
...presents two evolutionarycomputationbased models to produce hyper heuristics that solve twodimensional binpacking problems. the first model uses an xcstype learning...a large set of benchmark problems, per form better than the combinations of single heuristics. the testbed is composed of problems used in other similar studies...

the idea behind hyperheuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. to be worthwhile, such combination should...presents two evolutionarycomputationbased models to producehyperheuristics that solve twodimensional binpacking problems. the first model uses an xcstype learning...
Published in 2007.

...the idea behind hyperheuristics is to discover some combination of straightforward heuristics to solve a wide range of problems.
to be worthwhile, such a combination should outperform the single heuristics. this article presents a gabased method that
produces general hyperheuristics that solve twodimensional regular (rectangular) and irregular (convex polygonal...

...increases at least exponentially with the size of the problem [2]. to overcome this, the concept of
hyperheuristics could be applied. the idea...the resulting algorithm was applied to the twodimensional bin packing problem, and encouraging results
were obtained when solving classic instances taken from the literature. the performance of our approach is...

...such instance. such representation intends to include the most relevant features
related to the instance and the problem domain. the proper selection of these features...representation is proposed. we chose the irregular case of the twodimensional bin packing problem
(2d irregular bpp) and a ga...

...some com bination of straightforward heuristics to solve a wide range of problems. to be worthwhile, such combination should outperform the single heuristics. this paper presents a ga based method that produces general hyperheuristics that solve twodimensional cutting stock problems. the ga uses a variablelength...

...heuristics and learning classifier systems for solving 2d cutting stock problems. the idea behind hyperheuristics is to discover some combination of straightforward heuristics to solve a wide range of problems. to be worthwhile, such combination should outperform the single heuristics. in this paper, the hyperheuristic is formed using a xcs...

...recent years have witnessed the great success of hyperheuristics applying to numerous realworld applications. hyperheuristics raise the generality of search methodologies by manipulating...adhh by adaptively maintaining the llps for two hyperheuristic models. furthermore, aiming at tackling the search space expansion due to the llp adaptation, we apply a...

...such instance. such representation intends to include the most relevant features related to the instance and the problem domain. previous approaches for hyperheuristics have been relying in intuitive...proposed. as an experimental environment to test the methodology, we employed the irregular case of the twodimensional bin packing problem (2d irregular bpp) and a ga...

...get an upper bound of the model. a simulated annealing based hyperheuristic algorithm is proposed to solve several problem instances with different problem sizes and space ratios. the results show that the simulated annealing hyperheuristic significantly outperforms two conventional simulated annealing algorithms and...