Application of elephant herding optimization and system dynamics to access supply chain capabilities

Purpose This study investigates the supply chain capabilities that contribute to overall supply chain efficiency under disruptive conditions. With increasing uncertainty and demand volatility, organizations require a systematic approach to identify and strengthen critical capabilities. The purpose of this research paper is to assess, prioritize and optimally combine key supply chain capabilities to enhance efficiency during disruptions. Design/methodology/approach A comprehensive industrial study was conducted to identify factors that influence supply chain capabilities. Based on industrial inputs, a structured questionnaire was developed to capture expert judgments. A multi-level assessment model was formulated to categorize factors contributing to individual capabilities. The analytic hierarchy process (AHP) was used to determine the relative importance of these factors. Subsequently, the elephant herding optimization (EHO) algorithm was applied to identify optimal pairs of supply chain capabilities for further analysis. These selected capability combinations were modeled using a system dynamics framework. Real-world demand data obtained from industries were integrated to simulate system behavior under high-demand and disruptive scenarios. Findings The results identify the most influential factors affecting supply chain capabilities and highlight optimal capability combinations that significantly improve supply chain efficiency during disruptions. System dynamics simulations demonstrate the dynamic performance of these combinations under demand fluctuations, supporting improved resilience and operational performance. Research limitations/implications This study relies on expert judgment and industry-specific data, which may limit generalizability across all sectors. Future research can extend the model to additional industries and disruption scenarios. Practical implications The proposed framework supports managers in making data-driven decisions to prioritize and combine supply chain capabilities for improved efficiency and resilience. Originality/value This study offers a novel integrated framework combining AHP, EHO and system dynamics to assess and optimize supply chain capabilities under disruptive environments.