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- W2048039662 abstract "In this paper, we combine the techniques of approximation, parallelism, and randomization to solve the traveling salesman problem, one of the most celebrated problems in computer science. We show that there is an EREW PRAM algorithm A 1 such that A 1(l) ≤ 2 OPT(l) for all TSP instances l, where A 1(l) is the length of the tour produced by A 1, and OPT(l) is the length of an optimum tour. The algorithm has time complexity O(log2 n), and uses O(n 2) processors. There is a similar CREW PRAM algorithm A 2 that uses O(n 2/log2 n) processors. Furthermore, there is a Monte Carlo CREW PRAM algorithm A 3 which, for all TSP instances l, finds a traveling salesman lour such that A 3(l) ≤ 1.5OPT(l) with probability at least 1 − (1/2 k ), where k is any large integer. The randomized algorithm has time complexity O(log2 n), and uses O(n 5.5 L) processors, where L is the length of the interval which contains all distances in l. We also show that there is a Las Vegas CREW PRAM algorithm A 4 which, for all TSP instances l..." @default.
- W2048039662 created "2016-06-24" @default.
- W2048039662 creator A5087894632 @default.
- W2048039662 date "1997-01-01" @default.
- W2048039662 modified "2023-10-04" @default.
- W2048039662 title "SOLVING THE TRAVELING SALESMAN PROBLEM USING EFFICIENT RANDOMIZED PARALLEL APPROXIMATION ALGORITHMS" @default.
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- W2048039662 doi "https://doi.org/10.1080/10637199708915622" @default.
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