Revised Dual Simplex Algorithm

Part of the Springer Optimization and Its Applications book series (SOIA, volume 127)


In Section  2.6, we presented the basic duality concepts. This chapter extends these concepts and presents the dual simplex algorithm. The dual simplex algorithm is an attractive alternative for solving linear programming problems (LPs). The dual simplex algorithm is very efficient on many types of problems and is especially useful in integer linear programming. This chapter presents the revised dual simplex algorithm. Numerical examples are presented in order for the reader to understand better the algorithm. Furthermore, an implementation of the algorithm in MATLAB is presented. The implementation is modular allowing the user to select which scaling technique and basis update method will use in order to solve LPs. Finally, a computational study over benchmark LPs and randomly generated sparse LPs is performed in order to compare the efficiency of the proposed implementation with the revised primal simplex algorithm presented in Chapter  8

Supplementary material (6 kb)
chapter 9 (Zip 6 kb)


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Applied InformaticsUniversity of MacedoniaThessalonikiGreece

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