基于SMT的机组排班问题优化求解

机组排班是航空公司运营计划非常重要的一个环节,合理的机组排班可以为航空公司省下一大笔机组成本支出,从而增加航空公司的收益.由于机组排班过程涉及大量的复杂约束,属于NP难问题,因此优化求解困难.本文提出了一种基于可满足性模理论(Satisfiability Modulo Theories,SMT)的航空公司机组排班问题的优化求解方法,将机组排班过程中的各种约束转化为一阶逻辑公式,设立求解目标为最小化成本和最大化机组利用率,将问题转化为求在给定逻辑公式可满足情况下的最优解,并利用SMT求解器Z3进行求解.实验表明,本文的算法能有效的求解一定规模航班计划的机组排班问题,给航空公司带来一定的收益.     

求解极小SMT不可满足子式的宽度优先搜索算法

极小不可满足子式能够为可满足性模理论(SMT)公式的不可满足的原因提供精确的解释,帮助自动化工具迅速定位错误.针对极小SMT不可满足子式的求解问题,提出了SMT公式搜索树及其3类结点的概念,并给出了不可满足子式、极小不可满足子式与3类结点之间的映射关系.基于这种映射关系,采用宽度优先的搜索策略提出了宽度优先搜索的极小SMT不可满足子式求解算法.基于业界公认的SMT Competition 2007测试集进行实验的结果表明,该算法能够有效地求解极小不可满足子式.     

可满足性模理论综述

可满足性模理论(SMT)是指判定一阶逻辑公式在特定背景理论下的可满足性问题。基于一阶逻辑的SMT相比SAT描述能力更强、抽象能力更高,能处理更加复杂的问题。SMT求解器在各个领域都有应用,已经成为重要的形式化验证引擎。目前,SMT已被广泛应用在人工智能、硬件RTL验证、自动化推理和软件工程等领域。根据近些年SMT的发展,首先阐述SMT基本知识和常见的背景理论;然后分析总结Eager方法、Lazy方法和DPLL(T)方法的实现流程,并进一步介绍主流求解器Z3、CVC5和MathSAT5的实现过程;接着介绍SMT的扩展问题#SMT、SMT应用在深度神经网络的SMTlayer方法和量子SMT求解器;最后对SMT的发展进行展望,并讨论其面临的挑战。     

SMT求解器理论组合技术研究

可满足模理论(SMT)求解器是计算机科学中用来判定一阶逻辑公式可满足性的程序,是许多形式化方法的验证引擎.理论求解器实现了SMT基于不同理论背景的求解过程,然而实际问题常以多个理论为背景.因此,本文重点介绍理论组合判定方法,概述SMT求解器的发展现状,并分析了几个主流SMT求解器理论组合判定关键技术.通过对照实验,评估...     

RTL验证中的混合可满足性求解

RTL混合可满足性求解方法分为基于可满足性模理论(SMT)和基于电路结构搜索两大类.前者主要使用逻辑推理的方法,目前已在处理器验证中得到了广泛的应用,主要得益于SMT支持用于描述验证条件的基础理论;后者能够充分地利用电路中的约束信息,因而求解效率较高.介绍了每一大类中的典型研究及其所采用的重要策略,以及RTL可满足性求解方面的研究进展.     

一种求解布尔不可满足子式的局部搜索算法

解释布尔公式不可满足的原因在众多领域都具有非常重要的理论与应用价值,而不可满足子式能够为公式不可满足的原因提供精确的解释,帮助应用领域的自动化工具迅速定位错误,诊断问题失败的本质缘由。近年来涌现了许多基于SAT求解器DPLL回溯搜索过程的完全算法,但关于不完全方法提取不可满足子式的研究相对较少。因此,本文提出一种采用启发式局部搜索过程从公式的不可满足性证明中求解布尔不可满足子式的算法。该算法根据公式的消解规则通过局部搜索过程直接构造证明不可满足性的消解序列,并融合了布尔推理技术以提高搜索效率;而后通过一个递归过程遍历证明序列从而得到不可满足子式。通过实验与贪心遗传算法进行对比,结果表明本文提出的算法优于贪心遗传算法。     

基于树状线性规划搜索的单调速率优化设计

改善单调速率(rate monotonic,简称RM)可调度性判定算法的效率,是过去40年计算机实时系统设计的重要问题.最近,研究人员把可调度性判定问题扩展到了更一般的优化设计问题,即,如何调节在区间可选择情况下的任务运行时间,使得:(1)系统RM可调度;(2)系统的某个性能(如CPU利用率)达到最优.在已有的求解实时系统RM优化设计问题的方法中,都是先把原问题建模成广义约束优化问题,然后再对广义约束优化问题进行求解.但现有方法的求解速度较慢,任务数较多时不再适用.提出一种求解优化问题的方法——基于树状的线性规划搜索(linearprogramming search,简称LPS)方法.该方法先将实时系统RM优化设计问题建模成广义约束优化问题,再将其分拆成若干线性规划子问题,然后构造线性规划搜索树,利用剪枝搜索算法求解部分线性规划子问题,最后得到优化解.实验结果表明:LPS方法相比于已有的方法能够节省20%~70%的求解时间,任务数越多,节省时间越多.该研究成果可以与计算机可满足性模定理(satisfiability modulo theories,简称SMT)领域的多个研究热点问题联系起来,并可望改善SMT问题的求解效率.     

