Manuscript completed

Research Manuscript

Resilient Multi-Echelon FMCG Supply Chain Network Design under Uncertainty

A resilient multi-echelon FMCG supply-chain network design model under supplier and warehouse disruptions, formulated using two-stage stochastic mixed-integer linear programming.

Authors
Bhavish Jain, Vijaya Kumar Manupati

Research Problem

Fast-moving consumer goods networks must keep serving demand even when suppliers and warehouses are disrupted. This work formulates a resilient multi-echelon FMCG supply-chain network design model that makes integrated decisions across facility location, production, inventory, transportation, cross-docking, lateral transshipment, capacity loss, and lost sales. The two-stage stochastic programme is solved and validated with a classical and accelerated Benders decomposition scheme, and its computational performance is compared against CPLEX branch-and-cut and classical Benders decomposition.

Methodology

Two-Stage Stochastic Mixed-Integer Linear ProgrammingSample Average ApproximationLatin Hypercube SamplingClassical Benders DecompositionAccelerated Benders DecompositionValid InequalitiesOptimality CutsFeasibility CutsLazy-Constraint CallbacksStatistical Validation

Tools

PythonIBM ILOG CPLEX

Current Stage

To be communicated to Transportation Research Part E: Logistics and Transportation Review