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A review of methods and algorithms for optimizing construction scheduling

Author

Listed:
  • J Zhou

    (Curtin University, Perth, Australia)

  • P E D Love

    (Curtin University, Perth, Australia)

  • X Wang

    (Curtin University, Perth, Australia)

  • K L Teo

    (Curtin University, Perth, Australia)

  • Z Irani

    (Brunel University, Middlesex, UK)

Abstract

Optimizing construction project scheduling has received a considerable amount of attention over the past 20 years. As a result, a plethora of methods and algorithms have been developed to address specific scenarios or problems. A review of the methods and algorithms that have been developed to examine the area of construction schedule optimization (CSO) is undertaken. The developed algorithms for solving the CSO problem can be classified into three methods: mathematical, heuristic and metaheuristic. The application of these methods to various scheduling problems is discussed and implications for future research are identified.

Suggested Citation

  • J Zhou & P E D Love & X Wang & K L Teo & Z Irani, 2013. "A review of methods and algorithms for optimizing construction scheduling," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(8), pages 1091-1105, August.
    • Handle: RePEc:pal:jorsoc:v:64:y:2013:i:8:p:1091-1105
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    Citations

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    Cited by:

    1. Pamela C. Nolz, 2021. "Optimizing construction schedules and material deliveries in city logistics: a case study from the building industry," Flexible Services and Manufacturing Journal, Springer, vol. 33(3), pages 846-878, September.
    2. Jerzy Rosłon & Mariola Książek-Nowak & Paweł Nowak, 2020. "Schedules Optimization with the Use of Value Engineering and NPV Maximization," Sustainability, MDPI, vol. 12(18), pages 1-20, September.
    3. Shahryar Monghasemi & Mohammad Reza Nikoo & Mohammad Ali Khaksar Fasaee & Jan Adamowski, 2017. "A Hybrid of Genetic Algorithm and Evidential Reasoning for Optimal Design of Project Scheduling: A Systematic Negotiation Framework for Multiple Decision-Makers," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 16(02), pages 389-420, March.

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