Tabu search (TS) is a metaheuristic search method employing local search methods used for mathematical optimization. It was created by Fred W. Glover in 1986[1] and formalized in 1989.[2][3]
Local (neighborhood) searches take a potential solution to a problem and check its immediate neighbors (that is, solutions that are similar except for very few minor details) in the hope of finding an improved solution. Local search methods have a tendency to become stuck in suboptimal regions or on plateaus where many solutions are equally fit.
Tabu search enhances the performance of local search by relaxing its basic rule. First, at each step worsening moves can be accepted if no improving move is available (like when the search is stuck at a strict local minimum). In addition, prohibitions (hence the term tabu) are introduced to discourage the search from coming back to previously-visited solutions.
The implementation of tabu search uses memory structures that describe the visited solutions or user-provided sets of rules.[2] If a potential solution has been previously visited within a certain short-term period or if it has violated a rule, it is marked as "tabu" (forbidden) so that the algorithm does not consider that possibility repeatedly.
^Fred Glover (1986). "Future Paths for Integer Programming and Links to Artificial Intelligence". Computers and Operations Research. 13 (5): 533–549. doi:10.1016/0305-0548(86)90048-1.
^ abFred Glover (1989). "Tabu Search – Part 1". ORSA Journal on Computing. 1 (2): 190–206. doi:10.1287/ijoc.1.3.190.
^Fred Glover (1990). "Tabu Search – Part 2". ORSA Journal on Computing. 2 (1): 4–32. doi:10.1287/ijoc.2.1.4.
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