Smart Topology Optimization Using Adaptive Neighborhood Simulated Annealing

Simulated Annealing with Advanced Adaptive Neighborhood

It was Kirkpatrick et al. who first proposed simulated annealing, SA, as a method for solving combinatorial optimization problems[1]. It is reported that SA is very useful for several types of combinatorial optimization problems[2]. The advantages and the disadvantages of SA are well summarized in [3]. The most remarkable disadvantages are that it needs a lot of time to find the optimum solutio...

Temperature Parallel Simulated Annealing with Adaptive Neighborhood

In this paper, a Temperature Parallel Simulated Annealing with Adaptive Neighborhood (TPSA/AN) for continuous optimization problems is introduced. TPSA/AN is based on the temperature parallel simulated annealing (TPSA), which is suitable for parallel processing, and the SA that Corana developed for continuous optimization problems. The moves in TPSA/AN are adjusted to have equal acceptance rate...

Neighborhood Parallel Simulated Annealing

Parallel simulated annealing with adaptive neighborhood determined by GA

Abstract – Simulated annealing (SA) is an effective general heuristic method for solving many optimization problems. This paper deals with the two problems in SA. One is the long computational time of the numerical annealings, and the solution to it is the parallel processing of SA. The other one is the determination of the appropriate neighborhood range in SA, and the solution to it is the int...

Temperature Parallel Simulated Annealing with Advanced Adaptive Neighborhood

多峰性の連続最適化問題にシミュレーテッドアニーリング (SA)を適用する場合,著者らがすでに 提案している最適な受理確率を目標とする適応的近傍を持つ SA(SA/AAN)が有効である.本論文 では,並列計算機を用いて組み合わせ最適化問題を解く場合に有効な並列アルゴリズムの 1つである 温度並列シミュレーテッドアニーリング (TPSA)に SA/AAN を組み込んだ手法を提案する.提案 手法は各プロセス (プロセッサ)が担当する各温度において,適応的な近傍拡大率を持つ近傍を用い て探索するため,関数のランドスケープに適応した探索が行うことが可能である.一方,TPSAは温 度スケジュールが不要であるという特徴がある.そのため本論文で提案する手法は,温度,近傍とも に関数のランドスケープに合わせ自律的な調節を行うことができるという優れた特徴を持つことがわ かった.3 つの代表的なテスト関数...