Financing - Scheduling Optimization for Construction Projects by using Genetic Algorithms
Investment in a constructed facility represents a cost in
the short term that returns benefits only over the long term use of the
facility. Thus, the costs occur earlier than the benefits, and the owners
of facilities must obtain the capital resources to finance the costs of
construction. A project cannot proceed without an adequate
financing, and the cost of providing an adequate financing can be
quite large. For these reasons, the attention to the project finance is an
important aspect of project management. Finance is also a concern to
the other organizations involved in a project such as the general
contractor and material suppliers. Unless an owner immediately and
completely covers the costs incurred by each participant, these
organizations face financing problems of their own. At a more
general level, the project finance is the only one aspect of the general
problem of corporate finance. If numerous projects are considered
and financed together, then the net cash flow requirements constitute
the corporate financing problem for capital investment. Whether
project finance is performed at the project or at the corporate level
does not alter the basic financing problem .In this paper, we will first
consider facility financing from the owner's perspective, with due
consideration for its interaction with other organizations involved in a
project. Later, we discuss the problems of construction financing
which are crucial to the profitability and solvency of construction
contractors. The objective of this paper is to present the steps utilized
to determine the best combination of minimum project financing.
The proposed model considers financing; schedule and maximum net
area .The proposed model is called Project Financing and Schedule
Integration using Genetic Algorithms "PFSIGA". This model
intended to determine more steps (maximum net area) for any project
with a subproject. An illustrative example will demonstrate the
feature of this technique. The model verification and testing are put
into consideration.
[1] Cui, Q., Hastak, M., Halpin, D. W. 2010. Systems analysis of project
cash flow management strategies. Construction Management and
Economics In print: 1-16.
[2] Senouci, A. B., El-Rayes, K. A. 2009. Time-profit trade-off analysis for
construction projects. Journal of Construction Engineering and
Management 135(8): 718-725.
[3] Elazouni, A. M., Metwally, F. G. 2005. Finance-based scheduling: Tool
to maximize project profit using improved genetic algorithms. Journal of
Construction Engineering and Management 131(4): 400- 412.
[4] Elazouni, A. M., Metwally, F. G. 2007. Expanding finance-based
scheduling to devise overall-optimized project schedules. Journal of
Construction Engineering and Management 133(1): 86-90
[5] Elazouni, A. M. 2009. Heuristic method for multi-project finance-based
scheduling. Construction Management and Economics 27(2): 199-211.
[6] Liu, S.-S., Wang, C.-J. 2008. Resource-constrained construction project
scheduling model for profit maximization considering cash flow.
Automation in Construction 17(8): 966-974
[7] Barbosa, P. S. F., Pimentel, P. R. 2001. A linear programming model for
cash flow management in the Brazilian construction industry.
Construction Management and Economics 19(5): 469-479.
[8] Halpin, D. W., Woodhead, R. W. 1998. Construction management. New
York, NY: John Wiley & Sons.
[9] Garner, D. R., Owen, R. R., Conway, R. P. 1994. The Ernst & Young
guide to financing for growth. New York, NY: John Wiley & Sons
[10] Elazouni, A. M., Metwally, F. G. 2005. Finance-based scheduling: Tool
to maximize project profit using improved genetic algorithms. Journal of
Construction Engineering and Management 131(4): 400- 412
[11] EL-Beltagi E., Hegazy T., and Grierson D. (2005). "Comparison among
five evolutionary-based optimization algorithms" Advanced Engineering
Informatics (19), 43-53.
[12] Goldberg D. E. (1989). "Genetic Algorithm in Search Optimization and
Machine Learning" Addison-Wesley reading, University of Alabama,
U.S.A.
[1] Cui, Q., Hastak, M., Halpin, D. W. 2010. Systems analysis of project
cash flow management strategies. Construction Management and
Economics In print: 1-16.
