Solving multiobjective mathematical programming problems with fixed and fuzzy coefficients

• Main Author: Ruzibiza, Stanislas Sakera
• Other Authors: Luhandjula, M. K.
• Format: Others
• Language: en
• Published: 2011
• Subjects: Multiobjective Programming; Fuzzy set; Pareto optimal solution; Possibility measures; Embedding theorem; 519.7; Programming (Mathematics); Fuzzy logic; Fuzzy sets; Embedding theorems
• Online Access: http://hdl.handle.net/10500/4801

Many concrete problems, ranging from Portfolio selection to Water resource management, may be cast into a multiobjective programming framework. The simplistic way of superseding blindly conflictual goals by one objective function let no chance to the model but to churn out meaningless outcomes. Hence interest of discussing ways for tackling Multiobjective Programming Problems. More than this, in many real-life situations, uncertainty and imprecision are in the state of affairs. In this dissertation we discuss ways for solving Multiobjective Programming Problems with fixed and fuzzy coefficients. No preference, a priori, a posteriori, interactive and metaheuristic methods are discussed for the deterministic case. As far as the fuzzy case is concerned, two approaches based respectively on possibility measures and on Embedding Theorem for fuzzy numbers are described. A case study is also carried out for the sake of illustration. We end up with some concluding remarks along with lines for further development, in this field. === Operations Research === M. Sc. (Operations Research)