语义网的一阶逻辑推理技术支持

研究了一阶逻辑推理工具对语义网的推理支持.语义网的关键推理问题可以化为公式的可满足性判定问题.一阶逻辑的自动定理证明器可以证明不可满足性,而有限模型查找器为可满足的公式在有限域内构造模型.提出在语义网的推理中,同时使用定理证明器和有限模型查找器.实验结果表明,这样可以解决描述逻辑工具的不足,并可以弥补定理证明器对可满足的公式推理的不完备性.     

基于可满足性模理论的虚拟网映射问题求解

针对物理网络不支持路径分割且物理节点不支持重复映射的虚拟网映射问题，建立以物理网络资源消耗量最小化为目标的整数线性规划模型；基于可满足性模理论，构建这类虚拟网映射问题的SMT公式，并采用SMT求解器求解最优解。实验表明，所提方法能有效提高虚拟网络构建请求的接受率和物理网络提供商的长期收益。     

SMT求解技术简述

SMT问题是在特定理论下判定一阶逻辑公式可满足性问题。它在很多领域,尤其是形式验证、程序分析、软件测试等领域,都有重要的应用。介绍了SMT问题的基本概念、相关定义以及目前的主流理论。近年来出现了很多提高SMT求解效率的技术,着重介绍并分析了这些技术,包括积极类算法、惰性算法及其优化技术等。介绍了目前的主流求解器和它们各自的特点,包括Z3、Yices、CVC3/CVC4等。对SMT求解技术的前景进行了展望,量词的处理、优化问题和解空间大小的计算等尤其值得关注。     

Approximate counting in SMT and value estimation for probabilistic programs

#SMT, or model counting for logical theories, is a well-known hard problem that generalizes such tasks as counting the number of satisfying assignments to a Boolean formula and computing the volume of a polytope. In the realm of satisfiability modulo theories (SMT) there is a growing need for model counting solvers, coming from several application domains (quantitative information flow, static analysis of probabilistic programs). In this paper, we show a reduction from an approximate version of #SMT  to SMT. We focus on the theories of integer arithmetic and linear real arithmetic. We propose model counting algorithms that provide approximate solutions with formal bounds on the approximation error. They run in polynomial time and make a polynomial number of queries to the SMT solver for the underlying theory, exploiting “for free” the sophisticated heuristics implemented within modern SMT solvers. We have implemented the algorithms and used them to solve the value problem for a model of loop-free probabilistic programs with nondeterminism.

     

基于可满足性模理论的多处理机通信延迟优化任务调度方法

在一组相同处理器上调度带有通信延迟的任务图以实现其最短的执行时间,这在并行计算的调度理论和实践中具有重要的意义。针对具有通信延迟的任务图调度问题,提出一种基于可满足性模理论（SMT）的改进SMT方法。首先,将处理器映射约束和任务执行顺序等约束条件进行编码,将任务图调度问题转化为SMT问题;然后,调用SMT求解器对可行解空间进行搜索,以确定问题最优解。在约束编码阶段,使用整型变量表示任务和处理器的映射关系,从而降低处理器约束编码的复杂程度;在求解器调用阶段,通过添加独立任务的约束条件减小求解器的搜索空间,进一步提升最优解的查找效率。实验结果表明,与原始SMT方法相比,改进SMT方法在20 s和1 min超时实验中的平均求解时间分别减少了65.9%与53.8%,并且在处理器数量较多时取得了更大的效率优势。改进的SMT方法可以有效求解带通信延迟的任务图调度问题,尤其适用于处理器数量较多的调度场景。     

Modelling and solving temporal reasoning as propositional satisfiability

Representing and reasoning about time dependent information is a key research issue in many areas of computer science and artificial intelligence. One of the best known and widely used formalisms for representing interval-based qualitative temporal information is Allen's interval algebra (IA). The fundamental reasoning task in IA is to find a scenario that is consistent with the given information. This problem is in general NP-complete.In this paper, we investigate how an interval-based representation, or IA network, can be encoded into a propositional formula of Boolean variables and/or predicates in decidable theories. Our task is to discover whether satisfying such a formula can be more efficient than finding a consistent scenario for the original problem. There are two basic approaches to modelling an IA network: one represents the relations between intervals as variables and the other represents the end-points of each interval as variables. By combining these two approaches with three different Boolean satisfiability (SAT) encoding schemes, we produced six encoding schemes for converting IA to SAT. In addition, we also showed how IA networks can be formulated into satisfiability modulo theories (SMT) formulae based on the quantifier-free integer difference logic (QF-IDL). These encodings were empirically studied using randomly generated IA problems of sizes ranging from 20 to 100 nodes. A general conclusion we draw from these experimental results is that encoding IA into SAT produces better results than existing approaches. More specifically, we show that the new point-based 1-D support SAT encoding of IA produces consistently better results than the other alternatives considered. In comparison with the six different SAT encodings, the SMT encoding came fourth after the point-based and interval-based 1-D support schemes and the point-based direct scheme. Further, we observe that the phase transition region maps directly from the IA encoding to each SAT or SMT encoding, but, surprisingly, the location of the hard region varies according to the encoding scheme. Our results also show a fixed performance ranking order over the various encoding schemes.     

