Sustainable supply chain resilience for logistics problems: Empirical validation using robust and computational intelligence methods.

A supply chain's ability to avoid an unexpected disruption or quickly return to a normal situation defines supply chain resilience. Prior works have emphasized the integration of supply chain resilience and sustainable development goals (sustainable supply chain resilience), which is the focus of this paper. This paper proposes a four-level supply chain consisting of suppliers, intermodal hubs, manufacturers, and distributors along with a heterogeneous fleet of vehicles. Two types of manufacturers are included: large and small. The small manufacturers are moveable. To contribute to sustainable logistics problems, the objectives are cost, carbon emissions, and job opportunities when the appropriate supply chain members and flow of materials are optimized. To contribute to supply chain resilience, this paper presents a new robust approach and a new multiobjective algorithm to capture uncertain parameters (e.g., supply cost and employee availability). A numerical example based on empirical data shows the applicability of the proposed model. • This paper proposes sustainable supply chain resilience. • A heterogeneous fleet of vehicles and manufacturers are considered. • A new robust approach is introduced. • A new multiobjective algorithm is proposed. • Datasets along with algorithms codes are available for journal readers. [ABSTRACT FROM AUTHOR]