## 2 Literature Review
### Methods for Decision Support  
Decision support techniques are crucial to solving the intricate allocation problems that arise while choosing a logistics location. The analytic hierarchy process (AHP) technique has been extensively utilized in the literature to rank the criteria for logistics location selection [16]. AHP helps in the selection process by enabling decision-makers to methodically evaluate and rank various location possibilities according to various criteria. The study established an international crew transfer facility located in Taiwan using the FD-AHP-TOPSIS technique [17]. The researchers used a methodology that integrated the FDapproach, the analytical hierarchy process (AHP), and the technique for order preference by similarity to ideal solution (TOPSIS). The findings offered a systematic methodology for assessing and selecting the best site for an international crew transfer facility located in Taiwan. Personal evaluations in the fuzzy analysis and possible differences in stakeholder perspectives are examples of limitations. To determine the placement of logistical centers, they utilized the AHP and the fuzzy comprehensive evaluation method in their analysis [18]. The researchers offered possible improvements in the efficiency and effectiveness of central location selection and provided a methodical approach to logistics decision-making. However, the particular context and variables considered during the evaluation may have constraints. The Gulf Cooperation Council (GCC) nations' logistics performance within international supply chains was examined in previous research [19]. The researchers used an extensive approach, perhaps combining quantitative and qualitative methodologies, to evaluate the GCC countries' logistical efficiency. The findings shed light on the differences in performance between GCC nations and their involvement in international supply chains. However, data accessibility issues and the changing characteristics of logistics factors could present challenges. A mixed-integer linear programming (MILP) model was utilized in the article to solve the logistics village location and capacity planning problem [20]. Capacity planning and logistics village site selection should be optimized to increase sustainability. The method used formulates and resolved the problem using MILP modeling. The findings offered information about effective capacity allocation and logistics network design techniques. Streamlining assumptions that might affect the model's applicability in the real world is one of its potential disadvantages. The study focused on risk assessment in the CPEC's supply chain networks. The authors concentrated on the complex dynamics of the business partnership. They examined the possible supply chain hazards and provided insights into the difficulties faced in the context of the CPEC. They assisted in comprehending and controlling hazards in the intricate CPEC network. The research investigated sustainable modeling using reverse logistics techniques in CPEC [21]. The authors used fuzzy multi-criteria decision-making (MCDM) to evaluate environmental and economic problems. They offered valuable perspectives for improving sustainability measures in the logistics sector, focusing on the complex dynamics of the CPEC. The article examined associated risks in the CPEC's road transportation networks [22]. The authors offered a complete analysis of these hazards and highlighted their all-encompassing characteristics. They provided insightful information that could be used to identify better and manage the risks connected to CPEC construction projects. The authors analyzed the CPEC's technical specifications and the policy implications for electric vehicles used in Pakistan [23]. They offered insights into technological issues and policy recommendations for a sustainable and effective electric transportation system. They examined whether Pakistan's transportation system could be integrated with electric vehicles.