This article explores the meta-heuristic approach called tabu search,
which is dramatically changing our ability to solve a host of
problems in applied science, business and engineering. Tabu search
has important links to evolutionary and “genetic” methods,
often overlooked, through its intimate connection with scatter search
and path relinking — evolutionary procedures that have recently
attracted attention for their ability to facilitate the solution of
complex problems. The adaptive memory designs of tabu search have
also provided useful alternatives and supplements to the types of
memory embodied in neural networks, allowing enhancements of neural
network processes in practical settings.
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