The aim of natural gas pipeline projects is generally to make it possible to transfer the natural gas produced from one place to another. There are various safety risks for these broad construction systems. Therefore, to reduce the negative effects of emerged risks, a new risk assessment approach for occupational health and safety (OHS) is needed. In this paper, FMEA-based AHP-MOORA integrated approach under Pythagorean fuzzy sets is proposed for assessing occupational risks in a natural gas pipeline construction project. A case study for concrete coating process of natural gas pipeline project is employed to show the feasibility and effectiveness of the proposed integrated approach. A comparative study, correlation analysis, and sensitivity analysis are also presented to approve the novel risk assessment approach. In conclusion, the integrated approach gives more reasonable results for evaluating the occupational risks in project of pipeline construction using the advantage of Pythagorean fuzzy sets that reflects uncertainty in more suitable way.

Supplier selection is one of the most important multi-criteria decision-making (MCDM) problems for decision-makers in the competitive market. Today’s organizations are seeking new ways to reduce the negative effects they have on the environment and to achieve a greener system. Currently, the concept of green supplier selection has gained great importance for its ability to incorporate environmental or green criteria into classical supplier selection practices. Therefore, in this study, a multi-phase MCDM model based on the best-worst method (BWM) and the interval type-2 fuzzy technique for order preference by similarity to ideal solution (IT2F TOPSIS) is proposed. A case study in a plastic injection molding facility in Turkey was carried out to show the applicability of the proposed integrated methodology. The paper offers insights into decision-making, methodology, and managerial implications. Results of the case study are examined and suggestions for future research are provided.

In recent years, the interests of disassembly line have increased owing to economic reasons and the increase of environmental awareness. Effective line can provide many advantages in terms of economic aspect and it facilitates competition the companies with others. This study contributes to the relevant literature by a branch, bound and remember algorithm for disassembly line balancing problem with AND/OR precedence. The proposed exact solution method employs the memory-based dominance rule to eliminate the reduplicated sub-problems by storing all the searched sub-problems and to utilise cyclic best-first search strategy to obtain high-quality complete solutions fast. In this paper, minimising the number of stations is taken as the performance measure. The proposed methodology is tested on a set of 260 instances and compared with the mathematical model using CPLEX solver and five well-known metaheuristics. Computational results show that the proposed method is capable of obtaining the optimal solutions for all the tested instances with less than 0.1 seconds on average. Additionally, comparative study demonstrates that the proposed method is the state-of-the-art algorithm and outperforms the CPLEX solver and metaheuristics in terms of both solution quality and search speed aspects.