The most-obtuse-angle row pivot rule for achieving dual feasibility: a computational study

Article Abstract:

The most-obtuse-angle row pivot rule for achieving dual feasibility has been found to outperform the MINOS 5.3 when full pricing is applied. A computational study of pivot rules is used to achieve dual feasibility in linear programming. The rule was tested by implementing a two-phase dual simplex algorithm with the rule being used as row selection requirements for phase 1. The algorithm was then implemented on FORTRAN 77 modules and tested on a set of NETLIB standard linear programming models.

Author: Ping-Qi Pan

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A heuristic to minimax absolute regret for linear programs with interval objective function coefficients

Article Abstract:

A heuristic was proposed to obtain minimax regret solution for linear programs with interval objective function coefficients. The heuristic, when utilized as a stand-alone procedure for a candidate maximum regret problem, was able to derive solutions that are within 5% of optimal on average. Such solutions are comparable to those obtained using the exact method. Because of the heuristic's ability to address larger problems, the usefulness of the minimax regret criterion is extended.

Author: Laguna, Manuel, Mausser, Helmut E.
Algorithms

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On design of a survivable network architecture for a dynamic routing: optimal solution strategy and an efficient heuristic

Article Abstract:

A heuristic was developed to establish a protection network for two link failures or overloads. The heuristic, which was created with the use of the Gomory and Hu procedure, entails modification and synthesizing a maximum spanning tree. Simulation results show that it is O(n6) faster than an optimal model which is non-simultaneous multi-commodity problem. The results also show that it is almost optimal for problems with up to 40 nodes.

Author: Wirth, Andrew, Ouveysi, Iradj

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Subjects list: Operations research, Research, Management science, Analysis, Linear programming, Heuristic, Heuristics (Psychology)
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