On the Fractal Nature of Local Optima Networks

被引:6
|
作者
Thomson, Sarah L. [1 ]
Verel, Sebastien [2 ]
Ochoa, Gabriela [1 ]
Veerapen, Nadarajen [1 ]
McMenemy, Paul [1 ]
机构
[1] Univ Stirling, Comp Sci & Math, Stirling, Scotland
[2] Univ Littoral Cote dOpale, LISIC, EA 4491, Calais, France
基金
英国工程与自然科学研究理事会;
关键词
Combinatorial fitness landscapes; Local optima networks; Fractal analysis; NK Landscapes; FITNESS LANDSCAPES;
D O I
10.1007/978-3-319-77449-7_2
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
A Local Optima Network represents fitness landscape connectivity within the space of local optima as a mathematical graph. In certain other complex networks or graphs there have been recent observations made about inherent self-similarity. An object is said to be self-similar if it shows the same patterns when measured at different scales; another word used to convey self-similarity is fractal. The fractal dimension of an object captures how the detail observed changes with the scale at which it is measured, with a high fractal dimension being associated with complexity. We conduct a detailed study on the fractal nature of the local optima networks of a benchmark combinatorial optimisation problem (NK Landscapes). The results draw connections between fractal characteristics and performance by three prominent metaheuristics: Iterated Local Search, Simulated Annealing, and Tabu Search.
引用
收藏
页码:18 / 33
页数:16
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