The resource allocation model for multi-process instances based on particle swarm optimization

Weidong Zhao (), Qingfeng Zeng (), Guangjian Zheng () and Liu Yang ()
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Weidong Zhao: Fudan University
Qingfeng Zeng: Shanghai University of Finance & Economics
Guangjian Zheng: Fudan University
Liu Yang: Fudan University

Information Systems Frontiers, 2017, vol. 19, issue 5, No 7, 1057-1066

Abstract: Abstract Resource allocation in process management focuses on how to maximize process performance via proper resource allocation since the quality of resource allocation determines process outcome. In order to improve resource allocation, this paper proposes a resource allocation method, which is based on the improved hybrid particle swarm optimization (PSO) in the multi-process instance environment. Meanwhile, a new resource allocation model is put forward, which can optimize the resource allocation problem reasonably. Furthermore, some improvements are made to streamline the effectiveness of the method, so as to enhance resource scheduling results. In the end, experiments are conducted to demonstrate the effectiveness of the proposed method.

Keywords: Particle swarm optimization; Genetic algorithm; Resource allocation model; Multi-process; Update mechanism (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1007/s10796-017-9743-5

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