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Tabu search : ウィキペディア英語版
Tabu search
Tabu search, created by Fred W. Glover in 1986〔
〕 and formalized in 1989,〔
〕〔
〕 is a metaheuristic search method employing local search methods used for mathematical optimization.
Local (neighborhood) searches take a potential solution to a problem and check its immediate neighbors (that is, solutions that are similar except for one or two 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 mimimum).
In addition, ''prohibitions'' (henceforth 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.〔 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.
==Background==

The word ''tabu'' comes from ''Tongan'', a language of Polynesia, used by the aborigines of Tonga to indicate things that cannot be touched because they are sacred.〔http://www.ise.ncsu.edu/fangroup/ie789.dir/IE789F_tabu.pdf〕
Tabu search (TS) is a metaheuristic algorithm that can be used for solving combinatorial optimization problems (problems where an optimal ordering and selection of options is desired).
Current applications of TS span the areas of resource planning, telecommunications, VLSI design, financial analysis, scheduling, space planning, energy distribution, molecular engineering, logistics, pattern classification, flexible manufacturing, waste management, mineral exploration, biomedical analysis, environmental conservation and scores of others. In recent years, journals in a wide variety of fields have published tutorial articles and computational studies documenting successes by tabu search in extending the frontier of problems that can be handled effectively — yielding solutions whose quality often significantly surpasses that obtained by methods previously applied. A comprehensive list of applications, including summary descriptions of gains achieved from practical implementations, can be found in Recent TS developments and applications can also be found in (Tabu Search Vignettes ).

抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)
ウィキペディアで「Tabu search」の詳細全文を読む



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