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A new non-monotonic infeasible simplex-type algorithm for Linear Programming
Charalampos P Triantafyllidis1, Nikolaos Samaras2
1Computational Biology & Integrative Genomics, Department of Oncology, Medical Sciences Division, University of Oxford, Oxford, United Kingdom.
Abstract:
This paper presents a new simplex-type algorithm for Linear Programming with the following two main characteristics: (i) the algorithm computes basic solutions which are neither primal or dual feasible, nor monotonically improving and (ii) the sequence of these basic solutions is connected with a sequence of monotonically improving interior points to construct a feasible direction at each iteration. We compare the proposed algorithm with the state-of-the-art commercial CPLEX and Gurobi Primal-Simplex optimizers on a collection of 93 well known benchmarks. The results are promising, showing that the new algorithm competes versus the state-of-the-art solvers in the total number of iterations required to converge.
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