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A new non-monotonic infeasible simplex-type algorithm for Linear Programming
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DOI：10.7717/peerj-cs.265.png)
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Abstract
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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.
Keywords:
Linear programming
Simplex-type
Interior point method
Exterior point
Non-monotonic
Infeasible
Mathematical programming
Optimization
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