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• Optimization of fleet size combination in containers terminal is presented. • The optimization minimizes both vessel turnaround time and handling cost. • A new double-cycling handling strategy is incorporated in the optimization process. • The new strategy saved 20% in both time and cost and increased productivity by 25% Every few years, larger containerized vessels are introduced to the market to accommodate the increase in global trade. Although increasing the capacity of vessels results in maximizing the amount of imported and exported goods per voyage, yet it is accompanied with new challenges to terminal planners. One of the primary challenges is minimizing the vessel turnaround time with the least possible cost. In this context, this paper presents the development of a multi-level optimization model using the elitist non-dominated sorting genetic algorithm (NSGA-II) to determine the optimal or near-optimal fleet size combination of the different container handling equipment used in the terminal. The model aims to minimize two conflicting objective functions, namely, vessel turnaround time and total handling cost. Furthermore, the model considers a double-cycling strategy for the container handling process to achieve increased productivity and eventually more reduction in the vessel turnaround time. The model was implemented on a real-life case study to demonstrate its efficiency and the benefit of employing the double-cycling strategy compared with the traditional single-cycling strategy. The results demonstrated the efficiency of employing the double-cycling strategy by providing a reduction of above 20% in both the vessel turnaround time and the total handling cost and an increase of above 25% in the productivity when compared to the traditional single-cycling strategy. [ABSTRACT FROM AUTHOR]

• Critical causes of RMAA-related accidents are identified. • Novel hybrid fuzzy-based algorithms are employed for result accuracy enhancement. • Considerable inherent interrelationships exist among RMAA-related causal factors. • "Limited financial/safety resources of SMEs" is the most influential causal factor. • The identified causes are prioritized using IVIF-DEMATEL-ANP method. Despite the recent improvements made to the area of occupational health and safety (OHS) within the construction sector, the Repair, Maintenance, Minor alteration, and Addition (RMAA) works have been given scant attention. In this study, given the significance of the injuries reported in the RMAA sector, a meticulous investigation is conducted into the causal factors contributing to the related accidents by capturing their causal interrelationships together with their importance levels. To this end, first, a comprehensive list of factors contributing to RMAA accidents was obtained through an extensive literature review and experts' interviews. Then, through the lenses of qualified relevant experts in Hong Kong, the proposed interval-valued intuitionistic fuzzy (IVIF) DEMATEL and IVIF analytic network process were employed to respectively uncover the cause-and-effect relationships among these factors and prioritize them. The findings show that "the lack of assessment and praising of workers' OHS understanding and performance," "the high turnover rate of workers resulting in difficulties in providing safety training and education," and "lack of safety training for workers" are the most critical causes to be given full attention by construction safety managers. The methodological approach proposed in this study brings about two theoretical contributions: unraveling interrelationships existing among the causal factors, and prioritization of them considering their interrelationships. The findings reported in this study also aid decision-makers in improving the critical causal factors in a way to enhance the OHS of RMAA sector. [ABSTRACT FROM AUTHOR]