Dempster, P. and Drake, J.H. (2015) Two frameworks for cross-domain heuristic and parameter selection using harmony search. In: Harmony Search Algorithm : Proceedings of the 2nd International Conference on Harmony Search Algorithm (ICHSA2015). Advances in Intelligent Systems and Computing . Springer, pp. 83-94. ISBN 9783662479254
Full text not available from this repository.Abstract
Harmony Search is a metaheuristic technique for optimizing problems involving sets of continuous or discrete variables, inspired by musicians searching for harmony between instruments in a performance. Here we investigate two frameworks, using Harmony Search to select a mixture of continuous and discrete variables forming the components of a Memetic Algorithm for cross-domain heuristic search. The first is a single-point based framework which maintains a single solution, updating the harmony memory based on performance from a fixed starting position. The second is a population-based method which co-evolves a set of solutions to a problem alongside a set of harmony vectors. This work examines the behaviour of each framework over thirty problem instances taken from six different, real-world problem domains. The results suggest that population co-evolution performs better in a time-constrained scenario, however both approaches are ultimately constrained by the underlying metaphors.