In this paper, an algorithm, called ACS-OPHS, is proposed to tackle the Orienteering Problem with Hotel Selection (OPHS). This algorithm is strongly based on the Ant Colony System (ACS); however, it differs from the ACS in the way the paths are constructed, in tuning a parameter of the transition rule and in the pheromone trails updating rules. The ACS-OPHS uses a bi-directional search strategy and employs a novel and fast approach to identify all feasible intermediate hotels in an offline manner. Moreover, in the ACS-OPHS, the relative importance of exploitation versus exploration is determined according to the progress of the algorithm in approaching to the global optima. The ACS-OPHS is a simple and well-performing approach to solve the OPHS. Concerning the standard benchmark instances, it outperforms the state-of-the-art algorithms in several instances and produces competitive solutions in reasonable time. This algorithm also improves the best known results of four instances with unknown optimal solutions.

在本文中，提出了一种称为ACS-OPHS的算法，以解决带有酒店选择的定向越野问题（OPHS）。该算法强烈基于蚁群系统（ACS）。但是，它与ACS的区别在于路径的构造方式，调整过渡规则的参数以及信息素路径更新规则。ACS-OPHS使用双向搜索策略，并采用新颖，快速的方法以离线方式识别所有可行的中间酒店。此外，在ACS-OPHS中，根据算法在接近全局最优值方面的进展来确定开发与探索的相对重要性。ACS-OPHS是解决OPHS的简单且性能良好的方法。关于标准基准测试实例，在某些情况下，它的性能优于最先进的算法，并在合理的时间内提供了具有竞争力的解决方案。该算法还利用未知的最佳解决方案提高了四个实例的最佳已知结果。