Programs and Binary Deci-sion Diagrams-Theory and Applications

I. Wegener, 1987 .

VARIABLE ORDERINGS FOR OBDDs , SIMULATED ANNEALING

I. Wegener, FUNCTIONBeate, Bollig, 1996 .

A rigorous complexity analysis of the (1+1) evolutionary algorithm for linear functions with Boolean inputs

I. Wegener, Stefan Droste, T. Jansen, 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

On the Optimization of Monotone Polynomials by the (1+1) EA and Randomized Local Search

I. Wegener, C. Witt, 2003, GECCO.

The complexity of Boolean functions

Ingo Wegener, I. Wegener, 1987 .

A Rigorous Complexity Analysis Of The (1 + 1)- Evolution Strategy For Separable Functions With Boole

I. Wegener, Stefan Droste, T. Jansen, 1998 .

The Analysis of Evolutionary Algorithms on Sorting and Shortest Paths Problems

I. Wegener, J. Scharnow, K. Tinnefeld, 2004 .

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Evolutionary Algorithms-How to Cope With Plateaus of Constant Fitness and When to Reject Strings of the Same Fitness

Thomas Jansen, Ingo Wegener, I. Wegener, 2001 .

Towards a Theory of Randomized Search Heuristics

Ingo Wegener, I. Wegener, 2003, MFCS.

SIMULATED ANNEALING TO IMPROVE VARIABLE ORDERINGS FOR OBDDsBeate

I. Wegener, Bollig, 1995 .

GECCO 2007: Genetic and Evolutionary Computation Conference

Thomas Stützle, Riccardo Poli, Mauro Birattari, 2007 .

Simulated Annealing Beats Metropolis in Combinatorial Optimization

Ingo Wegener, I. Wegener, 2005, ICALP.

Dynamic Parameter Control in Simple Evolutionary Algorithms

I. Wegener, Stefan Droste, T. Jansen, 2001 .

Optimal Decision Trees and One-Time-Only Branching Programs for Symmetric Boolean Functions

Ingo Wegener, I. Wegener, 1984, Inf. Control..

Complexity Theoretical Aspects of OFDDs

Beate Bollig, Ingo Wegener, Martin Sauerhoff, 1996 .

COMPLEXITY THEORETICAL ASPECTS OF

I. Wegener, Bollig, OFDDsBeate, 1996 .

UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods On the Design and Analysis of Evolutionary Algorithms

I. Wegener, 2004 .

Theoretical Aspects of Evolutionary Algorithms

I. Wegener, Ingo Wegener, 2001, ICALP.

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Fitness Landscapes Based on Sorting and Shortest Path Problems

I. Wegener, J. Scharnow, K. Tinnefeld, 2022 .

Boolean Function Complexity: Symmetry Functions in AC° can be Computed in Constant Depth with Very Small Size

I. Wegener, Norbert Wurm, Sang-Zin Yi, 1992 .

On the Behavior of the (1+1) Evolutionary Algorithm on Quadratic Pseudo-Boolean Functions

I. Wegener, C. Witt, 2001 .

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods A Natural and Simple Function Which is Hard For All Evolutionary Algorithms

I. Wegener, Stefan Droste, T. Jansen, 2007 .

www.econstor.eu Modified repeated median filters

T. Bernholt, I. Wegener, 2004 .

Prof. Dr. math. Ingo Wegener

I. Wegener, 2010 .

Boolean Functions whose Monotone Complexity is of Size n2/log n

Ingo Wegener, I. Wegener, 1981, Theoretical Computer Science.

Approximability and Non-Approximability by Binary Decision Diagrams ∗ ( Extended Abstract )

I. Wegener, B. Bollig, Martin Sauerhoff, 2007 .

ON THE COMPLEXITY OF THE HIDDEN WEIGHTED BITFUNCTION FOR VARIOUS BDD MODELSBeate

I. Wegener, Bollig, Martin Sauerho, 1998 .

Advances in Computational Intelligence: Theory and Practice

Hans-Paul Schwefel, Ingo Wegener, Klaus Weinert, 2002 .

