In this paper we review the current state of the problem solving environment (PSE) field and make projections for the future. First we describe the computing context, the definition of a PSE and the goals of a PSE. The state-of-the-art is summarized along with sources (books, bibliographics, web sites) of more detailed information. The principal components and paradigms for building PSEs are presented. The discussion of the future is given in three parts: future trends, scenarios for 2010/2025, and research

: Optimization algorithms can exploit problem structures of various kinds, such as sparsity of derivatives, complementarity conditions, block structure, stochasticity, priorities for discrete variables, and information about piecewiselinear terms. Moreover, some algorithms deduce additional structural information that may help the modeler. We review and discuss some ways of conveying structure, with examples from our designs for the AMPL modeling language. We show in particular how "declared suffixes" provide a new and useful way to express structure and acquire solution information. 1. INTRODUCTION A modeling language can provide a useful way to express the elaborate optimization problems that often arise in practice. Many of these problems have structure that an optimization algorithm can exploit, such as sparsity of first and second derivatives, complementarity conditions, block structure, time-dependent stochasticity, priorities for discrete variables, and information about piecew...

thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public. Determining the maximum power system loadability, as well as preventing the system from being operated close to the stability limits is very important in power systems planning and operation. The application of optimization techniques to power systems security and electricity markets is a rather relevant research area in power engineering. The study of optimization models to determine critical operating conditions of a power system to obtain secure power dispatches in an electricity market has gained particular attention. This thesis studies and develops optimization models and techniques to detect or avoid voltage instability points in a power system in the context of a competitive electricity market. A thorough analysis of an optimization model to determine the maximum power loadability points is first presented, demonstrating that a solution of this model corresponds to either Saddle-node Bifurcation (SNB) or Limit-induced Bifurcation

The design of the AMPL modeling language stresses naturalness of expressions, generality of iterating over sets, separation of model and data, ease of data manipulation, and automatic updating of derived values when fundamental values change. We show how such principles have guided the addition of database access, complementarity modeling, and other language features.

Optimization, mathematical programming, linear programming, modeling languages Optimization algorithms can exploit problem structures of various kinds, such as sparsity of derivatives, complementarity conditions, block structure, stochasticity, priorities for discrete variables, and information about piecewiselinear terms. Moreover, some algorithms deduce additional structural information that may help the modeler. We review and discuss some ways of conveying structure, with examples from our designs for the AMPL modeling language. We show in particular how Òdeclared suffixesÓ provide a new and useful way to express structure and acquire solution information. 1.