Citation
A biased random-key genetic algorithm for scheduling divisible loads. In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic, pages 570-578, 2015.
Paper
Abstract
A divisible load is an amount W ? 0 of computational work that can be arbitrarily divided into chunks and distributed among a set P of worker processors to be processed in parallel. The Divisible Load Scheduling Problem consists in (a) selecting a subset of active workers, (b) de?ning the order in which the chunks will be transmitted to each of them, and (c) deciding the amount of load ?i that will be transmitted to each active worker, so as to minimize the makespan, i.e., the total elapsed time since the master began to send data to the ?rst worker, until the last worker stops its computations. We propose a biased random-key genetic algorithm for solving the divisible load scheduling problem. Computational results show that the genetic algorithm outperforms the best heuristic in the literature.
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Bibtex
@INPROCEEDINGS{2015-570-578-P, author = {J.S. Brandao and T.F. Noronha and M.G.C. Resende and C. C. Ribeiro},
title = {A biased random-key genetic algorithm for scheduling divisible loads},
booktitle = {In proceedings of the 7th Multidisciplinary International Conference on Scheduling : Theory and Applications (MISTA 2015), 25 - 28 Aug 2015, Prague, Czech Republic},
year = {2015},
editor = {Z. Hanzalek and G. Kendall and B. McCollum and P. Sucha},
pages = {570--578},
note = {Paper},
abstract = {A divisible load is an amount W ? 0 of computational work that can be arbitrarily divided into chunks and distributed among a set P of worker processors to be processed in parallel. The Divisible Load Scheduling Problem consists in (a) selecting a subset of active workers, (b) de?ning the order in which the chunks will be transmitted to each of them, and (c) deciding the amount of load ?i that will be transmitted to each active worker, so as to minimize the makespan, i.e., the total elapsed time since the master began to send data to the ?rst worker, until the last worker stops its computations. We propose a biased random-key genetic algorithm for solving the divisible load scheduling problem. Computational results show that the genetic algorithm outperforms the best heuristic in the literature.},
owner = {Graham},
timestamp = {2017.01.16},
webpdf = {2015-570-578-P.pdf} }