Abstract
As we have seen in Ch. II1, the simplex procedure can be described as a systematic method of examining the set of basic feasible solutions, starting in an arbitrary initial basis of m variables (activities) where m is the number of linear restrictions. If the initial basic solution does not satisfy the simplex criterion, we move to a neighbouring basis by replacing one of the basic variables, and so forth, until a basic feasible solution is attained in which all of the simplex coefficients are non-positive (in a minimization problem, non-negative). By the Fundamental Theorem, such a solution will be an optimal solution.
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© 1974 Springer-Verlag/Wien
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Danø, S. (1974). Computational Procedures for Solving Linear Programming Problems. In: Linear Programming in Industry. Springer, Vienna. https://doi.org/10.1007/978-3-7091-8346-5_5
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DOI: https://doi.org/10.1007/978-3-7091-8346-5_5
Publisher Name: Springer, Vienna
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