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The Optimal Set and Optimal Partition Approach to Linear and Quadratic Programming

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Advances in Sensitivity Analysis and Parametic Programming

Abstract

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.

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Berkelaar, A.B., Roos, K., Terlaky, T. (1997). The Optimal Set and Optimal Partition Approach to Linear and Quadratic Programming. In: Gal, T., Greenberg, H.J. (eds) Advances in Sensitivity Analysis and Parametic Programming. International Series in Operations Research & Management Science, vol 6. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6103-3_6

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  • DOI: https://doi.org/10.1007/978-1-4615-6103-3_6

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-7796-2

  • Online ISBN: 978-1-4615-6103-3

  • eBook Packages: Springer Book Archive

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