A key task in combinatorial optimisation is the minimisation of discrete functions. Important examples are submodular functions, see e. g. [6, 13, 14, 17], and bisubmodular functions, see e. g. [2, 6, 14, 16]. These functions can be viewed as (special) functions from D to R where D is a 2-element set for the submodular case and a 3-element set for the bisubmodular case. Fix a finite set D. One ...

A method is proposed for automatic synthesis of quantitative feedback theory (QFT) based robust fractional-order controllers. The problem of QFT controller synthesis is formulated as an interval constraint satisfaction problem, where the nonlinear and non-convex robust stability and tracking bound specifications form the constraints. The problem is solved using the branch and prune algorithm. A...

The paper aims to analyze the differences in employees’ work stress and job satisfaction across the casino hotels and the non-casino hotels in Macau. Through questionnaires, the paper investigates total 400 employees from both casino hotels and non-casino hotels. Work stress and job satisfaction of employees in casino hotels and non-casino hotels are compared. Statistic techniques such as descr...

In maintaining consistencies, such as GAC*, FDGAC* and weak EDGAC*, for global cost functions, Weighted CSP (WCSP) solvers rely on the projection and extension operations, which entail the computation of the cost functions’ minima. Tractability of this minimum computation is essential for efficient execution. Since projections/extensions modify the cost functions, an important issue is tractabl...

A common technique for bounding the runtime required to solve a constraint satisfaction problem is to exploit the structure of the problem's constraint graph [Dechter, 92]. We show that a simple structure-based technique with a minimal space requirement, pseudo-tree search [Freuder & Quinn, 85], is capable of bounding runtime almost as effectively as the best exponential space-consuming schemes...

Motivated by a desire to understand the computational complexity of counting constraint satisfaction problems (counting CSPs), particularly the complexity of approximation, we study functional clones of functions on the Boolean domain, which are analogous to the familiar relational clones constituting Post’s lattice. One of these clones is the collection of log-supermodular (lsm) functions, whi...

In this paper we study the complexity of the maximum constraint satisfaction problem (Max CSP) over an arbitrary finite domain. An instance of Max CSP consists of a set of variables and a collection of constraints which are applied to certain specified subsets of these variables; the goal is to find values for the variables which maximize the number of simultaneously satisfied constraints. Usin...

An important extension of constraint technology involves problems that undergo changes that may invalidate the current solution. Previous work on dynamic problems sought methods for eeciently nding new solutions. We take a more proactive approach, exploring methods for nding solutions more likely to remain valid after changes that temporarily alter the set of valid assignments (stable solutions...

Load balancing across a networked environment is a monotonous job. Moreover, if the job to be distributed is a constraint satisfying one, the distribution of load demands core intelligence. This paper proposes parallel processing through Global Evaluation Function by means of randomly initialized agents for solving Constraint Satisfaction Problems. A potential issue about the number of agents i...