The PROMETHEE is a significant method for evaluating alternatives with respect to criteria in multi-criteria decision-making problems. It is characterized by many types of preference functions that are used for assigning the differences between alternatives in judgements. This paper proposes a preference of green suppliers using the PROMETHEE under the usual criterion preference functions. Comparable results are presented to check the effect of different preference functions on the final preference. Seven economical and environmental criteria, four suppliers and five decision makers were the main structures in the green supplier selection problem. Data were collected via personal communication with decision makers using five-point Likert scale. The algorithm of PROMETHEE under usual criterion function was implemented, and the results show that supplier A₁ is the most preferred alternative. Comparative results also show that supplier A₁ is the most preferred alternative despite the difference in preference functions used.

Last-mile delivery (LMD) is essential in supply chains, and providers of logistics services are aware that they must adapt to changing customer and society expectations, competition challenges, and modern technologies. In light of the importance of artificial intelligence (AI) in modern technologies, this article employed a narrative literature review to recognize impacts of AI-powered technologies that aid in optimizing the LMD component. For this study, two possible classes of technologies were considered: tangible technologies, such as robots, drones, and autonomous vehicles, and intangible technologies, such as decision support tools and operating systems. Thus, this article frames potential developments in modern LMD, taking into account the fact that technological advancement brings both opportunities and challenges. According to this literature review, the modern version of LMD is capable of providing services that are both more productive and more sustainable, thus satisfying demands for better services. Last but not least, another goal of this article was to look into the challenges that limit the benefits of modern LMDs. Finally, suggestions are provided as a resource for practitioners and policymakers working in the supply chain to improve performance.

Personnel selection determines the input quality of personnel, therefore, plays a decisive role in human resource management. Personnel selection problem has been studied extensively. Selecting the best personnel among many alternatives is a multi-criteria decision making (MCDM) problem. The necessity of dealing with uncertainty in real world problems has been a long-term research challenge that has originated different methodologies and theories. Fuzzy decision making along with their extensions have provided a wide range of tools that are able to deal with uncertainty in different types of problems. Fuzzy decision making methods have become increasingly popular in decision making for personnel selection. Various decision making approaches have been proposed to solve the problem. This paper presents a comprehensive literature review of the applying Fuzzy decision making techniques in personnel selection problem.