Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. (2003)
Presentation / Conference Contribution
Ross, P., Marin-Blazquez, J. G., Schulenburg, S., & Hart, E. (2003, July). Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics. Presented at Genetic and Evolutionary Computation Conference (GECCO) 2003

The idea underlying hyper-heuristics is to discover some
combination of familiar, straightforward heuristics that performs very well across a whole range of problems. To be worthwhile, such a combination should outperform all of the constituent heur... Read More about Learning a procedure that can solve hard bin-packing problems: a new GA-based approach to hyperheuristics..

Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. (2002)
Presentation / Conference Contribution
Ross, P., Schulenburg, S., Marin-Blazquez, J. G., & Hart, E. (2002, July). Hyper-heuristics: learning to combine simple heuristics in bin-packing problems. Presented at Genetic and Evolutionary Computation Conference (GECCO)

Evolutionary algorithms (EAs) often appear to be a ‘black box’, neither offering worst-case bounds nor any guarantee of optimality when used to solve individual problems. They can also take much longer than non-evolutionary methods. We
try to addres... Read More about Hyper-heuristics: learning to combine simple heuristics in bin-packing problems..