(5) Applying Constraint Logic Programming Languages for Modelling Multi-objective Decision Making under Uncertainty

This project aims to develop a modelling tool for large scale multi-objective decision problems by applying constraint logic programming technologies. The distinct advantage of the logical specification lies in its declarative nature and the flexibility of abstraction, thus enabling operations research to be effectively applied to real world applications.
A CLP specified business model can then be translated into mixed integer linear programming problem solved using parallel constraint solvers.

The concrete research subjects of the project include:
1)A logic based framework to support the natural specification of complex modelling and decision making procedures.

2)A methodology for translating such logic-based specifications into an integer programming formulation.

3)The modelling language will interface with a set of parallel constraint solvers including simplex algorithm, Grobner base symbolic IP solver and interior point algorithm.

4)A WWW-based interface to support easy system deployment.

The currently available deliverables include:
1) A prototype of the logic based modelling language implemented in Prolog

2) A prototype of the Grobner based symbolic IP solver designed for solving stochastic integer programming problem

Research Period :	June 1997 - February 1998
Cooperate Researchers :	Yike Guo Imperial College Berc Rustem Imperial College