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Setting Limits on Supersymmetry Using Simplified Models
Published on: November 15, 2013
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通过消散过度满足的约束来推进随机的3-SAT解决者.
Joachim Schwardt1,2, Jan Carl Budich1,2
1Condensed Matter Division, Max Planck Institute for the Physics of Complex Systems, Dresden 01187, Germany.
概括
我们开发了DOCSAT,这是3SAT问题的新启发式,通过避免局部最小值,在极其困难的实例上显著优于现有的解决者. 在可满足性问题解决方面的这一进步为其他优化挑战提供了潜力.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 计算复杂性 计算复杂性
背景情况:
- 3-SAT问题是一个基本的非确定性多项式时间 (NP) -完整问题.
- 像WalkSAT这样的现有随机局部搜索启发式可以被局部最小值困住.
- 在3-SAT中,局部最小值通常具有大量过度满足的约束.
研究的目的:
- 介绍并对3-SAT.的新型随机局部搜索启发式进行基准测试.
- 解决现有解决方案被局部最小值所限制的局限性.
- 在非常困难的3-SAT实例上提高性能.
主要方法:
- 开发了一个新的算法,分散过度满足的约束SAT (DOCSAT).
- DOCSAT的重点是减少过度满足的约束,以逃避局部最小值.
- 与WalkSAT和Kissat等既有解决方案相比,对随机生成的难以满足的3SAT实例进行了基准DOCSAT,最高可达N=15,000.
主要成果:
- 在极其困难的3SAT实例中,DOCSAT显著优于WalkSAT和其他解决方案.
- 在最艰难的实例中,即使与竞争对手的平均性能相比,DOCSAT也表现出卓越的性能.
- 该算法通过消除过度满足的约束来有效地避免局部最小值.
结论:
- 在解决困难的3SAT实例方面,DOCSAT代表了显著的改进.
- DOCSAT的核心机制是利用统计结构来逃避局部最小值.
- 该方法提供了对其他复杂的组合优化问题的概括的潜力.
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