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Analysis of a simple evolutionary algorithm for the multiobjective shortest path problem

机译:多目标最短路径问题的简单进化算法分析

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摘要

We present a natural fitness function f for the multiobjective shortest path problem, which is a fundamental multiobjective combinatorial optimization problem known to be NP-hard. Thereafter, we conduct a rigorous runtime analysis of a simple evolutionary algorithm (EA) optimizing f. Interestingly, this simple general algorithm is a fully polynomial-time randomized approximation scheme (FPRAS) for the problem under consideration, which exemplifies how EAs are able to find good approximate solutions for hard problems.
机译:我们提出了针对多目标最短路径问题的自然适应度函数f,这是一个基本的多目标组合优化问题,已知为NP-难问题。此后,我们对优化f的简单进化算法(EA)进行了严格的运行时分析。有趣的是,这种简单的通用算法是针对所考虑问题的完全多项式时间随机逼近方案(FPRAS),它例示了EA如何能够为困难问题找到良好的近似解。

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