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On the analysis of the (1+1) evolutionary algorithm
TLDR
A step towards a theory on Evolutionary Algorithms, in particular, the so-called (1+1) evolutionary Algorithm, is performed and linear functions are proved to be optimized in expected time O(nlnn) but only mutation rates of size (1/n) can ensure this behavior. Expand
The complexity of Boolean functions
TLDR
This chapter discusses Circuits and other Non-Uniform Computation Methods vs. Turing Machines and other Uniform Computation Models, and the Design of Efficient Circuits for Some Fundamental Functions. Expand
Improving the Variable Ordering of OBDDs Is NP-Complete
Ordered binary decision diagrams are a useful representation of Boolean functions, if a good variable ordering is known. Variable orderings are computed by heuristic algorithms and then improved withExpand
Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization
TLDR
Lower bounds on the black-box complexity of problems are derived without complexity theoretical assumptions and are compared with upper bounds in this scenario. Expand
On the Choice of the Offspring Population Size in Evolutionary Algorithms
TLDR
Using a simplified but still realistic evolutionary algorithm, a thorough analysis of the effects of the offspring population size is presented and a simple way to dynamically adapt this parameter when necessary is suggested. Expand
The analysis of evolutionary algorithms on sorting and shortest paths problems
TLDR
This work analyzes simple EAs on well-known problems, namely sorting and shortest paths, and finds that sorting is the maximization of “sortedness” which is measured by one of several well- known measures of presortedness. Expand
Branching Programs and Binary Deci-sion Diagrams-Theory and Applications
Preface Introduction 1. Introduction 2. BPs and Decision Trees (DTs) 3. Ordered Binary Decision Diagrams (OBDDs) 4. The OBDD Size of Selected Functions 5. The Variable-Ordering Problem 6. Free BDDsExpand
Methods for the Analysis of Evolutionary Algorithms on Pseudo-Boolean Functions
TLDR
Important analytical tools are presented, discussed, and applied to well-chosen example functions in the analysis of different variants of evolutionary algorithms on selected functions. Expand
Evolutionary algorithms - how to cope with plateaus of constant fitness and when to reject strings of the same fitness
A pair of skis are provided on their upper surfaces with respective mounting plates each carrying a treadle depressible by the boot of the user, the treadle overlying the bight of a yoke biased intoExpand
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