Tuning a Simulated Annealing metaheuristic for cross-domain search

Jackson, Warren G. and Özcan, Ender and John, Robert (2017) Tuning a Simulated Annealing metaheuristic for cross-domain search. In: IEEE Congress on Evolutionary Computation 2017, 5-9 June 2017, Donostia-San Sebastian, Spain.

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Abstract

Simulated Annealing is a well known local search metaheuristic used for solving computationally hard optimization problems. Cross-domain search poses a higher level issue where a single solution method is used with minor, preferably no modification for solving characteristically different optimisation problems. The performance of a metaheuristic is often dependant on its initial parameter settings, hence detecting the best configuration, i.e. parameter tuning is crucial, which becomes a further challenge for cross-domain search. In this paper, we investigate the cross-domain search performance of Simulated Annealing via tuning for solving six problems, ranging from personnel scheduling to vehicle routing under a stochastic local search framework. The empirical results show that Simulated Annealing is extremely sensitive to the initial parameter settings leading to sub-standard performance when used as a single solution method for cross-domain search. Moreover, we demonstrate that cross-domain parameter tuning is inferior to domain-level tuning highlighting the requirements for adaptive parameter configurations when dealing with cross-domain search.

Item Type: Conference or Workshop Item (Paper)
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Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
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Depositing User: Eprints, Support
Date Deposited: 21 Mar 2017 11:29
Last Modified: 13 Oct 2017 01:25
URI: http://eprints.nottingham.ac.uk/id/eprint/41418

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