双目标旅行贼问题的专门进化方法

Maciej Laszczyk, P. Myszkowski
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引用次数: 5

摘要

近年来,现实世界的问题通常由两个相互依赖的子问题组成。通常,单独解决这些问题并不能解决整个问题。本文考虑了一个旅行小偷问题,它结合了旅行推销员问题和背包问题。研究了一种非支配排序遗传算法II (NSGA-II),并对其进行了改进——非支配比赛遗传算法(NTGA)。每种方法都在两种配置中进行了研究。一种是通用表示法和遗传算子。另一个,专门针对给定的问题,以显示遗传算子的专业化如何导致更好的结果。验证了NTGA引入的修改的影响。使用一组质量度量来验证所得到的PF近似的收敛性、多样性以及该方法的效率。进行了一组实验。结果表明,当使用泛型表示时,这两种方法的工作原理几乎相同。然而,NTGA在专业结果上优于经典NSGA-II。
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A Specialized Evolutionary Approach to the bi-objective Travelling Thief Problem
In the recent years, it has been shown that real world-problems are often comprised of two, interdependent subproblems. Often, solving them independently does not lead to the solution to the entire problem. In this article, a Travelling Thief Problem is considered, which combines a Travelling Salesman Problem with a Knapsack Problem. A Non-Dominated Sorting Genetic Algorithm II (NSGA-II) is investigated, along with its recent modification - a Non-Dominated Tournament Genetic Algorithm (NTGA). Each method is investigated in two configurations. One, with generic representation, and genetic operators. The other, specialized to the given problem, to show how the specialization of genetic operators leads to better results. The impact of the modifications introduced by NTGA is verified. A set of Quality Measures is used to verify the convergence, and diversity of the resulting PF approximations, and efficiency of the method. A set of experiments is carried out. It is shown that both methods work almost the same when generic representation is used. However, NTGA outperforms classical NSGA-II in the specialized results.
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