I. Wegener, 2003 .

Proceedings of the 33rd international conference on Automata, Languages and Programming - Volume Part II

Michele Bugliesi, Bart Preneel, Vladimiro Sassone, 2006 .

Automata, Languages and Programming, 33rd International Colloquium, ICALP 2006, Venice, Italy, July 10-14, 2006, Proceedings, Part I

Michele Bugliesi, Bart Preneel, Vladimiro Sassone, 2006, ICALP.

Automata, Languages and Programming: 33rd International Colloquium, ICALP 2006, Venice, Italy, July 10-14, 2006, Proceedings, Part II (Lecture Notes in Computer Science)

Michele Bugliesi, Bart Preneel, Vladimiro Sassone, 2006 .

Complexity Theory

Ingo Wegener, I. Wegener, 2005 .

Identication of Partial Disjunction, Parity, and Threshold Functions 3

I. Wegener, K. Tsuchida, 1999 .

Minimum spanning trees made easier via multi-objective optimization

I. Wegener, F. Neumann, 2005, GECCO.

Approximability and Nonapproximability by Binary Decision Diagrams (Extented Abstract)

I. Wegener, B. Bollig, 2000 .

Introduction: Workshop on Boolean Functions and Applications

Juraj Hromkovic, Ingo Wegener, I. Wegener, 2000, ICALP Satellite Workshops.

Branching Programs and Binary Decision Diagrams

Ingo Wegener, I. Wegener, 1987 .

Bottom-Up-Heap Sort, a New Variant of Heap Sort Beating on Average Quick Sort (if n is not very small)

Ingo Wegener, I. Wegener, 1990, MFCS.

Advances in Computational Intelligence

Hans-Paul Schwefel, Ingo Wegener, Klaus Weinert, 2003, Natural Computing Series.

Optimal Decisions Trees and One-Time-Only Branching Programs for Symmetric Boolean Functions

Ingo Wegener, I. Wegener, 1984, CAAP.

13. Applications in Verification and Model Checking

Ingo Wegener, I. Wegener, 2000 .

Genetic and Evolutionary Computation Conference 2008 : GECCO 2008

Julian F. Miller, Giuliano Antoniol, Maarten Keijzer, 2008, GECCO 2008.

Search Problems

R. Ahlswede, I. Wegener, 1987 .

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Minimum Spanning Trees Made Easier via Multi-objective Optimization Minimum Spanning Trees Made Easier via Multi-objective Optimization

I. Wegener, F. Neumann, 2022 .

Relating Monotone Formula Size and Monotone Depth of Boolean Functions

Ingo Wegener, I. Wegener, 1983, Inf. Process. Lett..

Theory of Evolutionary Algorithms and Genetic Programming

Thomas Jansen, Günter Rudolph, Hans-Paul Schwefel, 2003 .

How to analyse evolutionary algorithms

Hans-Paul Schwefel, Hans-Georg Beyer, Ingo Wegener, 2002, Theor. Comput. Sci..

Real royal road functions--where crossover provably is essential

Ingo Wegener, Thomas Jansen, I. Wegener, 2001, Discret. Appl. Math..

On separating systems whose elements are sets of at most k elements

Ingo Wegener, I. Wegener, 1979, Discret. Math..

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods on the Choice of the Offspring Population Size in Evolutionary Algorithms on the Choice of the Offspring Population Size in Evolutionary Algorithms

Kenneth A. De Jong, Ingo Wegener, Thomas Jansen, 2004 .

On the analysis of a simple evolutionary algorithm on quadratic pseudo-boolean functions

Ingo Wegener, Carsten Witt, I. Wegener, 2005, J. Discrete Algorithms.

On the analysis of the (1+1) evolutionary algorithm

Thomas Jansen, Ingo Wegener, Stefan Droste, 2002, Theor. Comput. Sci..

A comparison of simulated annealing with a simple evolutionary algorithm on pseudo-boolean functions of unitation

Thomas Jansen, Ingo Wegener, I. Wegener, 2007, Theor. Comput. Sci..

