Performance analysis of randomised search heuristics is a rapidly growing and developing field. We contribute to its further development by introducing a novel analytical perspective that we call unlimited budget analysis. It has its roots in the very recently introduced approximation error analysis and bears some similarity to fixed budget analysis. The focus is on the progress an optimisation heuristic makes towards a set goal, not on the time it takes to reach this goal, setting it far apart from runtime analysis. We present the framework, apply it to simple mutation-based algorithms, covering both, local and global search. We provide analytical results for a number of simple example functions for unlimited budget analysis and compare th...
A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to...
International audienceBenchmarking aims to investigate the performance of one or several algorithms ...
Evolutionary algorithms (EAs) are bio-inspired general purpose optimisation methods which are applic...
Performance analysis of randomised search heuristics is a rapidly growing and developing field. We c...
When for a difficult real-world optimisation problem no good problem-specific algorithm is available...
Randomised search heuristics are used in practice to solve difficult problems where no good problem-...
Randomised search heuristics are used in practice to solve difficult problems where no good problem-...
Dynamic optimisation is an area of application where randomised search heuristics like evolutionary ...
The fitness-level technique is a simple and old way to derive upper bounds for the expected runtime ...
Different studies have theoretically analyzed the performance of artificial immune systems in the co...
Runtime analyses of randomized search heuristics for combinatorial optimization problems often depen...
When stochastic search heuristics are used for optimisation they are often stopped after some time h...
At last year’s GECCO a novel perspective for theoretical performance analysis of evolutionary algori...
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. ...
Local search is a powerful technique on many combinatorial optimisation problems. However, the effec...
A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to...
International audienceBenchmarking aims to investigate the performance of one or several algorithms ...
Evolutionary algorithms (EAs) are bio-inspired general purpose optimisation methods which are applic...
Performance analysis of randomised search heuristics is a rapidly growing and developing field. We c...
When for a difficult real-world optimisation problem no good problem-specific algorithm is available...
Randomised search heuristics are used in practice to solve difficult problems where no good problem-...
Randomised search heuristics are used in practice to solve difficult problems where no good problem-...
Dynamic optimisation is an area of application where randomised search heuristics like evolutionary ...
The fitness-level technique is a simple and old way to derive upper bounds for the expected runtime ...
Different studies have theoretically analyzed the performance of artificial immune systems in the co...
Runtime analyses of randomized search heuristics for combinatorial optimization problems often depen...
When stochastic search heuristics are used for optimisation they are often stopped after some time h...
At last year’s GECCO a novel perspective for theoretical performance analysis of evolutionary algori...
Randomized search heuristics are frequently applied to NP-hard combinatorial optimization problems. ...
Local search is a powerful technique on many combinatorial optimisation problems. However, the effec...
A hyper-heuristic is a search method or learning mechanism for selecting or generating heuristics to...
International audienceBenchmarking aims to investigate the performance of one or several algorithms ...
Evolutionary algorithms (EAs) are bio-inspired general purpose optimisation methods which are applic...