Multi-objective time–cost trade-off in dynamic PERT networks using an interactive approach

2007 ◽  
Vol 180 (3) ◽  
pp. 1186-1200 ◽  
Author(s):  
Amir Azaron ◽  
Reza Tavakkoli-Moghaddam
Keyword(s):  
Time Cost ◽  
Interactive Approach ◽  
Trade Off ◽  
Multi Objective ◽  
Objective Time

scholarly journals Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money

Symmetry ◽  
2021 ◽  
Vol 13 (12) ◽  
pp. 2402
Author(s):  
Omid Kebriyaii ◽  
Ali Heidari ◽  
Mohammad Khalilzadeh ◽  
Jurgita Antucheviciene ◽  
Miroslavas Pavlovskis
Keyword(s):  
Construction Projects ◽  
Metaheuristic Algorithms ◽  
Grey Wolf Optimizer ◽  
Time Cost ◽  
Nsga Ii ◽  
Trade Off ◽  
Time Value Of Money ◽  
Multi Objective ◽  
Time Value ◽  
Value Of Money

Time, cost, and quality have been known as the project iron triangles and substantial factors in construction projects. Several studies have been conducted on time-cost-quality trade-off problems so far, however, none of them has considered the time value of money. In this paper, a multi-objective mathematical programming model is developed for time-cost-quality trade-off scheduling problems in construction projects considering the time value of money, since the time value of money, which is decreased during a long period of time, is a very important matter. Three objective functions of time, cost, and quality are taken into consideration. The cost objective function includes holding cost and negative cash flows. In this model, the net present value (NPV) of negative cash flow is calculated considering the costs of non-renewable (consumable) and renewable resources in each time period of executing activities, which can be mentioned as the other contribution of this study. Then, three metaheuristic algorithms including multi-objective grey wolf optimizer (MOGWO), non-dominated sorting genetic algorithm (NSGA-II), and multi-objective particle swarm optimization (MOPSO) are applied, and their performance is evaluated using six metrics introduced in the literature. Finally, a bridge construction project is considered as a real case study. The findings show that considering the time value of money can prevent cost overrun in projects. Additionally, the results indicate that the MOGWO algorithm outperforms the NSGA-II and MOPSO algorithms.

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.

scholarly journals Developing a Resource Allocation Approach for Resource-Constrained Construction Operation under Multi-Objective Operation

2021 ◽  
Vol 13 (13) ◽  
pp. 7318
Author(s):  
Wei He ◽  
Wenjing Li ◽  
Wei Wang
Keyword(s):  
Resource Allocation ◽  
Energy Consumption ◽  
Limited Resource ◽  
Industrial Plant ◽  
Time Cost ◽  
Multi Objective Optimization ◽  
Trade Off ◽  
Quantum Genetic Algorithm ◽  
Multi Objective ◽  
Arrangement Problem

In the construction industry, it is of great importance for project managers (PM) to consider the resource allocation arrangement problem based on different perspectives. In this situation, the management of resources in construction becomes a challenge. Generally speaking, there are many objectives that need to be optimized in construction that are in conflict with each other, including time, cost, and energy consumption (EC). This paper proposed a multi-objective optimization framework based on the quantum genetic algorithm (QGA) to obtain the best trade-off relationship among these goals. The construction resources allocated in each construction activity would eventually determine its execution time, cost, and EC, and a complexed time-cost-energy consumption trade-off framework of the project is finally generated due to correlations between construction activities. QGA was performed to find the best combination among time, cost, and EC and the optimal scheme of resource arrangement under this state. The construction process is simulated in BIM to check the rationality of this resource allocation mode. An industrial plant office building in China is presented as an example to illustrate the implementation of the proposed model. The results show that the presented method could effectively reduce 7% of cost, 17% of time, and 21% of energy consumption. This developed model is expected to help PMs to solve the problem of multi-objective optimization with limited resource allocation.

scholarly journals Time-Cost-Quality Trade-off Model for Optimal Pile Type Selection Using Discrete Particle Swarm Optimization Algorithm

2019 ◽  
Vol 5 (11) ◽  
pp. 2461-2471
Author(s):  
Hanaa H. Lateef ◽  
Abbas Mohammed Burhan
Keyword(s):  
Decision Making ◽  
Particle Swarm Optimization ◽  
Pso Algorithm ◽  
Pile Foundations ◽  
Time Cost ◽  
Multi Objective Optimization ◽  
Swarm Optimization ◽  
Trade Off ◽  
Multi Objective ◽  
Pile Type

The cost of pile foundations is part of the super structure cost, and it became necessary to reduce this cost by studying the pile types then decision-making in the selection of the optimal pile type in terms of cost and time of production and quality .So The main objective of this study is to solve the time–cost–quality trade-off (TCQT) problem by finding an optimal pile type with the target of "minimizing" cost and time while "maximizing" quality. There are many types In the world of piles but  in this paper, the researcher proposed five pile types, one of them is not a traditional, and   developed a model for the problem and then employed particle swarm optimization (PSO) algorithm, as one of evolutionary algorithms with the help of (Mat lab software), as a tool for decision making problem about choosing the best alternative of the traded piles, and proposes a multi objective optimization model, which aims to optimize the time, cost and quality of the pile types, and assist in selecting the most appropriate pile types. The researcher selected 10 of senior engineers to conduct interviews with them.  And prepared some questions for interviews and open questionnaire. The individuals are selected from private and state sectors each one have 10 years or more experience in pile foundations work. From personal interviews and field survey the research has shown that most of the experts, engineers are not fully aware of new soft wear techniques to helps them in choosing alternatives, despite their belief in the usefulness of using modern technology and software. The Problem is multi objective optimization problem, so after running the PSO algorithm it is usual to have more than one optimal solution, for five proposed pile types, finally the researcher  evaluated and  discussed the output results and  found out that pre-high tension spun (PHC)pile type was the optimal pile type.

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