  This paper describes a novel refinement to a Tabu search algorithm that has
been implemented in an attempt to improve the robustness of the search when
applied to particularly complex problems. In this approach, two Tabu searches
are carried out in parallel. Each search thread is characterised by it's own
short term memory which forces that point out of local optima. However, the two
search threads share an intermediate term memory so allowing a degree of
information to be passed between them. Results are presented for both
unconstrained and constrained numerical functions as well as a problem in the
field of hydraulic circuit optimization. Simulation of hydraulic circuit
performance is achieved by linking the optimization algorithm to the commercial
simulation package Bathfp.
