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Comparative Experiments with GRASP and Constraint Programming for the Oil Well Drilling Problem

机译:对油井钻井问题的掌握和约束规划的比较实验

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Before promising locations become productive oil wells, it is often necessary to complete drilling activities at these locations. The scheduling of such activities must satisfy several conflicting constraints and attain a number of goals. Here, we describe a Greedy Randomized Adaptive Search Procedure (GRASP) for the scheduling of oil well drilling activities. The results are compared with those from a well accepted constraint programming implementation. Computational experience on real instances indicates that the GRASP implementation is competitive, outperforming the constraint programming implementation.
机译:在承诺地点成为生产油井之前,通常需要在这些地点完成钻井活动。这些活动的调度必须满足几个冲突的限制,并获得了许多目标。在这里,我们描述了一种贪婪的随机自适应搜索程序(掌握),用于调度油井钻井活动。将结果与来自良好的限制规划实施方式进行比较。实例上的计算体验表明掌握实现具有竞争力,优于约束编程实现。

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