On the maximum acyclic subgraph problem under disjunctive constraints

Disjunctively constrained versions of classic problems in graph theory such as shortest paths, minimum spanning trees and maximum matchings were recently studied. In this article we introduce disjunctive constrained versions of the Maximum Acyclic Subgraph problem. Negative disjunctive constraints state that a certain pair of edges cannot be contained simultaneously in a feasible solution. Positive disjunctive constraints enforces that at least one arc for the underlying pair is in a feasible solution. It is convenient to represent these disjunctive constraints in terms of an undirected graph, called constraint graph, whose vertices correspond to the arcs of the original graph, and whose edges encode the disjunctive constraints. For the Maximum Acyclic Subgraph problem under Negative Disjunctive Constraints we develop 1/2-approximative algorithms that are polynomial for certain classes of constraint graphs. We also show that determining if a feasible solution exists for an instance of the Maximum Acyclic Subgraph problem under Positive Disjunctive Constraints is an NP-Complete problem.     

工作流系统带权角色与周期时间访问控制模型

带权角色激活任务和周期时间授权是工作流系统访问控制研究尚未解决的核心问题.以基于角色的访问控制模型为基础,提出了一种新的工作流系统带权角色与周期时间访问控制模型WRPTAC(weighted role and periodic time access control).讨论了周期时间表示方法,定义了工作流系统授权新概念和时态授权推导规则,给出了时间复杂度为O(n²)的时态授权推导规则一致性验证图论算法,并定义了任务激活约束规则.它能够表达复杂的工作流系统访问控制约束.     

Modeling and reasoning techniques in geologic interpretation

A thorough investigation is reported on the qualitative modeling of geologic systems, focusing on the reconstruction of three-dimensional (3-D) profiles from image data by means of spatial and temporal reasoning techniques. A conceptual model of the relevant knowledge is proposed for both the domain elements and the inference processes. At the former level the authors describe the objects in terms of geometric primitives and relations among them; at the inference level, reconstruction is identified as a synthesis task, in which a 3-D model of underground bodies results from assembling simpler components. The process is incremental and nomnonotonic, according to a basic assemble-validate-and-debug cycle, underlying both low-level and high-level steps. A formal (logical) model of the latter is proposed and worked out in detail. Concepts from topology and graph theory provide effective tools to define representations and algorithms, and allow one to address the intertwining of spatial and temporal knowledge. Some relevant reasoning steps are also regarded as constraint satisfaction problems. The authors analyze the constraints, show that the related tasks can be solved with algorithms of polynomial complexity, and provide the appropriate procedures. The practical feasibility of the model has been tested, and results of the applications to realistic input data are discussed. The authors also discuss solutions for embedding the modules into a man-machine interface for the intelligent support to the interpretation of data     

High-Order Consistency in Valued Constraint Satisfaction

k-consistency operations in constraint satisfaction problems (CSPs) render constraints more explicit by solving size-k subproblems and projecting the information thus obtained down to low-order constraints. We generalise this notion of k-consistency to valued constraint satisfaction problems (VCSPs) and show that it can be established in polynomial time when penalties lie in a discrete valuation structure.A generic definition of consistency is given which can be tailored to particular applications. As an example, a version of high-order consistency (face consistency) is presented which can be established in low-order polynomial time given certain restrictions on the valuation structure and the form of the constraint graph.     

Hybrid genetic algorithms for timetabling

Hybrid genetic algorithms are presented that use optimization heuristics and genetic techniques to outperform all existing programs for the timetabling problem. The timetabling problem is very hard (NP-complete) and a general polynomial time deterministic algorithm is not known. An artificial intelligence approach, in a logic programming environment, may be useful for such a problem. The decomposition and classification of constraints and the constraint ordering to obtain the minimization of the backtracking and the maximization of the parallelism are illustrated. The school timetabling problem is discussed in detail as a case study. The genetic algorithm approach is particularly well suited for this kind of problem, since there exists an easy way to assess a good timetable but not a well-structured automatic technique for constructing it. So, a population of timetables is created that evolves toward the best solutions. The evaluation function and the genetic operators are well separated from the domain-specific parts, such as the problem knowledge and the heuristics, i.e., from the timetable builder. A fundamental issue and a general problem in the decision process and automated reasoning is how to efficiently obtain logic decisions under disjunctive constraints. Logic constraint satisfaction problems are in general NP-hard and a general deterministic polynomial time algorithm is not known. The present article illustrates an approach based on the hybridization of constrained heuristic search with novel genetic algorithm techniques. It compares favorably with the best-known programs to solve decisions problems under logic constraints. Complexity of the new algorithms and results of significant experiments are reported. © 1996 John Wiley & Sons, Inc.     

