Tackling the Grid Job Planning and Resource Allocation Problem Using a Hybrid Evolutionary Algorithm

Autor:	Wilfried Jakob, Karl-Uwe Stucky, Wolfgang Süß, Alexander Quinte
Rok vydání:	2008
Předmět:	Rate-monotonic scheduling Mathematical optimization Job shop scheduling Computer science Evolutionary algorithm Resource allocation Flow shop scheduling Grid Heuristics Fair-share scheduling
Zdroj:	Parallel Processing and Applied Mathematics ISBN: 9783540681052 PPAM
DOI:	10.1007/978-3-540-68111-3_61
Popis:	This paper presents results of new experiments with the Global Optimising Resource Broker and Allocator GORBA for grid systems. The scheduling algorithm is based on the Evolutionary Algorithm GLEAM (General Learning Evolutionary Algorithm and Method) and several heuristics. The task of planning grid resource allocation is compared to pure NP-complete job shop scheduling and it is shown in which way it is of greater complexity. Two different gene models and two repair methods are described in detail and assessed by the experimental results. Based on the analysis of the experimental results, directions of further work and improvements will be outlined.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::fe67c4462c115fc43929bcc55ce41d76 https://doi.org/10.1007/978-3-540-68111-3_61 Zobrazit plný text záznamu