Assessment of productivity and duration of highway construction activities subject to impact of rain

Pan, Nang-Fei

doi:10.1016/j.eswa.2004.10.011

Cited by 30 publications

(24 citation statements)

References 9 publications

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“…Pan (2005) notes the importance of estimating the effect of rainfall on scheduling construction of roads and develop a fuzzy reasoning system that considers the impact of rainfall on planning construciton of roads. The paper by Bonfatti et al (2006) argues that most approaches to scheduling falsely assume that parameters, such as quantity and due date, are deterministic and precise.…”

Section: Fuzzy Logic In Schedulingmentioning

confidence: 99%

A survey of AI in operations management from 2005 to 2009

Kobbacy

Vadera

2011

Journal of Manufacturing Technology Management

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Purpose: The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence this paper presents a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.Design/methodology/approach: The paper builds upon our previous survey of this field which was carried out for the 10 year period 1995 to 2004(Kobbacy et al. 2007. Like the previous survey, it uses the Elsevier's ScienceDirect database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus the application categories adopted are: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Research on utilising neural networks, case based reasoning, fuzzy logic, knowledge based systems, data mining, and hybrid AI in the four application areas are identified. Findings:The survey categorises over 1400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: (a) The trends for Design and Scheduling show a dramatic increase in the use of GAs since 2003-04 that reflect recognition of their success in these areas, (b) A significant decline in research on use of KBS, reflecting their transition into practice, (c) an increasing trend in the use of fuzzy logic in Quality, Maintenance and Fault Diagnosis, (d) surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.Originality/value: This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

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Section: Fuzzy Logic In Schedulingmentioning

confidence: 99%

A survey of AI in operations management from 2005 to 2009

Kobbacy

Vadera

2011

Journal of Manufacturing Technology Management

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“…6 Rainfall may have cost-related effects on highways. For instance, excessive rainfall leads to delays and even to complete suspension of highway construction activities, thereby leading to cost overruns (El-Rayes and Moselhi 2001;Pan 2005). I therefore 4 While states are apportioned a certain amount of highway funding each year, the actual federal funds states receive are reimbursements for actual costs incurred on approved projects.…”

Section: Empirical Model and Strategymentioning

confidence: 99%

Volatile earmarked revenues and state highway expenditures in the United States

Nguyen‐Hoang

2014

Transportation

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Heavy use of transportation-related revenues earmarked for highways is one of the distinguishing characteristics of state highway finance in the United States. This is the first study to examine the potentially differential effects of earmarked revenue volatility on state highway expenditures. Using panel data for over 30 years, I found in both OLS and 2SLS estimations that state highway expenditures did not respond to upward cyclical deviations in earmarked revenues. Also, a one-percentage-point downward deviation of earmarked revenues from trend was associated with a decline of between 0.24 and 0.32 % in state highway expenditures. This finding has potential policy implications for state budgets and efforts to maintain or expand transportation infrastructure and, by extension, efforts to spur economic growth.

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“…Mao [4] used FIS to model labor productivity of concrete wall formwork activity. Pan [5] studied the effect of rainfall on productivity and duration of highway activities using a FIS. Fayek and Oduba [6] also used FISs to model the labor productivity of industrial pipe rigging and welding activities.…”

Section: Introductionmentioning

confidence: 99%

Context Adaptation of Fuzzy Inference System-Based Construction Labor Productivity Models

Tsehayae

Fayek

2018

Advances in Fuzzy Systems

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Construction labor productivity (CLP) is one of the most studied areas in the construction research field, and several contextspecific predictive models have been developed. However, CLP model development remains a challenge, as the complex impact of multiple subjective and objective influencing variables have to be examined in various project contexts while dealing with limited data availability. On the other hand, lack of a framework for adapting existing or original models from one context to other contexts limits the possibility of reusing existing models. Such challenges are addressed in this paper through the development of a context adaptation framework. The framework is used to transfer the knowledge represented in fuzzy inference (FIS) based CLP models from one context to another, by using linear and nonlinear evolutionary based transformation of the membership functions combined with sensitivity analysis of fuzzy operators and defuzzification methods. Using four context-specific CLP models developed for concreting activity under industrial, warehouse, high-rise, and institutional building project contexts, the framework was implemented, and the prediction capability of the adapted models was evaluated based on their prediction similarity with the original models. The results showed that linearly adapted CLP models for industrial and institutional contexts and nonlinearly adapted CLP models for warehouse and high-rise contexts provide a similar prediction capability with the original models. The proposed context adaptation framework and findings from this paper address the limitations in past context adaptation research by examining a practical context-sensitive application problem and further examining the role of fuzzy operators and defuzzification methods. The findings assist researchers and industry practitioners to take full advantage of existing FIS-based models in the study of new contexts, for which data availability might be limited.

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Assessment of productivity and duration of highway construction activities subject to impact of rain

Cited by 30 publications

References 9 publications

A survey of AI in operations management from 2005 to 2009

A survey of AI in operations management from 2005 to 2009

Volatile earmarked revenues and state highway expenditures in the United States

Context Adaptation of Fuzzy Inference System-Based Construction Labor Productivity Models

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