Minimum spanning trees made easier via multi-objective optimization

Frank Neumann, Ingo Wegener, I. Wegener, 2005, GECCO '05.

Circuit Complexity

Peter L. Hammer, Yves Crama, Ingo Wegener, 2010, Boolean Models and Methods.

More on the Complexity of Slice Functions

Ingo Wegener, I. Wegener, 1986, Theor. Comput. Sci..

On the Complexity of Slice Functions

Ingo Wegener, I. Wegener, 1984, Theor. Comput. Sci..

Proving lower bounds of the monotone complexity of Boolean functions

Ingo Wegener, I. Wegener, 1983, Logic and Machines.

A new lower bound on the monotone network complexity of Boolean sums

Ingo Wegener, I. Wegener, 1980, Acta Informatica.

Switching Functions Whose Monotone Complexity is Nearly Quadratic

Ingo Wegener, I. Wegener, 1979, Theor. Comput. Sci..

The Number of Knight's Tours Equals 33, 439, 123, 484, 294 - Counting with Binary Decision Diagrams

Ingo Wegener, Martin Löbbing, I. Wegener, 1996, Electron. J. Comb..

Randomized local search, evolutionary algorithms, and the minimum spanning tree problem

Ingo Wegener, Frank Neumann, I. Wegener, 2004, Theor. Comput. Sci..

Real royal road functions for constant population size

Ingo Wegener, Tobias Storch, I. Wegener, 2003, Theor. Comput. Sci..

Evolutionary Algorithms and the Maximum Matching Problem

Ingo Wegener, Oliver Giel, I. Wegener, 2003, STACS.

Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions

Ingo Wegener, I. Wegener, 2003 .

Theoretical Aspects of Evolutionary Algorithms

Ingo Wegener, I. Wegener, 2001, ICALP.

On the utility of populations in evolutionary algorithms

Ingo Wegener, Thomas Jansen, I. Wegener, 2001 .

On the Optimization of Unimodal Functions with the (1 + 1) Evolutionary Algorithm

Thomas Jansen, Ingo Wegener, Stefan Droste, 1998, PPSN.

A Rigorous Complexity Analysis of the (1 + 1) Evolutionary Algorithm for Separable Functions with Boolean Inputs

Ingo Wegener, Thomas Jansen, Stefan Droste, 1998, Evolutionary Computation.

Tight Bounds for Blind Search on the Integers and the Reals

Martin Dietzfelbinger, Ingo Wegener, Philipp Woelfel, 2008, Combinatorics, Probability and Computing.

On the analysis of a dynamic evolutionary algorithm

Thomas Jansen, Ingo Wegener, I. Wegener, 2006, J. Discrete Algorithms.

The one-dimensional Ising model: Mutation versus recombination

Ingo Wegener, Simon Fischer, I. Wegener, 2005, Theor. Comput. Sci..

On the Optimization of Monotone Polynomials by Simple Randomized Search Heuristics

Ingo Wegener, Carsten Witt, I. Wegener, 2005, Combinatorics, Probability and Computing.

The analysis of evolutionary algorithms on sorting and shortest paths problems

Ingo Wegener, Jens Scharnow, Karsten Tinnefeld, 2004, J. Math. Model. Algorithms.

UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization

Thomas Jansen, Ingo Wegener, Stefan Droste, 2004 .

The Analysis of Evolutionary Algorithms—A Proof That Crossover Really Can Help

Thomas Jansen, Ingo Wegener, I. Wegener, 2002, Algorithmica.

Dynamic Parameter Control in Simple Evolutionary Algorithms

Thomas Jansen, Ingo Wegener, Stefan Droste, 2001, FOGA.

On the Analysis of Evolutionary Algorithms - A Proof That Crossover Really Can Help

Thomas Jansen, Ingo Wegener, I. Wegener, 1999 .

On the influence of the variable ordering for algorithmic learning using OBDDs

Ingo Wegener, Matthias Krause, Petr Savický, 2005, Inf. Comput..