An architecture for workflow scheduling under resource allocation constraints

Research on specification and scheduling of workflows has concentrated on temporal and causality constraints, which specify existence and order dependencies among tasks. However, another set of constraints that specify resource allocation is also equally important. The resources in a workflow environment are agents such as person, machine, software, etc. that execute the task. Execution of a task has a cost and this may vary depending on the resources allocated in order to execute that task. Resource allocation constraints define restrictions on how to allocate resources, and scheduling under resource allocation constraints provide proper resource allocation to tasks. In this work, we provide an architecture to specify and to schedule workflows under resource allocation constraints as well as under the temporal and causality constraints. A specification language with the ability to express resources and resource allocation constraints and a scheduler module that contains a constraint solver in order to find correct resource assignments are core and novel parts of this architecture.     

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。     

A job-shop problem with one additional resource type

We consider a job-shop scheduling problem with n jobs and the constraint that at most p<n jobs can be processed simultaneously. This model arises in several manufacturing processes, where each operation has to be assisted by one human operator and there are p (versatile) operators. The problem is binary NP-hard even with n=3 and p=2. When the number of jobs is fixed, we give a pseudopolynomial dynamic programming algorithm and a fully polynomial time approximation scheme (FPTAS). We also propose an enumeration scheme based on a generalized disjunctive graph, and a dynamic programming-based heuristic algorithm. The results of an extensive computational study for the case with n=3 and p=2 are presented.     

Negative Results for Equivalence Queries

We consider the problem of exact identification of classes of concepts using only equivalence queries. We define a combinatorial property,approximate fingerprints, of classes of concepts and show that no class with this property can be exactly identified in polynomial time using only equivalence queries. As applications of this general theorem, we show that there is no polynomial time algorithm using only equivalence queries that exactly identifies deterministic or nondeterministic finite state acceptors, context free grammars, or disjunctive or conjunctive normal form boolean formulas.     

Temporal linear relaxation in IBM ILOG CP Optimizer

IBM ILOG CP Optimizer is a constraint solver that implements a model-and-run paradigm. For scheduling problems, CP Optimizer provides a relatively simple but very expressive modeling language based on the notion of interval variables. This paper presents the temporal linear relaxation (TLR) used to guide the automatic search when solving scheduling problems that involve temporal and resource allocation costs. We give the rationale of the TLR, describe its integration in the automatic search of CP Optimizer, and present the relaxation of most of the constraints and expressions of the model. An experimental study on a set of classical scheduling benchmarks shows that using the TLR is essential for problems with irregular temporal costs and generally helps for problems with resource allocation costs.     

Dulmage-Mendelsohn Canonical Decomposition as a generic pruning technique

We introduce a new generic propagation mechanism for constraint programming. A first advantage of our pruning technique stems from the fact that it can be applied on various global constraints. In this work we describe a filtering scheme for such a family based on Dulmage-Mendelsohn Structure Theorem. Our method checks the feasibility in polynomial time and then ensures hyper-arc consistency in linear time. It is also applicable to any soft version of global constraint expressed in terms of a maximum matching in a bipartite graph and remains of linear complexity.     

基于改进遗传算法的多天线地面站硬件资源分配方法

多天线卫星地面站硬件设备资源分配问题是一个基于约束满足的复杂资源组合优化问题。在考虑任务执行时间、地面站可见时间窗口、地面站设备接收能力和设备链路约束的情况下,对多天线地面站硬件资源分配问题建立了高可用模型。以加权任务执行总时间为目标,以经典遗传算法为基础,根据问题特点改进了相关遗传算子,在进行遗传变异的过程中,通过深度优先搜索算法确定单个染色体对应的最佳资源分配方案,同时利用启发式信息优化搜索过程。最后通过高可用算例仿真表明,所建模型和算法是合理有效的。     

A CSP model for simple non-reversible and parallel repair plans

This work presents a constraint satisfaction problem (CSP) model for the planning and scheduling of disassembly and assembly tasks when repairing or substituting faulty parts. The problem involves not only the ordering of assembly and disassembly tasks, but also the selection of them from a set of alternatives. The goal of the plan is the minimization of the total repairing time, and the model considers, apart from the durations and resources used for the assembly and disassembly tasks, the necessary delays due to the change of configuration in the machines, and to the transportation of intermediate subassemblies between different machines. The problem considers that sub-assemblies that do not contain the faulty part are nor further disassembled, but allows non-reversible and parallel repair plans. The set of all feasible repair plans are represented by an extended And/Or graph. This extended representation embodies all of the constraints of the problem, such as temporal and resource constraints and those related to the selection of tasks for obtaining a correct plan.     

