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Using Artificial Bee Colony to Solve Stochastic Resource Constrained Project Scheduling Problem

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Advances in Swarm Intelligence (ICSI 2011)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6728))

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Abstract

Resource constrained project scheduling (RCPSP) is one of the most crucial problems in project problem. The aim of RCPSP, which is NP-hard, is to minimize the project duration. Sometimes the activity durations are not known in advance and are random variables. These problems are called stochastic resource constrained project scheduling problems or stochastic RCPSP. Various algorithms such as genetic algorithm and GRASP have been applied on stochastic RCPSP. Bee algorithm is a metaheuristic based on the intelligent behavior of honey bee swarms. The goal of this study is adopting the artificial bee colony (ABC) algorithm to solve stochastic RCPSP and investigating its performance on the stochastic RCPSP. Simulation results show that proposed algorithm is an effective method for solving the stochastic resource constrained project scheduling problem. With regard to the problems with high distribution variability, the ABC algorithm is more effective than the other algorithms in the literature.

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Author information

Authors and Affiliations

  1. Department of Mathematics, College of Science, Shiraz University, Shiraz, Iran

    Amin Tahooneh

  2. Department of Computer Science and Engineering, Shiraz University, Shiraz, Iran

    Koorush Ziarati

Authors
  1. Amin Tahooneh
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  2. Koorush Ziarati
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Editor information

Editors and Affiliations

  1. Key Laboratory of Machine Perception, Department of Machine Intelligence, School of Electronics Engineering and Computer Science, Peking University, 100871, Beijing, China

    Ying Tan

  2. Department of Electrical and Electronic Engineering, Xi’an Jiaotong-Liverpool University, 215123, Suzhou, China

    Yuhui Shi

  3. Automation College, Chongqing University, 400030, Chongqing, China

    Yi Chai

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, P.R. China

    Guoyin Wang

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© 2011 Springer-Verlag Berlin Heidelberg

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Tahooneh, A., Ziarati, K. (2011). Using Artificial Bee Colony to Solve Stochastic Resource Constrained Project Scheduling Problem. In: Tan, Y., Shi, Y., Chai, Y., Wang, G. (eds) Advances in Swarm Intelligence. ICSI 2011. Lecture Notes in Computer Science, vol 6728. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21515-5_35

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  • DOI: https://doi.org/10.1007/978-3-642-21515-5_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21514-8

  • Online ISBN: 978-3-642-21515-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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