MAX-SAT物流的演变
Evolved preambles for MAX-SAT heuristics
摘要：
MAX-SAT算法通常从随机初始真值分配到变量。我们考虑使用我们称之为的qualibles，这是序列的变量与相应的单变量分配行动，旨在用于确定一个更合适的初始真理分配一个给定的问题实例和一个给定的启发式。对于一些建立良好的MAX-SAT算法和基准实例，我们证明了可以通过遗传算法来进化算法，使得算法在很大一部分情况下优于基准。
英文摘要：
MAX-SAT heuristics normally operate from random initial truth assignments to the variables. We consider the use of what we call preambles, which are sequences of variables with corresponding single-variable assignment actions intended to be used to determine a more suitable initial truth assignment for a given problem instance and a given heuristic. For a number of well established MAX-SAT heuristics and benchmark instances, we demonstrate that preambles can be evolved by a genetic algorithm such that the heuristics are outperformed in a significant fraction of the cases.
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