A primal simplex algorithm that solves the maximum flow problem in at most nm pivots and o(n2m) time
Mathematical Programming: Series A and B
Hyperbolic 0-1 programming and query optimization in information retrieval
Mathematical Programming: Series A and B
The scaling network simplex algorithm
Operations Research - Supplement
Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
A genuinely polynomial primal simplex algorithm for the assignment problem
Discrete Applied Mathematics
An algorithm for fractional assignment problems
Discrete Applied Mathematics - Special issue: Fifth Franco-Japanese Days, Kyoto, October 1992
A polynomial time primal network simplex algorithm for minimum cost flows
Mathematical Programming: Series A and B
A new pivot selection rule for the network simplex algorithm
Mathematical Programming: Series A and B
A network simplex algorithm with O(n) consecutive degenerate pivots
Operations Research Letters
Model for assigning roles automatically in egovernment virtual organizations
Expert Systems with Applications: An International Journal
Determining Type II sensitivity ranges of the fractional assignment problem
Operations Research Letters
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In this paper we show that the complexity of the simplex method for the linear fractional assignment problem (LFAP) is strongly polynomial. Although LFAP can be solved in polynomial time using various algorithms such as Newton's method or binary search, no polynomial time bound for the simplex method for LFAP is known.