Can Single-Objective Optimization Profit from Multiobjective Optimization?

Ingo Wegener, Frank Neumann, I. Wegener, 2008, Multiobjective Problem Solving from Nature.

Detecting high-order interactions of single nucleotide polymorphisms using genetic programming

Ingo Wegener, Holger Schwender, Robin Nunkesser, 2007, Bioinform..

Optimal Depth, Very Small Size Circuits for Symmetric Functions in AC0

Johan Håstad, Ingo Wegener, Norbert Wurm, 1994, Inf. Comput..

Optimal Lower Bounds on the Depth of Polynomial-Size Threshold Circuits for Some Arithmetic Functions

Ingo Wegener, I. Wegener, 1993, Inf. Process. Lett..

Approximations by OBDDs and the Variable Ordering Problem

Ingo Wegener, Matthias Krause, Petr Savický, 1999, ICALP.

Time-Space Trade-offs for Branching Programs

Ingo Wegener, I. Wegener, 1986, J. Comput. Syst. Sci..

A simplified correctness proof for a well-known algorithm computing strongly connected components

Ingo Wegener, I. Wegener, 2002, Inf. Process. Lett..

Asymptotically Optimal Bounds for OBDDs and the Solution of Some Basic OBDD Problems

Beate Bollig, Ingo Wegener, I. Wegener, 2000, J. Comput. Syst. Sci..

A Very Simple Function that Requires Exponential Size Read-Once Branching Programs

Beate Bollig, Ingo Wegener, I. Wegener, 1998, Inf. Process. Lett..

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods How to Analyse Evolutionary Algorithms

H. Schwefel, I. Wegener, H. Beyer, 2022 .

Analysis of composition complexity and how to obtain smaller canonical graphs

Yuan Lu, Ingo Wegener, Jawahar Jain, 2000, Proceedings 37th Design Automation Conference.

Searching Randomly for Maximum Matchings

Ingo Wegener, Oliver Giel, I. Wegener, 2004, Electron. Colloquium Comput. Complex..

Improving the Variable Ordering of OBDDs Is NP-Complete

Beate Bollig, Ingo Wegener, I. Wegener, 1996, IEEE Trans. Computers.

Graph Driven BDDs - A New Data Structure for Boolean Functions

Ingo Wegener, Detlef Sieling, I. Wegener, 1995, Theor. Comput. Sci..

Optimization with randomized search heuristics - the (A)NFL theorem, realistic scenarios, and difficult functions

Thomas Jansen, Ingo Wegener, Stefan Droste, 2002, Theor. Comput. Sci..

BDDs--design, analysis, complexity, and applications

Ingo Wegener, I. Wegener, 2004, Discret. Appl. Math..

Complexity theory - exploring the limits of efficient algorithms

Ingo Wegener, I. Wegener, 2005 .

On the complexity of branching programs and decision trees for clique functions

Ingo Wegener, I. Wegener, 1988, JACM.

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions

I. Wegener, 2006 .

On the Behavior of the (1+1) Evolutionary Algorithm on Quadratic Pseudo-Boolean Functions

I. Wegener, C. Witt, 2001 .

UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Evolutionary Algorithms and the Maximum Matching Problem

I. Wegener, O. Giel, 2006 .

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Evolutionary Algorithms and the Maximum Matching Problem Evolutionary Algorithms and the Maximum Matching Problem

I. Wegener, O. Giel, 2022 .

On the local performance of simulated annealing and the (1+1) evolutionary algorithm

Thomas Jansen, Ingo Wegener, I. Wegener, 2006, GECCO.

INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods How to analyse evolutionary algorithms

H. Schwefel, I. Wegener, H. Beyer, 2002 .

Ingo Wegener, I. Wegener, 2001 .

