A GA-based fuzzy optimal model for time-cost trade-off in a project with resources consideration

Parveen, Sultana; Saha, Surajit

doi:10.1504/ijise.2013.056094

Cited by 9 publications

(13 citation statements)

References 31 publications

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“…Parveen and S. K. Saha researched the techniques of solving time-cost trade-off problem with genetic algorithms based on modified adaptive weights approach, but determining proper values for these weights is rather complex issue (Parveen & Saha, 2012). Project stakeholders often can't prefer any of criterion functions, therefore, using that model with equal weights is just unwarranted.…”

Section: Discussionmentioning

confidence: 99%

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Genetic Algorithm of Network Graph Multi-Objective Optimization as an Instrument of Project Monitoring

Prokopyev¹

2014

ASS

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Proper tracking of progress remains a vital part of modern project management, defining prospects of successful implementation of planned tasks. There are several popular concepts of project monitoring, such as logical framework approach (LFA), earned value management (EVM), etc., and each of them depends on properly optimized network graph that represents dependences between project tasks. Article describes the features and problems of multi-objective optimization in project management with reference to network graphs. The significant role of network graph optimization for project monitoring systems is proved and the model of multi-objective optimization of the network graph on criterion functions of duration and project cost based on NSGA-II genetic algorithm is proposed as the main purpose of research. Model takes into account the reserves of time on a critical way of the network graph, possibility of decreasing the load of available resources at the expense of time reserves on non-critical ways of the network graph, variety of used resources and options of delegation. One of its main advantages is quite low laboriousness of implementation, that depends on number of nodes on the network graph of the project and on number of possible options of delegation for the project tasks with several alternatives of delegation. Model has been tested on sample project with real data and results have been analyzed.

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Section: Discussionmentioning

confidence: 99%

“…The network graph plays important role among these schedules (Parveen & Saha, 2012). The optimized network graph can be used subsequently as an evident source of standard values regarding terms and cost of realisation of separate operations and packages of works within the project (Wang et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

Genetic Algorithm of Network Graph Multi-Objective Optimization as an Instrument of Project Monitoring

Prokopyev¹

2014

ASS

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“…The configuration of this project is given in the Figure 5 and the optional days and direct cost for the activity of the project are given in the Table 1. Indirect cost rate was $1500/day [3]. The pareto solutions obtained from this study are given in the Table 2 by comparing the other results.…”

Section: Numerical Examplementioning

confidence: 92%

“…The detailed information can be found from the studies related to the time-cost trade-off problem such as [3]. In this study, to calculate the total project time the critical path method (CPM) is used.…”

Section: Time-cost Trade-off Problem In Construction Projectmentioning

confidence: 99%

Decision-Making Process Techniques Used in the Optimization of Construction Projects

Dede¹

2018

NWSA

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It is desirable that the construction projects can be completed in the most appropriate manner at the desired time, cost or other purposes. If any of these requests are solely aimed, the appropriate project parameters can be determined and the results such as the optimal time or cost can be determined after an optimization process. If more than one goal is to be achieved at the same time, the decision making process becomes more difficult. In this case, rather than a single final result, multiple results can be obtained. A number of techniques are used to optimize both time and cost. In this study, the techniques proposed for this purpose in the literature have been examined and some of these techniques have been applied to the construction projects considered as time-cost problem. Also, the TLBO algorithm, popular in recent years, has been the preferred in the solution of the multi-objective optimization problem. Construction project business activities which are taken into account as a timecost problem in the literature are examined as numerical examples. A computer program is developed to realize the time-cost trade-off problem by using MATLAB.

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“…Some researchers have tried to introduce evolutionary algorithms to find global optima such as genetic algorithm (GA) (Feng et al [6]; Gen and Cheng [21]; Zheng et al [10]; Zheng and Ng [9]; Mendes [16,18] and Parveen and Saha [32]) the particle swarm optimization algorithm (Yang [10]), ant colony optimization (ACO) (Xiong and Kuang [28]; Ng and Zhang [24]; Afshar et al [2]) and harmony search (HS) (Geem [29]). In this paper, the optimal time and cost generated by the GA techniques are compared with those produced by other techniques through some problems obtained from literature.…”

Section: Introductionmentioning

confidence: 99%

Multiobjective Optimization Using Genetic Algorithms in Time-Cost Construction Project Scheduling Problem

Magalhães-Mendes¹

2016

Proceedings of the VII European Congress on Computational Methods in Applied Sciences and Engineering (ECCOMAS Congress 2016)

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A GA-based fuzzy optimal model for time-cost trade-off in a project with resources consideration

Cited by 9 publications

References 31 publications

Genetic Algorithm of Network Graph Multi-Objective Optimization as an Instrument of Project Monitoring

Genetic Algorithm of Network Graph Multi-Objective Optimization as an Instrument of Project Monitoring

Decision-Making Process Techniques Used in the Optimization of Construction Projects

Multiobjective Optimization Using Genetic Algorithms in Time-Cost Construction Project Scheduling Problem

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