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On solving the most strings with few bad columns problem: An ILP model and heuristics

机译:关于用最少的坏列问题解决最多的字符串:ILP模型和启发式

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The most strings with few bad columns problem is an NP-hard combinatorial optimization problem from the bioinformatics field. This paper presents the first integer linear programming model for this problem. Moreover, a simple greedy heuristic and a more sophisticated extension, namely a greedy-based pilot method, are proposed. Experiments show that, as expected, the greedy-based pilot method improves over the greedy strategy. For problem instances of small and medium size the best results were obtained by solving the integer linear programming model by CPLEX, while the greedy-based pilot methods scales much better to large problem instances.
机译:不良列最少的字符串最多的问题是来自生物信息学领域的NP-hard组合优化问题。本文提出了该问题的第一个整数线性规划模型。此外,提出了一种简单的贪婪启发式和更复杂的扩展,即基于贪婪的导频方法。实验表明,正如预期的那样,基于贪婪的试验方法比贪婪策略有所改进。对于中小型问题实例,通过CPLEX求解整数线性规划模型可获得最佳结果,而基于贪婪的试验方法可更好地解决大型问题实例。

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