Providing a Model for Safety Risk in Construction Projects Using Fuzzy Expert System and Genetic Algorithm

Subject Areas : Project Management

Mehdi Vakilzadeh ¹ , Mohsenali Shayanfar ² , Masoud ZabihiSamani ³ , Mehdi Ravanshadnia ⁴

1 - Ph.D. candidate, Department of Civil Engineering, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran
2 - Associate Professor, Department of Civil Engineering, Iran University of Science and Technology, Tehran, Iran.
3 - Assistant Professor, Department of Civil Engineering, Parand Branch, Islamic Azad University, Tehran, Iran
4 - Associate Professor, Department of Civil Engineering, Tehran Science and Research Branch, Islamic Azad University, Tehran, Iran

Received: 2021-05-05 Accepted : 2021-12-08 Published : 2022-09-23

Keywords: Genetic Algorithm, fuzzy logic, Risk, safety, Expert System,

Abstract :

Today, the construction industry has a significant share of the economy and is considered as a leading and employment-generating industry. Due to various and sometimes risky activities during construction, there is a possibility of risks and personal and financial injuries, the control of which can be very effective in the success of the project. In the present study, a model for evaluating the safety risks of construction projects has been presented and new powerful tools such as fuzzy expert system improved with genetic algorithm have been used. Therefore, at first, the main factors influencing the safety of construction projects were identified by studying the literature and consulting with experts. Then, a questionnaire was provided to the experts to obtain their views and assess the severity of the risk effect and the probability of the occurrence of each risk. Then, based on the experts’ views, an expert system was obtained to assess the risks, which instead of using zero and one logic, governing expert systems, fuzzy logic was used. In the proposed model, to improve the performance of the fuzzy expert system, the genetic algorithm was employed as an optimizer. The research results indicated the optimal performance of the proposed model in assessing the safety risks of construction projects, so that the error rate of the model was acceptable. The model can also provide an effective tool for project managers in assessing and refining the safety situation in the construction site.

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