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An Ant Colony-Based Optimization Model for Resource-Leveling Problem

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Advances in Construction Management

Part of the book series: Lecture Notes in Civil Engineering ((LNCE,volume 191))

Abstract

Resource leveling, a resource management technique, plays an important role in developing a realistic schedule, aims to maintain a uniform resource profile, and avoids construction delays. Many researchers in the past have tried solving resource-leveling problems (RLPs) using various numerical, heuristic, metaheuristic approaches. RLP is a classic example of a combinatorial problem. It can be solved using a metaheuristic approach to obtain the optimal or near-global optimal solution. This study aims to solve RLP using ant colony optimization (ACO), a metaheuristic approach. MATLAB 2019 is used to implement the ACO model. A real-time project is used in this study to verify the efficiency of the proposed model. The results obtained from the ACO model are near-global optimum solutions that eliminate premature convergence.

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Author information

Authors and Affiliations

  1. Department of Civil Engineering, SRM Institute of Science and Technology, Chengalpattu District, Kattankuluthur, Tamil Nadu, 603203, India

    Asha Duraiswamy & Gopinath Selvam

Authors
  1. Asha Duraiswamy
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  2. Gopinath Selvam
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Corresponding author

Correspondence to Asha Duraiswamy .

Editor information

Editors and Affiliations

  1. IIC University of Technology, Phnom Penh, Cambodia

    Lee Yee Loon

  2. Indian Institute of Technology Ropar, Rupnagar, Punjab, India

    Muthulingam Subramaniyan

  3. SRM Institute of Science and Technology, Chennai, Tamil Nadu, India

    K. Gunasekaran

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Duraiswamy, A., Selvam, G. (2022). An Ant Colony-Based Optimization Model for Resource-Leveling Problem. In: Loon, L.Y., Subramaniyan, M., Gunasekaran, K. (eds) Advances in Construction Management. Lecture Notes in Civil Engineering, vol 191. Springer, Singapore. https://doi.org/10.1007/978-981-16-5839-6_29

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  • DOI: https://doi.org/10.1007/978-981-16-5839-6_29

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-5838-9

  • Online ISBN: 978-981-16-5839-6

  • eBook Packages: EngineeringEngineering (R0)

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