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Chemical Reaction Optimization for Solving Resource Constrained Project Scheduling Problem

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Cyber Security and Computer Science (ICONCS 2020)

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Abstract

In this paper, a renowned metaheuristic algorithm named chemical reaction optimization (CRO) is applied to solve the resource constrained project scheduling problem (RCPSP). This work employed chemical reaction optimization to schedule project tasks to minimize makespan concerning resource and precedence constraints. Chemical reaction optimization is a population-based metaheuristic algorithm. CRO is applied to RCPSP by redesigning its basic operators and taking solutions from the search space using priority-based selection to achieve a better result. The proposed algorithm based on CRO is then tested on large benchmark instances and compared with other metaheuristic algorithms. The experimental results have shown that our proposed method provides better results than other states of art algorithms in terms of both the qualities of result and execution time.

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Acknowledgement

This paper is partially funded by Green University of Bangladesh.

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Authors and Affiliations

  1. Green University of Bangladesh, Dhaka, Bangladesh

    Ohiduzzaman Shuvo

  2. Khulna University, Khulna, Bangladesh

    Md Rafiqul Islam

Authors
  1. Ohiduzzaman Shuvo
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  2. Md Rafiqul Islam
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Correspondence to Ohiduzzaman Shuvo .

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Editors and Affiliations

  1. Daffodil International University, Dhaka, Bangladesh

    Touhid Bhuiyan

  2. Daffodil International University, Dhaka, Bangladesh

    Md. Mostafijur Rahman

  3. Daffodil International University, Dhaka, Bangladesh

    Md. Asraf Ali

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Shuvo, O., Islam, M.R. (2020). Chemical Reaction Optimization for Solving Resource Constrained Project Scheduling Problem. In: Bhuiyan, T., Rahman, M.M., Ali, M.A. (eds) Cyber Security and Computer Science. ICONCS 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 325. Springer, Cham. https://doi.org/10.1007/978-3-030-52856-0_13

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  • DOI: https://doi.org/10.1007/978-3-030-52856-0_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-52855-3

  • Online ISBN: 978-3-030-52856-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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