There is an ever-growing demand for sustainable development (SD) plans, in order to foster a country’s economic growth by implementing suitable policies and initiative programs for the development of the primary, the secondary and the tertiary sectors. We present a multi-criteria modeling approach using the linear programming problem (LPP) framework for a simultaneous optimization of these three sectors. Furthermore, we develop a fuzzy goal programming (FGP) model that provides an optimal allocation of resources by achieving future goals on the gross domestic product (GDP), the electricity consumption (EC) and the greenhouse gas (GHG) emissions. Furthermore, a weighted model of FGP is presented to obtain varying solutions according to the priorities set by the decision-maker for achieving future goals of GDP growth, EC and GHG emissions. The presented models provide useful insight for decision-makers when implementing strategies across different sectors. As a model country, we chose India by the year 2030. A study of economic policies and sustainable development goals (SDGs) for India is finally carried out.

Purpose: The COVID-19 pandemic has caused significant disruptions to global supply chains (SCs), affecting the production, distribution, and transportation of goods and services. To mitigate these disruptions, it is essential to identify the barriers that have impeded the seamless operation of SCs. This study identifies these barriers and assesses their impact on supply chain network (SCN).Design/methodology/approach: To determine the relative importance of different barriers and rank the affected industries, a hybrid approach was employed, combining the best-worst method (BWM) and the technique for order preference by similarity to an ideal solution (TOPSIS). To accommodate the inherent uncertainties associated with the pandemic, a triangular fuzzy TOPSIS was used to represent the linguistic variable ratings provided by decision-makers.Findings: The study found that the airlines and hospitality industry was the most affected by the barriers, accounting for 46% of the total, followed by the healthcare industry (23%), the manufacturing industry (19%), and finally the consumer and retail industry (17%).Research limitations/implications: This study is limited to the four critical industries and nine identified barriers. Other industries and barriers may have different weights and rankings. Nevertheless, the findings offer valuable insights for decision-makers in SC management, aiding them in mitigating the impact of COVID-19 on their operations and enhancing their resilience against future disruptions.Originality/value: This study enhances understanding of COVID-19’s impact on SCN and provides a framework for assessing disruptions using multi-criteria decision-making processes. The hybrid approach of BWM and TOPSIS in a fuzzy environment is unique and offers potential applicability in various evaluation contexts.