| dc.description.abstract | This thesis evaluates the benefit of meshing mathematical programming and expert systems for
solving capital budgeting problems, using constraint logic programming methods. A review of
modelling capabilities of mathematical programs for capital budgeting, and of financial expert
systems leads to defining the respective role and potential of each method, and to the proposal
of a two-tiered project selection approach: project evaluation and resource allocation.
With emphasis placed on a tight coupling of the two tiers, logic programming is shown
to be a language of choice to implement mathematical programming within an expert system
shell. Prolog has the requisite properties to deal with both logical considerations and optimization
problems. Although Prolog was not primarily designed to solve optimization problems, it is
shown that the backtracking mechanism of the Prolog language is powerful enough for that
purpose; it liberates the programmer from having to implement tree-search programs. A generate
and test program is written in Turbo-Prolog, and compared to a more sophisticated test and
generate implementation that uses methods of constraint satisfaction programming. Continuous
capital budgeting problems. are "solved in CLP(9\~, an experimental extension of Prolog that
enables the solution of simultaneous algebraic constraints, as required to solve linear programs | en |
