L. K. Fleischer. Faster algorithms for the quickest transshipment problem. SIAM Journal on Optimization, 12:18--35, 2001.  Home/Search   Document Details and Download   Summary   Related Articles   Check

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L. K. Fleischer. Faster algorithms for the quickest transshipment problem. SIAM Journal on Optimization, 12:18--35, 2001.

....interval of time (0; t] for 0 t T . If there is more than one sink, a universally quickest transshipment may not exist, so the universally quickest transshipment problem refers to a dynamic transshipment problem with one sink only. The zero transit time version of this problem is discussed in [2, 6, 10, 13]. Hajek and Ogier [6] describe the first polynomial time algorithm to find a universally quickest transshipment for a dynamic network with all zero transit times. Their algorithm uses n maximum flow computations on the underlying static network. Fleischer [2] improves upon this by describing an ....

....this problem is discussed in [2, 6, 10, 13] Hajek and Ogier [6] describe the first polynomial time algorithm to find a universally quickest transshipment for a dynamic network with all zero transit times. Their algorithm uses n maximum flow computations on the underlying static network. Fleischer [2] improves upon this by describing an algorithm that solves this problem in the same asymptotic 2 time as a preflow push maximum flow algorithm. In this paper, we consider the generalization of the zero transit time, universally maximum flow problem that allows both arc capacities and node ....

L. Fleischer. Faster algorithms for the quickest transshipment problem with zero transit times. In Proceedings of the Ninth Annual ACM/SIAM Symposium on Discrete Algorithms, pages 147--156, 1998. Submitted to SIAM Journal on Optimization. 11

....cost flow computation. Here m is the number of arcs, is the maximum supply or demand, and U is the maximum capacity. When there is only one sink, this problem can be solved in the same asymptotic time as one minimum (convex) cost flow computation. This improves upon the recent algorithm in [5]which solves the quickest transshipment problem (the above mentioned problem without costs) on k terminals using k log T maximum flow computations and k minimum cost flow computations. Our solutions start with a stationary fractional flow, as described in [5] and use rounding to transform ....

....upon the recent algorithm in [5]which solves the quickest transshipment problem (the above mentioned problem without costs) on k terminals using k log T maximum flow computations and k minimum cost flow computations. Our solutions start with a stationary fractional flow, as described in [5], and use rounding to transform this into an integral flow. The rounding procedure takes O(n) time. email: lisa ieor.columbia.edu. Department of Industrial Engineering and Operations Research, Columbia University. y email: jorlin mit.edu. Sloan School of Management, Massachusetts Institute of ....

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L. Fleischer. Faster algorithms for the quickest transshipment problem with zero transit times. In Proceedings of the Ninth Annual ACM/SIAM Symposium on Discrete Algorithms, pages 147--156, 1998. Submitted to SIAM Journal on Optimization.

....on the flow rates, and infinite node storage, and construct an provably polynomial time algorithm to empty the network of excess supply in minimum time. Ogier [17] generalizes this result to solve the problem where the edge and storage capacities are piecewise constant functions of time. Fleischer [6] describes a faster algorithm to solve the Hajek Ogier problem and some also presents algorithms for some related dynamic flow problems. Fleischer [7] describes a faster algorithm to solve Ogier s problem. In this paper, we extend the polynomial algorithms developed for the discrete time model to ....

L. Fleischer. Faster algorithms for the quickest transshipment problem with zero transit times. In Proceedings of the Ninth Annual ACM/SIAM Symposium on Discrete Algorithms, pages 147--156, 1998. Submitted to SIAM Journal on Optimization.

....this problem can be solved using at most log T maximum flow computations and one minimum (convex) cost flow computation. When there is only one sink, this problem can be solved in the same asymptotic time as one minimum (convex) cost flow computation. This improves upon the recent algorithm in [5] which solves the quickest transshipment problem (the above mentioned problem without costs) on k terminals using k log T maximum flow computations and k minimum cost flow computations. Our solutions start with a stationary fractional flow, as described in [5] and use rounding to transform this ....

....improves upon the recent algorithm in [5] which solves the quickest transshipment problem (the above mentioned problem without costs) on k terminals using k log T maximum flow computations and k minimum cost flow computations. Our solutions start with a stationary fractional flow, as described in [5], and use rounding to transform this into an integral flow. The rounding procedure takes O(n) time. The above problems assume that flow is instantaneous but limited by bounds on per unit time capacities. The related problem with linear costs and non zero transit times is NP hard. The problem with ....

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L. Fleischer. Faster algorithms for the quickest transshipment problem. In Proceedings of the Ninth Annual ACM/SIAM Symposium on Discrete Algorithms, 1998. To appear.

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Fleischer, L., Faster algorithms for the quickest transshipment problem with zero transit times, to appear in SIAM Journal on Optimization.

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