Conditional Preference Network with Constraints and Uncertainty

In multi-attribute preference-based reasoning, the CP-net is a graphical model to represent user's conditional ceteris paribus (all else being equal) preference statements. This paper outlines three aspects of the CP-net. First, when a CP-net is involved with a set of hard constraints, solving the Constrained CP-net requires dominance testing which is a very expensive operation. We tackle this problem by extending the CP-net model such that dominance testing is not needed. Second, user's choices involve habitual behavior and genuine decision. The former is represented using preferences, while we introduce the notion of comfort to represent the latter. Then, we suggest an extension of the CP-net which can represent both preference and comfort. Third, preferences often come with noise and uncertainty. In this regard, we suggest the probabilistic extension of the Tradeoff-enhanced CP-net (TCP-net) model. The necessary semantics and usefulness of the extensions above are described. Finally, we outline some in-progress and future work.

A Case Study of Integrated Asset Modeling to Support Reservoir Management Strategies for Four Dry Gas Fields Sharing Production Facilities

The integrated asset modeling has gained popularity in the last years because it has a positive impact on field development, optimization and reservoir management. Especially it has become a must be to properly analyze the interaction between a reservoir and its production facilities or to predict the behavior of several fields sharing a common surface production facility (Ghorayeb, k. 2005). As a result of the strategic development plan, PEMEX Veracruz Asset has been discovering dry gas fields which must be produced through shared production facilities in order to be economic. This poses a complex operational scenario that demands the use of technology that enables the analysis of the whole system and the interrelation of its elements to support the reservoir management strategies. This paper describes a case study in which four reservoir models were coupled with a production network model, with the objective to maximize the recovery factor, identify operational problems along the exploitation, and also evaluate the water production impact, through the Integrated Asset Modeling (IAM) enabling the design of different exploitation strategies including compression stages and evaluate them both technically and economically. Besides it includes a full description of the modeling process with all the assumptions, constraints, solving method and results obtained. This methodology has been successfully implemented adding value to the asset due to a proven improvement in the reservoir management, operational plans and decision making process.

Consistency Maintenance of Collaborative Product Design Based on the Semantics Reasoning

Consistency maintenance is a key problem in collaborative product design. Firstly, based on product design theory, the semantics relationships described by XML among components in collaborative product design system are made. Secondly, the associated components are determined through backward and forward semantics reasoning. Finally, the data is updated by constraints solving, and the consistency maintenance is achieved.

A Comparative Study of Redundant Constraints Identification Methods in Linear Programming Problems

The objective function and the constraints can be formulated as linear functions of independent variables in most of the real-world optimization problems. Linear Programming (LP) is the process of optimizing a linear function subject to a finite number of linear equality and inequality constraints. Solving linear programming problems efficiently has always been a fascinating pursuit for computer scientists and mathematicians. The computational complexity of any linear programming problem depends on the number of constraints and variables of the LP problem. Quite often large-scale LP problems may contain many constraints which are redundant or cause infeasibility on account of inefficient formulation or some errors in data input. The presence of redundant constraints does not alter the optimal solutions(s). Nevertheless, they may consume extra computational effort. Many researchers have proposed different approaches for identifying the redundant constraints in linear programming problems. This paper compares five of such methods and discusses the efficiency of each method by solving various size LP problems and netlib problems. The algorithms of each method are coded by using a computer programming language C. The computational results are presented and analyzed in this paper.