A Soft Computing Framework for Destination Prioritization in Kanpur

Abstract

Kanpur, one of India’s historically rich cities, holds significant potential as a tourist destination, yet policymakers and stakeholders face challenges in deciding which attractions to prioritize. Existing studies have rarely provided systematic evaluations of Kanpur’s sites, and most overlook uncertainties in tourist preferences, infrastructure, accessibility, and cultural value. To address this gap, the present study applies soft computing techniques to evaluate and rank major tourist destinations in Kanpur. By incorporating factors such as visitor preferences, cultural significance, infrastructure, accessibility, and environmental impact within a fuzzy decision-making framework, the methodology effectively handles subjectivity and imprecision in expert judgments. The results highlight destinations that balance heritage, accessibility, and sustainability, offering valuable insights into sites with the greatest potential to attract diverse visitors. These findings provide a practical decision-support tool for policymakers and tourism planners, demonstrating the effectiveness of soft computing in guiding sustainable tourism development and strategic resource allocation in Uttar Pradesh.