Optimal Determination of Simulated Annealing Parameters using TOPSIS

被引:0
|
作者
Fotuhi, Fateme [1 ]
机构
[1] Univ S Carolina, Dept Civil & Environm Engn, Columbia, SC 29208 USA
关键词
Multi-Criteria decision making; simulated annealing parameters; TOPSIS;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Efficiency of a Meta heuristic approach depends effectively on the right and suitable choice of its parameters. Meta heuristics are used to develop qualified feasible solutions. They are used while common commercial soft wares can't find exact solutions in a logical computational time. They are random approaches as different target values might be gained during consecutive repetitions of the algorithm. An appropriate set of parameters avoids the problem to produce sporadic target values and controls the time to get coherent solutions. TOPSIS (Technique for Order Preference by Similarity to Ideal) is one of Multi Attribute Decision Making (MADM) approaches used in defining the best alternative in a complicated decision making problem which is used here to set the parameters of a simulated annealing algorithm in their suitable levels. This helps the algorithm to find good solutions besides controlling the time spent to get these values.
引用
收藏
页码:46 / 50
页数:5
相关论文
共 50 条
  • [1] DETERMINATION OF MULTILAYER SOIL PARAMETERS USING SIMULATED ANNEALING ALGORITHM
    Nikjoo, Roya S.
    Sadeghi, S. H. H.
    Moini, R.
    Sheshyekani, Keyhan
    2010 30TH INTERNATIONAL CONFERENCE ON LIGHTNING PROTECTION (ICLP), 2010,
  • [2] Determination of the parameters of a Skyrme type effective interaction using the simulated annealing approach
    Agrawal, BK
    Shlomo, S
    Au, VK
    PHYSICAL REVIEW C, 2005, 72 (01):
  • [3] Optimal vaccination schedules using simulated annealing
    Pennisi, Marzio
    Catanuto, Roberto
    Pappalardo, Francesco
    Motta, Santo
    BIOINFORMATICS, 2008, 24 (15) : 1740 - 1742
  • [4] OPTIMAL NETWORK TEARING USING SIMULATED ANNEALING
    IRVING, MR
    STERLING, MJH
    IEE PROCEEDINGS-C GENERATION TRANSMISSION AND DISTRIBUTION, 1990, 137 (01) : 69 - 72
  • [5] Optimal blank nesting using simulated annealing
    Jain, P.
    Fenyes, P.
    Richter, R.
    Journal of Mechanical Design - Transactions of the ASME, 1992, 114 (01): : 160 - 165
  • [6] Area Optimal Polygonization Using Simulated Annealing
    Goren N.
    Fogel E.
    Halperin D.
    ACM Journal of Experimental Algorithmics, 2022, 27 (02):
  • [7] COMPUTING OPTIMAL TRIANGULATIONS USING SIMULATED ANNEALING
    SCHUMAKER, LL
    COMPUTER AIDED GEOMETRIC DESIGN, 1993, 10 (3-4) : 329 - 345
  • [8] OPTIMAL BLANK NESTING USING SIMULATED ANNEALING
    JAIN, P
    FENYES, P
    RICHTER, R
    JOURNAL OF MECHANICAL DESIGN, 1992, 114 (01) : 160 - 165
  • [9] Optimal parameters selection for simulated annealing with limited computational effort
    Zhang, L
    Wang, L
    PROCEEDINGS OF 2003 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS & SIGNAL PROCESSING, PROCEEDINGS, VOLS 1 AND 2, 2003, : 412 - 415
  • [10] Hypocentral determination using simulated annealing method
    Gao, X
    Wang, WM
    Yao, ZX
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2002, 45 (04): : 525 - 532