Optimizing renewable transportation framework by an extended spherical fuzzy rough multi-criteria group decision making method

Regional transportation infrastructure plays a crucial role in driving economic growth by facilitating the smooth movement of goods, services, and people. It strengthens trade connections, links markets, attracts investment, and promotes job creation and business development. A well-developed transportation network enhances accessibility, reduces transportation costs, and increases overall productivity. Additionally, it supports tourism, fosters regional integration, and ensures the efficient distribution of resources. Collectively, these factors contribute to sustainable economic progress and enhance regional competitiveness. However, major challenges in developing efficient transportation infrastructure include insufficient funding and a lack of effective coordination among stakeholders. Additionally, political instability and regulatory challenges can delay or hinder project implementation. To address the issue of sustainable regional transport architecture, this research study aims to introduce a novel multi-criteria group decision making method based on various dominating and preference relations among criteria of available options for optimization of renewable transportation infrastructure. The presented outranking approach involves elimination of certain inferior options and then comparing the remaining alternatives through outranking relationships. This process helps to identify the most suitable choices while accounting for conflicting criteria and their relative significance. The Step-wise Weight Assessment Ratio Analysis method is used to assess the relative importance of criteria weights through sequential computation. The proposed method is further integrated with spherical fuzzy rough numbers to manage uncertainty by incorporating both lower and upper approximations. To illustrate the effectiveness of the approach, it is applied to a case study aimed at optimizing the regional transportation framework in Africa, with detailed computational steps provided. The alternative that consistently outranks others through both downward and upward distillation processes is identified as the optimal solution. The methods validity and reliability are confirmed by comparing its results with those obtained from other well-established techniques, where the consistent identification of the same optimal choice demonstrates the robustness of our approach. Finally, the advantages, limitations, and potential future applications of the proposed method are discussed.