Subheuristic search and scalability in a hyperheuristic

Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics are used as primitives for producing specialised metaheuristics (MH). Here, we show that the GP-HH works well with simple generic languages over subheuristic primitives, dealing with increases of problem size and reduction of resources. The system produces effective and efficient MHs that deliver best results known in a chosen test domain. We also demonstrate that user-given, modest domain information allows the HH to produce an improvement over a previous best result from the literature. Categories and Subject Descriptors Artificial Intelligence [Problem Solving, Control Methods, and Search]: Heuristic methods General Terms Algorithms Experimentation Languages

• Type: Conference
• Year: 2008
• Where: GECCO
• Authors: Robert E. Keller, Riccardo Poli
• Keywords: Chosen Test Domain, Domain-specific Local Heuristics, GECCO 2008, Optimization, Simple Generic Languages