Propagation by Selective Initialization and Its Application to Numerical Constraint Satisfaction Problems

TL;DR

This paper introduces selective initialization, a modification to constraint propagation that enhances efficiency in handling composite arithmetic expressions within numerical constraint satisfaction problems, enabling closer solution set approximation.

Contribution

The paper presents theorems supporting selective initialization, improving the efficiency of constraint propagation for complex arithmetic expressions in numerical constraint satisfaction.

Findings

Selective initialization reduces computational cost

Enables more efficient handling of composite expressions

Supports closer approximation of solution sets

Abstract

Numerical analysis has no satisfactory method for the more realistic optimization models. However, with constraint programming one can compute a cover for the solution set to arbitrarily close approximation. Because the use of constraint propagation for composite arithmetic expressions is computationally expensive, consistency is computed with interval arithmetic. In this paper we present theorems that support, selective initialization, a simple modification of constraint propagation that allows composite arithmetic expressions to be handled efficiently.