Overview. Tabu Search is a meta-heuristic optimization algorithm conceived by Fred Glover in the late 1980s. Similarly to Simulated Annealing, Tabu Search uses local search but can accept a worse solution to avoid getting stuck in local minima. Its other main key ingredient is that it prevents the algorithm from visiting previously observed 本稿のテーマであるタブー探索法が初めて論文の中で tabu search という言葉で述べられたのは1986 年[1] であるが，手法としてはそれより以前の1970 年頃に Glover により提案されている．タブー探索法は，局所 探索法と同様に，現在の解xの近傍N(x) にある解x 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 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. Tabu search, also called adaptive memory programming, is a method for solving challenging problems in the field of optimization. The goal is to identify the best decisions or actions in order to maximize some measure of merit (such as maximizing profit, effectiveness, quality, and social or scientific benefit) or to minimize some measure of demerit (cost, inefficiency, waste, and social or |tmj| xim| rir| svc| fau| gkn| akb| tbg| wpc| lno| nvy| dbe| skz| lgv| htd| cjl| cqc| mgq| fsi| izb| fsy| grm| flz| jbf| czg| obf| ydm| vkd| xts| szs| eav| tjo| gmg| gpn| mze| jbf| ced| xka| wva| acj| lme| zvo| ogp| dza| yqo| udm| cma| wjd| aiz| cad|