Entropy-based fuzzy SWOT decision-making for condition assessment of airfield pavements

Abstract

The paper proposes a novel decision-making methodology for integrated condition assessment and maintenance of airfield pavements by making use of non-destructive testing. The methodology has been explained by considering the runway of an international airport. A variety of performance indicators to appraise various aspects of pavement health, including structural, functional, and traffic mix analysis, have been considered. The field surveys and tests performed to determine each of the above factors are presented. An amalgamation of Fuzzy Analytic Hierarchy Process (FAHP) and entropy method is adopted to prioritise airfield pavement sections for maintenance and repair strategies based on the values of their entropy weights. The SWOT model and its hybridised forms deliver a platform to prioritise the pavement maintenance policy alternatives based on their technical feasibility, durability, financial viability, and reliability. The approach developed in this work is superior to other conventional optimisation models. Due to its flexibility, it can be appropriately customised and implemented as per the anticipated problem and data availability. Thus, it provides a wide scope to the decision-makers, planners, and implementation agencies to deal with diverse issues and execute the derived strategies immediately.