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods How to Analyse Evolutionary Algorithms

H. Schwefel, I. Wegener, H. Beyer, 2022 .

The Ising model on the ring

I. Wegener, S. Fischer, 2004 .

The Ising Model: Simple Evolutionary Algorithms as Adaptation Schemes

I. Wegener, T. Jansen, Patrick Briest, 2004 .

Dynamic Parameter Control in Simple Evolutionary Algorithms

I. Wegener, Stefan Droste, T. Jansen, 2001 .

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Perhaps Not a Free Lunch but at Least a Free Appetizer Perhaps Not a Free Lunch but at Least a Free Appetizer

Thomas Jansen, Ingo Wegener, Stefan Droste, 2022 .

I. Wegener, Stefan Droste, T. Jansen, 2022 .

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions

I. Wegener, 2001 .

The analysis of evolutionary algorithms on sorting and shortest paths problems

I. Wegener, J. Scharnow, Karsten Tinnefeld, 2004, J. Math. Model. Algorithms.

On the analysis of the (1+1) evolutionary algorithm

I. Wegener, Stefan Droste, T. Jansen, 2002, Theor. Comput. Sci..

Design and Management of Complex Technical Processes and Systems by Means of Computational Intelligence Methods Searching Randomly for Maximum Matchings Searching Randomly for Maximum Matchings

I. Wegener, O. Giel, 2022 .

The Analysis of Evolutionary Algorithms—A Proof That Crossover Really Can Help

I. Wegener, T. Jansen, 2002, Algorithmica.

Evolutionary Algorithms , Randomized Local Search , and the Maximum Matching Problem ∗

Ingo Wegener, Oliver Giel, I. Wegener, 2003 .

On the Performance of WEAK-HEAPSORT

Ingo Wegener, Stefan Edelkamp, S. Edelkamp, 2000, STACS.

Approximations by OBDDs and the Variable Ordering Problem

I. Wegener, Matthias Krause, Petr Savický, 1999, ICALP.

Modified repeated median filters

Ingo Wegener, Ursula Gather, Roland Fried, 2006, Stat. Comput..

Bottom-up-heat sort, a new variant of heap sort beating an average quick sort

Ingo Wegener, I. Wegener, 1990 .

On converting CNF to DNF

Peter Bro Miltersen, Jaikumar Radhakrishnan, Ingo Wegener, 2003, Theor. Comput. Sci..

A Comparison of Free BDDs and Transformed BDDs

Ingo Wegener, Detlef Sieling, I. Wegener, 2001, Formal Methods Syst. Des..

The Theory of Zero-Suppressed BDDs and the Number of Knight's Tours

Ingo Wegener, Olaf Schröer, I. Wegener, 1998, Formal Methods Syst. Des..

Parity OBDDs Cannot be Handled Efficiently Enough

Ingo Wegener, Detlef Sieling, Martin Löbbing, 1998, Inf. Process. Lett..

Completeness and Non-Completeness Results with Respect to Read-Once Projections

Beate Bollig, Ingo Wegener, I. Wegener, 1998, Inf. Comput..

Complexity Theoretical Results on Partitioned (Nondeterministic) Binary Decision Diagrams

Beate Bollig, Ingo Wegener, I. Wegener, 1997, Theory of Computing Systems.

Communication Complexity and BDD Lower Bound Techniques

Ingo Wegener, I. Wegener, 2000 .

Worst case examples for operations on OBDDs

Ingo Wegener, I. Wegener, 2000, Inf. Process. Lett..

A Remark on Minimal Polynomials of Boolean Functions

Ingo Wegener, Bernd Voigt, I. Wegener, 1988, CSL.

Reduction of OBDDs in Linear Time

Ingo Wegener, Detlef Sieling, I. Wegener, 1993, Inf. Process. Lett..

Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Optimization with Randomized Search Heuristics : The ( A ) NFL Theorem , Realistic Scenarios , and Difficult Functions

I. Wegener, Stefan Droste, T. Jansen, 2001 .

The Complexity of Symmetric Boolean Functions

Ingo Wegener, I. Wegener, 1987, Computation Theory and Logic.

On P versus NP $ \cap $ co-NP for decision trees and read-once branching programs

Alexander A. Razborov, Ingo Wegener, Stasys Jukna, 1997, computational complexity.