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New Aspects in Time-Cost Tradeoff Analysis
This paper presents a linear programming model for solution of the time-cost tradeoff problem. Although several analytical models have been developed for time-cost optimization (TCO), many of them mainly focused on projects where the contract duration is fixed. The optimization objective is therefore restricted to identify the minimum total cost only. Another group has primarily focused on project duration minimization. The model presented here considers scheduling characteristics that were ignored in prior research. In the new formulation, variability of funding and uncertainty of project duration are considered together. A chance-constrained programming is used to incorporate the variability of funding, which is quantified by the coefficient of variation. Financial feasibility is expressed as a stochastic constraint, which is transformed into a deterministic equivalent at a prespecified confidence level. Also, project duration uncertainty is incorporated into the model by applying the program evaluation and review technique (PERT) in scheduling and then the uncertainty is quantified by the coefficient of variation at a prespecified confidence level. A system of an objective function, which is minimizing direct cost, and the group of constraints are solved using the Lindo 6.1 software. Two examples are conducted to demonstrate the model’s performance and its contributions. Four scenarios were adopted in solving the example problems to reflect the effect of each on funding variability and time uncertainty of project cost and duration. The results revealed that with a 95% confidence level, 10% variability in funding versus omitting it, would increase direct cost by approximately 20% for a prespecified project deadline. Also, 10% variability in time versus omitting it would increase duration in the range of approximately 16.5 to 30% for prespecified direct cost. On the other hand, considering 10% variability in funding and time would increase direct cost by more than 25% for a prespecified project deadline. At the same time, an increase in project duration of more than 30% will occur for a prespecified direct cost.
New Aspects in Time-Cost Tradeoff Analysis
This paper presents a linear programming model for solution of the time-cost tradeoff problem. Although several analytical models have been developed for time-cost optimization (TCO), many of them mainly focused on projects where the contract duration is fixed. The optimization objective is therefore restricted to identify the minimum total cost only. Another group has primarily focused on project duration minimization. The model presented here considers scheduling characteristics that were ignored in prior research. In the new formulation, variability of funding and uncertainty of project duration are considered together. A chance-constrained programming is used to incorporate the variability of funding, which is quantified by the coefficient of variation. Financial feasibility is expressed as a stochastic constraint, which is transformed into a deterministic equivalent at a prespecified confidence level. Also, project duration uncertainty is incorporated into the model by applying the program evaluation and review technique (PERT) in scheduling and then the uncertainty is quantified by the coefficient of variation at a prespecified confidence level. A system of an objective function, which is minimizing direct cost, and the group of constraints are solved using the Lindo 6.1 software. Two examples are conducted to demonstrate the model’s performance and its contributions. Four scenarios were adopted in solving the example problems to reflect the effect of each on funding variability and time uncertainty of project cost and duration. The results revealed that with a 95% confidence level, 10% variability in funding versus omitting it, would increase direct cost by approximately 20% for a prespecified project deadline. Also, 10% variability in time versus omitting it would increase duration in the range of approximately 16.5 to 30% for prespecified direct cost. On the other hand, considering 10% variability in funding and time would increase direct cost by more than 25% for a prespecified project deadline. At the same time, an increase in project duration of more than 30% will occur for a prespecified direct cost.
New Aspects in Time-Cost Tradeoff Analysis
El-Kholy, A. M. (author)
2013-09-06
Article (Journal)
Electronic Resource
Unknown
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