Stochastic Approach to Vehicle Routing Problem: Development and Theories Abstract In this article, a chance constrained (CCP) formulation of the Vehicle Routing Problem (VRP) is proposed. The reality is that once we convert some special form of probabilistic constraint into their equivalent deterministic form then a nonlinear constraint generates. Knowing that reliable computer software...

In this paper, we propose a computational model for the direct execution of general specifications with multi-way constraints. Although this computational model has a similar structure to conventional constraint programming models, it is not meant for solving constraint satisfaction problems but rather for the simulation of social systems and to continue to execute assigned processes. Because o...

Constraint programming is a powerful paradigm for solving combinatorial search problems that draws on a wide range of techniques from artificial intelligence, operations research, algorithms, graph theory and elsewhere. The basic idea in constraint programming is that the user states the constraints and a general purpose constraint solver is used to solve them. Constraints are just relations, a...

Constraint programming o ers modeling features and solution methods that are un available in mathematical programming but its models are not declarative This raises this issue as to whether the two approaches can be combined in a declarative modeling frame work This paper proposes a general declarative modeling system in which the conditional structure of the constraints shows how to integrate ...

To model combinatorial decision problems involving uncertainty and probability, we have proposed “stochastic constraint programming” [3]. This extends constraint programming with stochastic variables, chance constraints and optimized expectations. We propose extending the OPL modelling language [1] with these features, and show how they can be compiled away using some simple rules.

Feature models have been cited as one of the main contributions to model software product families. However, there is still a gap in product family engineering which is the automated reasoning on feature models. In this paper we describe how to reason on feature models using constraint programming. Although, there are a few attempts to reason on feature models there are two main drawbacks in th...

We extend the Constraint Logic Programming (CLP) formalism in order to handle semiring-based constraint systems. This allows us to perform in the same language both constraint solving and optimization. In fact, constraint systems based on semirings are able to model both classical constraint solving and more sophisticated features like uncertainty, probability , fuzzyness, and optimization. We ...

We extend the Constraint Logic Programming (CLP) formalism in order to handle semiringbased constraint systems. This allows us to perform in the same language both constraint solving and optimization. In fact, constraint systems based on semirings are able to model both classical constraint solving and more sophisticated features like uncertainty, probability, fuzzyness, and optimization. We th...