SAT–LP–IIS joint-directed path-oriented bounded reachability analysis of linear hybrid automata

As discrete jumps and continuous flows tangle in the behavior of linear hybrid automata (LHA), the bounded model checking (BMC) for reachability of LHA is a challenging problem. Current works try to handle this problem by encoding all the discrete and continuous behaviors in the bound into a set of SMT formulas which can then be solved by SMT solvers. However, when the system size is large, the object SMT problem could be huge and difficult to solve. Instead of encoding everything into one constraint set, this paper proposes a SAT–LP–IIS joint-directed solution to conduct the BMC for reachability of LHA in a layered way. First, the bounded graph structure of LHA is encoded into a propositional formula set, and solved by SAT solvers to find potential paths which can reach the target location on the graph. Then, the feasibility of certain path is encoded into a set of linear constraints which can then be solved by linear programming (LP) efficiently. If the path is not feasible, irreducible infeasible set (IIS) technique is deployed to locate an infeasible path segment which will be fed to the SAT solver to accelerate the enumerating process. Experiments show that by this SAT–LP–IIS joint-directed solution, the memory usage of the BMC of LHA is well-controlled and the performance outperforms the state-of-the-art SMT-style competitors significantly.     

带实际约束的大规模车辆路径问题建模及求解

针对现有算法不能有效求解卷烟配送过程中, 问题规模大并具有诸多实际约束条件限制这类实际问题, 首 先分析实际约束, 建立问题模型; 然后从模型出发设计多阶段算法, 通过地理信息的分级管理实现区域划分, 在降低 问题规模的同时消除交通障碍; 采用改进的k 均值聚类法分派线路, 将问题转化为求解小规模旅行商问题; 最后以济 南市区的卷烟配送为例, 通过与典型优化算法的比较表明了所提出多阶段算法在实际应用中的优越性.

     

SAT Modulo Linear Arithmetic for Solving Polynomial Constraints

Polynomial constraint solving plays a prominent role in several areas of hardware and software analysis and verification, e.g., termination proving, program invariant generation and hybrid system verification, to name a few. In this paper we propose a new method for solving non-linear constraints based on encoding the problem into an SMT problem considering only linear arithmetic. Unlike other existing methods, our method focuses on proving satisfiability of the constraints rather than on proving unsatisfiability, which is more relevant in several applications as we illustrate with several examples. Nevertheless, we also present new techniques based on the analysis of unsatisfiable cores that allow one to efficiently prove unsatisfiability too for a broad class of problems. The power of our approach is demonstrated by means of extensive experiments comparing our prototype with state-of-the-art tools on benchmarks taken both from the academic and the industrial world.     

欠驱动刚性航天器时间最优轨迹规划设计

应用伪谱法解决欠驱动刚性航天器的时间最优轨迹规划问题.首先建立欠驱动刚性航天器的动力学和运动学模型,对于给定的初末姿态,选取机动时间最短为待优化的性能指标,并考虑到实际控制输入受限,将其转化为优化过程中的不等式约束条件;然后应用Legendre伪谱法,将优化问题离散化为非线性规划问题进行求解.仿真结果表明,应用伪谱法规划得到的欠驱动航天器最优轨迹,能够较好地满足各种约束条件,而且计算精度高、速度快,具有良好的实时性.     

基于目标和关键点检测的单目托盘定位

托盘的识别与定位是无人叉车中关键的问题之一.当前托盘定位多采用目标检测的方法,然而目标检测只能识别托盘在图像中的位置,无法得到托盘的空间信息.针对此问题,本文提出了一种基于目标和关键点检测的单目托盘定位方法,用于检测托盘并计算托盘当前的倾角和距离.首先对托盘进行目标检测,然后将检测的结果进行裁剪后输入到关键点检测网络中.通过对托盘关键点的检测和托盘固有的几何外形特征,设计边缘自适应调整,得到高精度的托盘轮廓信息.根据几何约束提出了基于轮廓点的托盘倾角与距离计算方法,并采用RANSAC算法提升了计算结果的精度和稳定性,解决了托盘的定位问题.实验表明,本文提出的算法在倾角计算上平均误差在5°以内,水平距离计算上平均误差在110 mm以内,能较好地定位托盘,具有较高的实用价值.