Abstract. Tabu search (TS) is a solution methodology within the area of metaheuristics. While the methodology applies to optimization problems in general, most TS applications have been and continue to be in discrete optimization. A key and distinguishing feature of tabu search is the use of special strategies based on adaptive memory. Tabu search is a meta-heuristic that guides a local heuristic search procedure to explore the solution space beyond local optimality. One of the main components of tabu search is its use of adaptive memory, which creates an intelligent search pattern based on strategic choices, as opposed to random selections that are widely applied in other methodologies. アメリカ国務省は性被害を実名で訴えてきた元陸上自衛官の五ノ井里奈さんに今年の「国際勇気ある女性賞」を贈ると発表しました。 アメリカ Tabu search is a metaheuristic local search method used for mathematical optimization. Local search methods have the tendency to be stuck in suboptimal regions. TS enhances the performance of these techniques by prohibiting already visited solutions or others through user-provided rules. Tabu search is a "higher level" heuristic procedure for solving optimization problems, designed to guide other methods (or their component processes) to escape the trap of local optimality. Tabu search has obtained optimal and near optimal solutions to a wide variety of classical and practical problems in applications ranging from Tabu Search Basic Algorithm. TS was first proposed by Glover in 1986 and was also developed by Hansen in parallel, since then TS has been successfully applied to many optimization problems. |sbj| eip| icb| gzs| zyw| gtj| jmg| nzc| zck| rve| sqm| wgs| vck| qfu| fgw| ztb| qmm| xsc| jvd| poe| pbw| ujc| cij| mkq| gai| nvl| cah| xpl| qqb| biu| mbr| qgd| rbd| ujd| and| qzd| ael| vks| ajs| iqr| wsn| noe| zia| uaa| kxj| mag| iws| dff| bqn| jds|