Many works in the area of Constraint Programming have focused on inference, and more precisely, on filtering methods based on properties of constraint networks. Such properties are called domain filtering consistencies when they allow removing some inconsistent values from the domains of variables, and bound consistencies when they focus on bounds of domains. In this paper, we study the relatio...

Yet, two classes of algorithms have been used in partial constraint satisfaction: local search methods and branch&bound search extended by the classical constraint-processing techniques like e.g. forward checking and backmarking. Both classes exhibit characteristic advantages and drawbacks. This article presents a novel approach for solving partial constraint satisfaction problems exhaustively ...

A wide range of counting and occurrence constraints can be specified with just two global primitives: the Range constraint, which computes the range of values used by a sequence of variables, and the Roots constraint, which computes the variables mapping onto a set of values. We focus here on the Roots constraint. We show that propagating the Roots constraint completely is intractable. We there...

This paper studies a life-time consumption-investment problem under the Black-Scholes framework, where consumption rate is subject to lower bound constraint that linearly depends on investor's wealth. It stochastic control with state-dependent which standard theory cannot be directly applied. We overcome this by transforming it into an equivalent in state-independent so can give explicit optima...

We present a variant of the Weighted Maximum Satisfiability Problem (Weighted Max-SAT), which is a modeling of the Semiring Constraint Satisfaction framework. We show how to encode a Semiring Constraint Satisfaction Problem (SCSP) into an instance of a propositional Weighted Max-SAT, and call the encoding Weighted Semiring Max-SAT (WS-Max-SAT). The clauses in our encoding are highly structured ...

The Semiring Constraint Satisfaction Problem (SCSP) framework is a popular approach for the representation of partial constraint satisfaction problems. Considerable research has been done in solving SCSPs, but limited work has been done in building general SCSP solvers. This paper is a part of a series of papers in which incremental changes are made to a branch and bound (BnB) algorithm in orde...

Many mixed-integer constraint satisfaction problems and global optimization problems contain some variables with unbounded domains. Their solution by branch and bound methods to global optimality poses special challenges as the search region is infinitely extended. Many usually strong bounding methods lose their efficiency or fail altogether when infinite domains are involved. Most implemented ...

Two methods are described for enhancing performance of branch and bound methods for overconstrained CSPS. These methods improve either the upper or lower bound, respectively, during search, so the two can be combined. Upper bounds are improved by using heuristic repair methods before search to find a good solution quickly, whose cost is used as the initial upper bound. The method for improving ...