This workshop will explore hybrid algorithms for complex optimisation problems. These will be based on the integration of different approaches, viz. These approaches have sometimes been perceived as competitors, but more recently they have come to be seen as complementary. The need for such algorithms in solving optimisation problems arises from the fact that different techniques are suited to solving different aspects of the problem. Among the key techniques are constraint propagation, Lagrangean relaxation, linear programming, randomised search and local optimisation.
Constraint propagation is ideal for customising an algorithm with domain-dependent constraints.
Lagrangean relaxation is the technique of choice for obtaining lower bounds in a branch and bound approach. Linear programming is the only technique that can solve to optimiality large linear problems. Randomised search is necessary for problems that are too large for branch and bound. Local optimisation is the preferred technique for problems that have a specific neighbourhood structure, such as routing problems. Many optimisation problems are hybrid, embracing several different requirements.