Fuzzy Based Project Time-Cost Optimization Using Simulated Annealing Search Technique

Haque, Khan Md. Ariful; Hasin, M. Ahsan Akhtar

doi:10.4018/ijitpm.2014010108

Cited by 8 publications

(3 citation statements)

References 33 publications

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“…Aliverdi et al (2013) emphasize using statistical quality control charts in the monitoring of project duration and costs. Chou et al (2011) and Haque & Hasin (2014) propose using cost simulation procedures along with hypothesis testing to measure and control cost overruns in construction projects.…”

Section: Theoretical Framework and Literatur Reviewmentioning

confidence: 99%

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Managing an Engineering Project

Rahman

Wittman

Thabet

2016

International Journal of Information Technology Project Management

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This article provides an overview of the comprehensive process in creating a “Project Plan” for an engineering project. The authors discuss the challenges of project management tasks, tools, and methods used. They also discuss and compare other commonly used project planning practices and techniques. This article includes authors' experiences drawn from their careers and industries that are applicable to projects of this nature. They propose methodical approaches to handle a large, and complex engineering and construction project that takes several years to complete. The project selected is a hypothetical biomass engineering plant considered for this examination.

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Section: Theoretical Framework and Literatur Reviewmentioning

confidence: 99%

“…We created a responsibility matrix. Each responsible member was in charge of determining cost estimates (Salari et al 2015;and Haque & Hasin, 2014), time it takes to complete each task, as well as task dependencies.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

Managing an Engineering Project

Rahman

Wittman

Thabet

2016

International Journal of Information Technology Project Management

View full text Add to dashboard Cite

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“…The most crucial aspect of the optimization profession is figuring out how to meet deadlines on time and within budget. Numerous approaches are often used to investigate the optimization problem in terms of time and cost, including the fuzzy-based simulation annealing technique [5], critical path method, linear programming [6], non-dominated genetic algorithm [7], fuzzy logic with genetic algorithm [8], and learning curve methods [9]. Likewise, mathematical programming might be the most appropriate option.…”

Section: Introductionmentioning

confidence: 99%

Extremal-Micro Genetic Algorithm Model for Time-Cost Optimization with Optimal Labour Productivity

Sivakumar

Singh²,

et al. 2021

SV-JME

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In a highly competitive manufacturing environment, it is critical to balance production time and cost simultaneously. Numerous attempts have been made to provide various solutions to strike a balance between these factors. However, more effort is still required to address these challenges in terms of labour productivity. This study proposes an integrated substitution and management improvement technique for enhancing the effectiveness of labour resources and equipment. Furthermore, in the context of time-cost optimization with optimal labour productivity, an extremal-micro genetic algorithm (Ex-μGA) model has been proposed. A real-world case from the labour-intensive medium-scale bus body fabricating industry is used to validate the proposed model performance. According to the results, the proposed model can optimize production time and cost by 34 % and 19 %, respectively, while maintaining optimal labour productivity. In addition, this study provides an alternative method for dealing with production parameter imbalances and assisting production managers in developing labour schedules more effectively.

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