Evaluating the resilience of residential buildings during a pandemic with a sustainable construction approach.

The COVID-19 pandemic has been a catastrophic event that has affected all aspects of human life worldwide. Due to the high genetic mutations of the virus, there has been a prolonged search for definitive therapeutic discovery, leading to extended periods of home quarantine. As a result, homes have become multipurpose spaces for work, education, sports, and other daily activities. Given the importance of residential buildings as the first line of defense against possible future pandemics, a model has been proposed to assess their readiness to handle pandemics using a sustainable development approach. This study investigates the most crucial criteria for evaluating residential buildings and applies them in a Multi-Criteria Decision Making (MCDM) process. The final evaluation model is presented using the SWARA and COCOSO methods, along with a set of criteria selected and weighted by experts. The study shows that the criteria related to health and safety are more critical than other sectors. Buildings that meet the standards of this group better are likely to have a higher score.

A prediction model for safety performance of construction sites using a linear artificial bee colony programming approach.

The reputation of the construction industry as one of the most world's dangerous industries is because of its tremendous accident and fatality rate. In this study, a prediction model for construction projects' safety performance was presented as an alarm system. The proposed model can predict the safety performance at the beginning of the project. To do so, firstly, data preparation and, secondly, developing an automatic regression model were carried out as the two main steps of the study. To collect data, after identifying effective criteria, a questionnaire was developed. Next, an innovative machine learning method, named linear artificial bee colony programming, was used to discover the relationship between the identified criteria and safety performance. The results of one-dimensional and two-dimensional sensitivity analysis show that the four criteria of management commitment to safety, safety training, safety team and safety budget are the most important factors that influence safety performance.

Construction and demolition waste management: Fuzzy Analytic Hierarchy Process approach.

Construction and Demolition Waste (CDW) has recently received significant attention in the most developing countries, such as Iran. Since CDW generation is unavoidable, so development and implementation of an appropriate CDW management is widely recognized as an essential need. Different alternatives in CDW management have been proposed and implemented currently. In this study, a novel framework was established based on the Fuzzy Analytic Hierarchy Process approach in order to assess different CDW management alternatives in Tehran, Iran. Proposed alternatives (including landfilling, recycling, reusing, and reduction) were investigated with respect to 16 different individual criteria. The criteria were divided into four different groups, namely environmental, social, technical, economic. A database in this study was established through a questionnaire survey. The relative significance of alternatives with respect to each criterion was assessed. The obtained results revealed that reduction has the highest and landfilling has the lowest priorities. Furthermore, it was found that economic criteria have the highest and social criteria have the lowest importance among the studied criteria. Also, the proposed framework can be used as a beneficial tool that will assist decision-makers in determining the most suitable CDW management alternatives in the case of different criteria that are completely/partially in conflict.