A NOVEL ADAPTIVE OPTIMIZATION FRAMEWORK FOR CLIMATE-RESILIENT TRANSPORTATION INFRASTRUCTURE: INTEGRATING SOFT COMPUTING WITH LIFE CYCLE SUSTAINABILITY ASSESSMENT
Shaikh Tausif Gulam Haqqani, Manoj Sharma, Shubhlakshmi Tiwari
Abstract: Climate change presents unprecedented challenges to the transportation infrastructure, especially in developing countries with a diversity of climatic conditions. This paper proposes an integrated adaptive optimization framework that combines climate projections, multi-objective optimization, and fuzzy logic-based sustainability assessment for designing climate resilient transportation infrastructure. The framework uses an optimization technique of Hybrid Genetic Algorithm-Fuzzy Logic Optimization (GA-FLO) to simultaneously optimize structural parameters while dealing with the uncertainty of climate. A novel Climate Resilience Index (CRI) based on 12 climatic parameters and their interactions with material properties is created to get India's infrastructure resilience. The methodology combines the Adaptive Neuro-Fuzzy Inference System (ANFIS) enhanced with LSTM's with a fuzzy based Life Cycle Assessment (LCA) for climate uncertainty based Adaptive maintenance prediction. The framework is verified by its application to 150 road and bridge projects over three climatic regions of India, viz, tropical (Kerala), arid (Rajasthan) and temperate (Himachal Pradesh). Results show that optimized adaptive designs reduce the damage caused by climate by 68.4%, increase the service life by 42.7% and save 31.8% lifecycle cost compared to the conventional designs. The proposed CRI is able to predict successfully the outcome of the resilience with an accuracy of 94.2%, while the optimization effect of GA-FLO is to reduce the cost of the materials by 24.3% without compromising the integrity of the structure. The research presents practical guidelines on climate-resilient infrastructure design/failure based on extensive numerical simulations and case studies.
Keywords: Climate-resilient infrastructure; Adaptive design; Genetic algorithms; Fuzzy logic; ANFIS; Life cycle assessment; Transportation infrastructure; Optimization
DOI: 10.24874/PES08.03.009
Recieved: 28.05.2026 Revised: 17.07.2026 Accepted: 11.08.2026
UDC:
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