Insights on Linear Programming and Pivoting Rules in Optimization
Linear programming involves maximizing a linear objective function within a set of linear constraints to find the optimal point in a polytope. The simplex algorithm, introduced by Dantzig in 1947, navigates through vertices to reach the optimal solution. Deterministic and randomized pivoting rules,
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A Unified Continuous Greedy Algorithm for Submodular Maximization
The paper discusses a unified continuous greedy algorithm for submodular maximization, exploring properties of set functions, submodular functions in combinatorics, polytope constraints, relaxation techniques, and the continuous greedy algorithm. It covers definitions, importance of submodularity, a
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Facts and Insights on s-t Path TSP Polytope
Explore the intricacies of the s-t Path TSP Polytope, including discussions on optimization, integer points, and the challenges associated with achieving a ratio of 5/3 in certain scenarios.
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