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Finance-based CPM/LOB scheduling of projects with repetitive non-serial activities

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  • Mohammed Mubashir Ali
  • Ashraf Elazouni

Abstract

Projects of repetitive non-serial activities constitute a major category of construction projects which can be scheduled more conveniently using the line of balance (LOB) technique. Generally, scheduling activities such that the expenditures are always in balance with the available cash is a must to devise financially feasible schedules. The objective is to integrate a CPM/LOB model for a project of repetitive non-serial activities with a cash flow model and utilize the integrated model to devise financially feasible schedules. The genetic algorithms (GAs) technique is employed to maximize the profit at the end of the project under the constraints of available cash. The optimization of the integrated models was demonstrated using an example project of 15 activities carried out at five units. The CPM/LOB model was validated against the results of a dynamic programming model in the literature and further by conducting a sensitivity analysis of the results of the integrated model. Finally, the model offers an effective financial planning tool for projects of repetitive non-serial activities.

Suggested Citation

  • Mohammed Mubashir Ali & Ashraf Elazouni, 2009. "Finance-based CPM/LOB scheduling of projects with repetitive non-serial activities," Construction Management and Economics, Taylor & Francis Journals, vol. 27(9), pages 839-856.
    • Handle: RePEc:taf:conmgt:v:27:y:2009:i:9:p:839-856
    DOI: 10.1080/01446190903191764
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    Cited by:

    1. Ionica Oncioiu & Sorinel Căpuşneanu & Dan Ioan Topor & Ana Maria Ifrim & Ramona Camelia Silvestru & Monica Ioana Toader, 2021. "Improving Business Processes in a Construction Project and Increasing Performance by Using Target Costing," SAGE Open, , vol. 11(1), pages 21582440219, February.
    2. Yuvraj Gajpal & Ashraf Elazouni, 2015. "Enhanced heuristic for finance-based scheduling of construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 33(7), pages 531-553, July.
    3. Goodell, John W. & Kumar, Satish & Lim, Weng Marc & Pattnaik, Debidutta, 2021. "Artificial intelligence and machine learning in finance: Identifying foundations, themes, and research clusters from bibliometric analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 32(C).

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