Introduction -- Geometry of the Feasible Region -- Simplex Method -- Duality principle and dual simplex method -- Implementation of the Simplex Method -- Sensitivity Analysis and Parametric LP -- Variants of the Simplex Method -- Decomposition Method -- Interior Point Method -- Integer Linear Programming (ILP) -- Pivot Rule -- Dual Pivot Rule -- Simplex Phase-I Method -- Dual Simplex Phase-l Method -- Reduced Simplex Method -- Improved Reduced Simplex Method -- D-Reduced Simplex Method -- Criss-Cross Simplex Method -- Generalizing Reduced Simplex Method -- Deficient-Basis Method -- Dual Deficient-Basis Method -- Face Method -- Dual Face Method -- Pivotal interior-point Method -- Special Topics -- Appendix -- References.

With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to conventional topics, such as the simplex method, duality, and interior-point methods, all deduced in a fresh and clear manner, it introduces the state of the art by highlighting brand-new and advanced results, including efficient pivot rules, Phase-I approaches, reduced simplex methods, deficient-basis methods, face methods, and pivotal interior-point methods. In particular, it covers the determination of the optimal solution set, feasible-point simplex method, decomposition principle for solving large-scale problems, controlled-branch method based on generalized reduced simplex framework for solving integer LP problems.