Experimental Analysis of Numeric and Symbolic Constraint Satisfaction Techniques for Temporal Reasoning

Many temporal applications like planning and scheduling can be viewed as special cases of the numeric and symbolic temporal constraint satisfaction problem. Thus we have developed a temporal model, TemPro, based on the interval Algebra, to express such applications in term of qualitative and quantitative temporal constraints. TemPro extends the interval algebra relations of Allen to handle numeric information. To solve a constraint satisfaction problem, different approaches have been developed. These approaches generally use constraint propagation to simplify the original problem and backtracking to directly search for possible solutions. The constraint propagation can also be used during the backtracking to improve the performance of the search. The objective of this paper is to assess different policies for finding if a TemPro network is consistent. The main question we want to answer here is how much constraint propagation is useful for finding a single solution for a TemPro constraint graph. For this purpose, we have experimented by randomly generating large consistent networks for which either arc and/or path consistency algorithms (AC-3, AC-7 and PC-2) were applied. The main result of this study is an optimal policy combining these algorithms either at the symbolic (Allen relation propagation) or at the numerical level.     

Extending constraint logic programming for temporal reasoning

In recent years, several constraint‐based temporal reasoning frameworks have been proposed. They consider temporal points or intervals as domain elements linked by temporal constraints. Temporal reasoning in these systems is based on constraint propagation. In this paper, we argue that a language based on constraint propagation can be a suitable tool for expressing and reasoning about temporal problems. We concentrate on Constraint Logic Programming (CLP) which is a powerful programming paradigm combining the advantages of Logic Programming and the efficiency of constraint solving. However, CLP presents some limitations in dealing with temporal reasoning. First, it uses an “arc consistency” propagation algorithm which is embedded in the inference engine, cannot be changed by the user, and is too weak in many temporal frameworks. Second, CLP is not able to deal with qualitative temporal constraints. We present a general meta CLP architecture which maintains the advantages of CLP, but overcomes these two main limitations. Each architectural level is a finite domain constraint solver(CLP(FD)) that reasons about constraints of the underlying level. Based on this conceptual architecture, we extend the CLP(FD)language and we specialize the extension proposed on Vilain and Kautz’sPoint Algebra, on Allen’s Interval Algebra and on the STP framework by Dechter, Meiri and Pearl. In particular, we show that we can cope effectively with disjunctive constraints even in an interval‐based framework. This revised version was published online in June 2006 with corrections to the Cover Date.     

Scheduling of no buffer job shop cells with blocking constraints and automated guided vehicles

The blocking job shop (BJS) problem is an extension of a job shop problem with no buffer constraints. It means that after a job is completed on the current machine, it remains on that machine until the next machine becomes available. This paper addresses an extension of the BJS problem, which takes into account transferring jobs between different machines using a limited number of automated guided vehicles (AGV), called a BJS–AGV problem. Two integer non-linear programming (INLP) models are proposed. A two-stage heuristic algorithm that combines an improving timetabling method and a local search is proposed to solve the BJS–AGV problem. A neighborhood structure in the local search is proposed based on a disjunctive graph model. According to the characteristics of the BJS–AGV problem, four principles are proposed to guarantee the feasibility of the search neighborhood. Computation results are presented for a set of benchmarking tests, some of which are enlarged by transportation times between different machines. The numerical results show the effectiveness of the proposed two-stage algorithm.     

Constraint models for graceful graphs

We present three constraint models of the problem of finding a graceful labelling of a graph, or proving that the graph is not graceful. An experimental comparison of the models applied to different classes of graph is given. The first model seems a natural way to represent the problem, but explores a much larger search tree than the other models. The second model does much less search, by making the most constrained decisions first, but is slow because the constraints are time-consuming to propagate. The third model combines the best features of the others, doing little more search than the second model while being much the fastest of the three. The comparison of the three models provides a useful case-study of modelling problems as constraint satisfaction problems. In addition, we show that constraint programming can be a useful tool for the study of graceful graphs; the models presented here have contributed many new results.     

实时、交互嵌入式系统的频率推导问题

嵌入系统在严格的时间约束(外部约束)下连续地与外界环境相互作用,把这些外部约束转换成系统任务的时间预算(内部约束)是非常重要的。知道这些时间预算能降低系统设计与验证问题的复杂度,并有助于设计者对系统的功能和时间正确性从设计的一开始就能同步地控制。转换用系统的任务结构和从环境对系统的输入刺激的频率推导系统中每个任务的频率,推导出的任务频率被用来推导和验证其余的内部和外部约束。提出了一个广义任务图模型去表示系统的任务结构,并给出了推导和验证系统时间约束的方法和一个把它们融合在一起的硬件/软件协同设计方法。