• Title/Summary/Keyword: 시뮬레이티드 어넬링

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Structural Optimization By Adaptive Simulated Annealing's Cooling Schedule Change (어댑티브 시뮬레이티드 어넬링의 냉각스케줄에 따른 구조최적설계)

  • Jung, Suk-Hoon;Park, Jung-Sun
    • Proceedings of the KSME Conference
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    • 2003.11a
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    • pp.1436-1441
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    • 2003
  • Recently, simulated annealing algorithms have widely been applied to many structural optimization problems. In this paper, simulated annealing, boltzmann annealing, fast annealing and adaptive simulated annealing are applied to optimization of truss structures for improvement quality of objective function and number of function evaluation. These algorithms are classified by cooling schedule. The authors have changed parameters of ASA's cooling schedule and the influence of cooling schedule parameters on structural optimization obtained is discussed. In addition, cooling schedule of BA and ASA mixed is applied to 10 bar-truss structure.

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Optimum Design for Sizing and Shape of Truss Structures Using Harmony Search and Simulated Annealing (하모니 서치와 시뮬레이티드 어넬링을 사용한 트러스의 단면 및 형상 최적설계)

  • Kim, Bong Ik
    • Journal of Korean Society of Steel Construction
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    • v.27 no.2
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    • pp.131-142
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    • 2015
  • In this paper, we present an optimization of truss structures subjected to stress, buckling, and natural frequency constraints. The main objective of the present study is to propose an efficient HA-SA algorithm for solving the truss optimization subject to multiple constraints. The procedure of hybrid HA-SA is a search method which a design values in harmony memory of harmony search are used as an initial value designs in simulated annealing search method. The efficient optimization of HA-SA is illustrated through several optimization examples. The examples of truss structures are used 10-Bar truss, 52-Bar truss (Dome), and 72-Bar truss for natural frequency constraints, and used 18-Bar truss and 47-Bar (Tower) truss for stress and buckling constraints. The optimum results are compared to those of different techniques. The numerical results are demonstrated the advantages of the HA-SA algorithm in truss optimization with multiple constraints.

A Effective Ant Colony Algorithm applied to the Graph Coloring Problem (그래프 착색 문제에 적용된 효과적인 Ant Colony Algorithm에 관한 연구)

  • Ahn, Sang-Huck;Lee, Seung-Gwan;Chung, Tae-Choong
    • The KIPS Transactions:PartB
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    • v.11B no.2
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    • pp.221-226
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    • 2004
  • Ant Colony System(ACS) Algorithm is new meta-heuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. Recently, various methods and solutions are proposed to solve optimal solution of graph coloring problem that assign to color for adjacency node($v_i, v_j$) that they has not same color. In this paper introducing ANTCOL Algorithm that is method to solve solution by Ant Colony System algorithm that is not method that it is known well as solution of existent graph coloring problem. After introducing ACS algorithm and Assignment Type Problem, show the wav how to apply ACS to solve ATP And compare graph coloring result and execution time when use existent generating functions(ANT_Random, ANT_LF, ANT_SL, ANT_DSATUR, ANT_RLF method) with ANT_XRLF method that use XRLF that apply Randomize to RLF to solve ANTCOL. Also compare graph coloring result and execution time when use method to add re-search to ANT_XRLF(ANT_XRLF_R) with existent generating functions.