One way to design a local search algorithm that is effective on many types of instances is allowing this algorithm to switch among heuristics. In this paper, we refer to the way in...
Currently, among the fastest approaches to AI task planning we find many forward-chaining heuristic planners, as FF. Most of their good performance comes from the use of domain-i...
In view of the strong increasing number of phylogeny problems and instances, the assessment of the respective optimization algorithms has become harder too. This paper contributes ...
Many heuristics, such as simulated annealing, genetic algorithms, greedy randomized adaptive search procedures are stochastic. In this paper, we propose a deterministic heuristic a...
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One way of overcoming this is by combining admissible heuristics (e.g. b...