Multiprocessor system scheduling with precedence and resource constraints using an enhanced ant colony system

Shih Tang Lo; Ruey Maw Chen; Yueh Min Huang; Chung Lun Wu

doi:10.1016/j.eswa.2007.02.022

Multiprocessor system scheduling with precedence and resource constraints using an enhanced ant colony system

Shih Tang Lo, Ruey Maw Chen, Yueh Min Huang, Chung Lun Wu

Department of Engineering Science

Research output: Contribution to journal › Article › peer-review

33 Citations (Scopus)

Abstract

This study presents and evaluates a modified ant colony optimization (ACO) approach for the precedence and resource-constrained multiprocessor scheduling problems. A modified ant colony system is proposed to solve the scheduling problems. A two-dimensional matrix is proposed in this study for assigning jobs on processors, and it has a time-dependency relation structure. The dynamic rule is designed to modify the latest starting time of jobs and hence the heuristic function. In exploration of the search solution space, this investigation proposes a delay solution generation rule to escape the local optimal solution. Simulation results demonstrate that the proposed modified ant colony system algorithm provides an effective and efficient approach for solving multiprocessor system scheduling problems with resource constraints.

Original language	English
Pages (from-to)	2071-2081
Number of pages	11
Journal	Expert Systems With Applications
Volume	34
Issue number	3
DOIs	https://doi.org/10.1016/j.eswa.2007.02.022
Publication status	Published - 2008 Apr

All Science Journal Classification (ASJC) codes

Engineering(all)
Computer Science Applications
Artificial Intelligence

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10.1016/j.eswa.2007.02.022

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title = "Multiprocessor system scheduling with precedence and resource constraints using an enhanced ant colony system",

abstract = "This study presents and evaluates a modified ant colony optimization (ACO) approach for the precedence and resource-constrained multiprocessor scheduling problems. A modified ant colony system is proposed to solve the scheduling problems. A two-dimensional matrix is proposed in this study for assigning jobs on processors, and it has a time-dependency relation structure. The dynamic rule is designed to modify the latest starting time of jobs and hence the heuristic function. In exploration of the search solution space, this investigation proposes a delay solution generation rule to escape the local optimal solution. Simulation results demonstrate that the proposed modified ant colony system algorithm provides an effective and efficient approach for solving multiprocessor system scheduling problems with resource constraints.",

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AU - Lo, Shih Tang

AU - Chen, Ruey Maw

AU - Huang, Yueh Min

AU - Wu, Chung Lun

PY - 2008/4

Y1 - 2008/4

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AB - This study presents and evaluates a modified ant colony optimization (ACO) approach for the precedence and resource-constrained multiprocessor scheduling problems. A modified ant colony system is proposed to solve the scheduling problems. A two-dimensional matrix is proposed in this study for assigning jobs on processors, and it has a time-dependency relation structure. The dynamic rule is designed to modify the latest starting time of jobs and hence the heuristic function. In exploration of the search solution space, this investigation proposes a delay solution generation rule to escape the local optimal solution. Simulation results demonstrate that the proposed modified ant colony system algorithm provides an effective and efficient approach for solving multiprocessor system scheduling problems with resource constraints.

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Multiprocessor system scheduling with precedence and resource constraints using an enhanced ant colony system

Abstract

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