6 research outputs found
The Optimal Set and Optimal Partition Approach to Linear and Quadratic Programming
In this chapter we describe the optimal set approach for sensitivity analysis for LP. We show that optimal partitions and optimal sets remain constant between two consecutive transition-points of the optimal value function. The advantage of using this approach instead of the classical approach (using optimal bases) is shown. Moreover, we present an algorithm to compute the partitions, optimal sets and the optimal value function. This is a new algorithm and uses primal and dual optimal solutions. We also extend some of the results to parametric quadratic programming, and discuss differences and resemblances with the linear programming case
Solving multiobjective mathematical programming problems with fixed and fuzzy coefficients
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 ResearchM. Sc. (Operations Research