多目标Pareto局部搜索
Many-Objective Pareto Local Search
摘要：
针对多目标组合优化问题，提出了一种新的Pareto局部搜索算法。Pareto局部搜索在双目标组合优化的情况下被证明是一个非常有效的工具，并且它被用于许多用于这类问题的最新算法中。另一方面，标准的Pareto局部搜索算法对于具有两个以上目标的问题变得非常低效。我们建立了一个有效的多目标Pareto局部搜索算法，使用三个新的机制：高效更新的大型Pareto档案与ND树数据结构，一个新的机制，用于选择有前途的解决方案的邻域探索，和部分探索的邻域。我们将所提出的算法应用到两个不同的问题，即旅行销售员问题和旅行销售员问题的利润高达5个目标的情况下，所提出的算法的高效率。
英文摘要：
We propose a new Pareto Local Search Algorithm for the many-objective combinatorial optimization. Pareto Local Search proved to be a very effective tool in the case of the bi-objective combinatorial optimization and it was used in a number of the state-of-the-art algorithms for problems of this kind. On the other hand, the standard Pareto Local Search algorithm becomes very inefficient for problems with more than two objectives. We build an effective Many-Objective Pareto Local Search algorithm using three new mechanisms: the efficient update of large Pareto archives with ND-Tree data structure, a new mechanism for the selection of the promising solutions for the neighborhood exploration, and a partial exploration of the neighborhoods. We apply the proposed algorithm to the instances of two different problems, i.e. the traveling salesperson problem and the traveling salesperson problem with profits with up to 5 objectives showing high effectiveness of the proposed algorithm.
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