The Guided Local Search method has been successfully applied to a numb
er of hard combinatorial optimisation problems from the well-known TSP
and QAP to real-world problems such as frequency assignment and workf
orce scheduling. In this paper it is demonstrated that the potential a
pplications of GLS are Mot limited to optimisation problems of discret
e nature but also to difficult continuous optimisation problems. Conti
nuous optimisation problems arise in many engineering disciplines (suc
h as electrical and mechanical engineering) in the context of analysis
, design or simulation tasks. The problem examined gives an illustrati
ve ex-ample of the behaviour of GLS, providing insights on the mechani
sms of the algorithm.