LP-type problem

Abstract: The existence of polynomial-time algorithms for the solution of parity games is a major open problem. The fastest known algorithms for the problem are randomized algorithms that run in subexponential time. These algorithms are all ultimately based on the randomized subexponential simplex algorithms of Kalai and of Matousek, Sharir, and Welzl. Randomness seems to play an essential role in these algorithms. We use a completely different, and elementary, approach to obtain a deterministic subexponential algorithm for the solution of parity games. The new algorithm, like the existing randomized subexponential algorithms, uses only polynomial space, and it is almost as fast as the randomized subexponential algorithms mentioned above.

Abstract: We show that with recently developed derandomization techniques, one can convert Clarkson’s randomized algorithm for linear programming in fixed dimension into a linear-time deterministic algorithm. The constant of proportionality is dO Žd ., which is better than those for previously known algorithms. We show that the algorithm works in a fairly general abstract setting, which allows us to solve various other problems, e.g., computing the minimum-volume ellipsoid enclosing a set of n points and finding the maximum volume ellipsoid in the intersection of n halfspaces. Q 1996 Academic Press, Inc.

Abstract: Three papers were published in 1992, each providing a combinatorial, randomized algorithm solving linear programming in subexponential expected time. Bounds on independent algorithms were proven, one by Kalai, and the other by Matousek, Sharir, and Welzl. Results by Gartner combined techniques from these papers to solve a much more general optimization problem in similar time bounds.Although the algorithms by Kalai and Sharir-Welzl seem remarkably different in style and evolution, this paper demonstrates that one of the variants of Kalai's algorithm is identical (although dual) to the algorithm of Sharir-Welzl. Also the implication of Gartner's framework on future improvements is examined more carefully.