Combinatorial optimisation is a ubiquitous discipline whose
usefulness spans vast applications domains. The intrinsic
complexity of most combinatorial optimisation problems makes
classical methods unaffordable in many cases. To acquire practical
solutions to these problems requires the use of metaheuristic
approaches that trade completeness for pragmatic effectiveness.
Such approaches are able to provide optimal or quasi-optimal
solutions to a plethora of difficult combinatorial optimisation
problems.
The application of metaheuristics to combinatorial optimisation
is an active field in which new theoretical developments, new
algorithmic models, and new application areas are continuously
emerging. This volume presents recent advances in the area of
metaheuristic combinatorial optimisation, with a special focus on
evolutionary computation methods. Moreover, it addresses local
search methods and hybrid approaches. In this sense, the book
includes cutting-edge theoretical, methodological, algorithmic and
applied developments in the field, from respected experts and with
a sound perspective.
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