Virtual interpolation of discrete multi-objective programming solutions with probabilistic operation

• Autor(a) principal: Silva,Ricardo C.
• Data de Publicação: 2011
• Outros Autores: Arruda,Edilson F., Ourique,Fabrício O.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Sba: Controle & Automação Sociedade Brasileira de Automatica
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0103-17592011000400005
• topic: Pareto-optimality; Dynamic operation; Discrete optimization

This work presents a novel framework to address the long term operation of a class of multi-objective programming problems. The proposed approach considers a stochastic operation and evaluates the long term average operating costs/profits. To illustrate the approach, a two-phase method is proposed which solves a prescribed number of K mono-objective problems to identify a set of K points in the Pareto-optimal region. In the second phase, one searches for a set of non-dominated probability distributions that define the probability that the system operates at each point selected in the first phase, at any given operation period. Each probability distribution generates a vector of average long-term objectives and one solves for the Pareto-optimal set with respect to the average objectives. The proposed approach can generate virtual operating points with average objectives that need not have a feasible solution with an equal vector of objectives. A few numerical examples are presented to illustrate the proposed method.