Paper Info
Title
Collaboration Between Hyperheuristics to Solve Strip-Packing Problems
Abstract
In this paper we introduce a collaboration framework for hyperheuristics to solve hard strip packing problems. We have designed a genetic based hyperheuristic to cooperate with a hill-climbing based hyperheuristic. Both of them use the most recently proposed low-level heuristics in the literature. REVAC, which has recently been proposed for tuning [18], has been used to find the best operators parameter values. The results obtained are very encouraging and have improved the results from both the single heuristics and the single hyperheuristics' tests. Thus, we conclude that the collaboration among hyperheuristics is a good way to solve hard strip packing problems.
Year
DOI
Venue
2007
10.1007/978-3-540-72950-1_69
IFSA (1)
Keywords
Field
DocType
parameter value,best operator,low-level heuristics,strip-packing problems,collaboration framework,single hyperheuristics,single heuristics,hard strip packing problem,hill climbing,metaheuristics,heuristic search
Mathematical optimization,Heuristic,Computer science,Heuristics,Operator (computer programming),Parameter control,Strip packing,Metaheuristic
Conference
Volume
ISSN
Citations 
4529
0302-9743
7
PageRank 
References 
Authors
0.50
14
2
Name
Order
Citations
PageRank
Pablo Garrido128212.57
María Cristina Riff220023.91