scholarly journals The Effect of Price Discount on Time-Cost Trade-off Problem Using Genetic Algorithm

Engineering ◽  
2009 ◽  
Vol 01 (01) ◽  
pp. 33-40 ◽  
Author(s):  
Hadi Mokhtari ◽  
Abdollah Aghaie
Keyword(s):  
Genetic Algorithm ◽  
Time Cost ◽  
Price Discount ◽  
Trade Off

A TIME-COST TRADE-OFF MODEL WITH RESOURCE CONSIDERATION USING GENETIC ALGORITHM

1997 ◽  
Vol 14 (4) ◽  
pp. 291-311 ◽  
Author(s):  
D. K. H. CHUA ◽  
W. T. CHAN ◽  
K. GOVINDAN
Keyword(s):  
Genetic Algorithm ◽  
Time Cost ◽  
Trade Off

Incentive genetic algorithm based time–cost trade-off analysis across a build–operate–transfer project concession period

2011 ◽  
Vol 38 (2) ◽  
pp. 166-174 ◽  
Author(s):  
Hongxian Li ◽  
Mohamed Al-Hussein ◽  
Zhen Lei
Keyword(s):  
Genetic Algorithm ◽  
Sensitivity Analysis ◽  
Genetic Algorithms ◽  
Construction Cost ◽  
Methodological Framework ◽  
Time Cost ◽  
Trade Off ◽  
Operation Period ◽  
Concession Period ◽  
New Infrastructure

The build–operate–transfer (BOT) scheme is widely applied to finance new infrastructure projects with private sector (concessionaire) participation. For a predetermined concession period (CP), assuming that CP consists of the construction duration (CD) and the concession operation period (OP), different construction durations result in different profits for the concessionaire. Meanwhile, according to the time–cost trade-off (TCT) principle, shortening the CD increases the construction cost; shortening the CD also prolongs the OP, which could increase the total benefit of BOT projects. Hence, how to arrange construction reasonably to maximize the whole profit is a key issue for a concessionary. This paper proposes a methodological framework including optimization, sensitivity analysis, and improved (incentive) genetic algorithms (GA) for BOT projects. Through the proposed methodological framework, the reasonable construction duration of a BOT project can be obtained. A numerical example is used to verify the proposed methodology.

scholarly journals Fuzzy Multi-Objective Genetic Algorithm Based Resource Constrained Time-Cost Trade-Off Model under Uncertain Environment

2021 ◽  
Vol 9 (8) ◽  
pp. 1126-1133
Author(s):  
Ashish Sharma
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Construction Projects ◽  
Risk Level ◽  
Pareto Optimal ◽  
Time Cost ◽  
Trade Off ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Abstract: In every construction project, the time and cost are the two most important objectives/factors to be considered. Clients and contractors should strive to optimize the project time and cost to maximize the return. Resources are also one of the major constraints of the construction projects. In recent years, several studies have been conducted to optimize the time and cost of project under constraint conditions of resources. Since most studies assume the time and cost as deterministic parameters, uncertainties should be considered in estimating the time and cost of the project's activities when minimizing the duration and cost of the project. For this purpose, this paper embeds the fuzzy logic to handle the uncertainties in estimating the time and cost. Besides, the multi-objective genetic algorithm (MOGA) is used to develop the resourceconstrained time-cost trade-off model. Alpha-cut approach is utilized to define the accepted risk level of decision maker. The efficiency of the proposed model is demonstrated through solvinga case study project of highway construction. The results of case study project provide a set of Pareto-optimal solutions. The developed model encourage the decision making process by choosing specified risk levels and utilizing the related Pareto-front. Keywords: Construction projects, time-cost trade-off, uncertainties, fuzzy logic, MOGA,Pareto-optimal solution.

scholarly journals A new approach to solving the time-cost trade-off problem based on the genetic algorithm and fuzzy theory

2012 ◽  
Vol 1 (3) ◽  
pp. 238
Author(s):  
Nasser Shahsavari Pour ◽  
Arman Ghamginzadeh ◽  
Mansoor Pour Kheradmand
Keyword(s):  
Genetic Algorithm ◽  
Taguchi Method ◽  
Fuzzy Theory ◽  
New Method ◽  
Time Cost ◽  
New Approach ◽  
Trade Off ◽  
Uncertainty Condition ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

Time and cost are two important and controllable objectives in project structures which are considerably dependent on each other. Recently, beneficiaries demands for cost and time reduction in completing a project have been increased. This study proposes a new method for time-cost trade off problem (TCTP) in uncertainty condition. To solve the model a multi objective genetic algorithm has been integrated with fuzzy theory. Efficiency of this algorithm is demonstrated through an existing case example from the literature. Finally to make the algorithm more efficient the existing parameters in the model have been set through Taguchi method.

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