[2] Senouci, A. B., El-Rayes, K. A. 2009. Time-profit trade-off analysis for
construction projects. Journal of Construction Engineering and
Management 135(8): 718-725.
[3] Elazouni, A. M., Metwally, F. G. 2005. Finance-based scheduling: Tool
to maximize project profit using improved genetic algorithms. Journal of
Construction Engineering and Management 131(4): 400- 412.
[4] Elazouni, A. M., Metwally, F. G. 2007. Expanding finance-based
scheduling to devise overall-optimized project schedules. Journal of
Construction Engineering and Management 133(1): 86-90
[5] Elazouni, A. M. 2009. Heuristic method for multi-project finance-based
scheduling. Construction Management and Economics 27(2): 199-211.
[6] Liu, S.-S., Wang, C.-J. 2008. Resource-constrained construction project
scheduling model for profit maximization considering cash flow.
Automation in Construction 17(8): 966-974
[7] Barbosa, P. S. F., Pimentel, P. R. 2001. A linear programming model for
cash flow management in the Brazilian construction industry.
Construction Management and Economics 19(5): 469-479.
[8] Halpin, D. W., Woodhead, R. W. 1998. Construction management. New
York, NY: John Wiley & Sons.
[9] Garner, D. R., Owen, R. R., Conway, R. P. 1994. The Ernst & Young
guide to financing for growth. New York, NY: John Wiley & Sons
[10] Elazouni, A. M., Metwally, F. G. 2005. Finance-based scheduling: Tool
to maximize project profit using improved genetic algorithms. Journal of
Construction Engineering and Management 131(4): 400- 412
[11] EL-Beltagi E., Hegazy T., and Grierson D. (2005). "Comparison among
five evolutionary-based optimization algorithms" Advanced Engineering
Informatics (19), 43-53.
[12] Goldberg D. E. (1989). "Genetic Algorithm in Search Optimization and
Machine Learning" Addison-Wesley reading, University of Alabama,
U.S.A.
@article{"International Journal of Business, Human and Social Sciences:54069", author = "Hesham Abdel-Khalek and Sherif M. Hafez and Abdel-Hamid M. el-Lakany and Yasser Abuel-Magd", title = "Financing - Scheduling Optimization for Construction Projects by using Genetic Algorithms", abstract = "Investment in a constructed facility represents a cost in
the short term that returns benefits only over the long term use of the
facility. Thus, the costs occur earlier than the benefits, and the owners
of facilities must obtain the capital resources to finance the costs of
construction. A project cannot proceed without an adequate
financing, and the cost of providing an adequate financing can be
quite large. For these reasons, the attention to the project finance is an
important aspect of project management. Finance is also a concern to
the other organizations involved in a project such as the general
contractor and material suppliers. Unless an owner immediately and
completely covers the costs incurred by each participant, these
organizations face financing problems of their own. At a more
general level, the project finance is the only one aspect of the general
problem of corporate finance. If numerous projects are considered
and financed together, then the net cash flow requirements constitute
the corporate financing problem for capital investment. Whether
project finance is performed at the project or at the corporate level
does not alter the basic financing problem .In this paper, we will first
consider facility financing from the owner's perspective, with due
consideration for its interaction with other organizations involved in a
project. Later, we discuss the problems of construction financing
which are crucial to the profitability and solvency of construction
contractors. The objective of this paper is to present the steps utilized
to determine the best combination of minimum project financing.
The proposed model considers financing; schedule and maximum net
area .The proposed model is called Project Financing and Schedule
Integration using Genetic Algorithms "PFSIGA". This model
intended to determine more steps (maximum net area) for any project
with a subproject. An illustrative example will demonstrate the
feature of this technique. The model verification and testing are put
into consideration.", keywords = "Project Management, Large-scale ConstructionProjects, Cash flow, Interest, Investment, Loan, Optimization,Scheduling, Financing and Genetic Algorithms.", volume = "5", number = "11", pages = "1487-9", }