📖 ABSTRACT/OVERVIEW
This dissertation develops and applies a robust optimisation model for supply chain network design under stochastic disruption conditions in the Nigerian FMCG sector. Existing supply chain network optimisation models developed for stable advanced economy environments fail to capture the multi-dimensional stochastic disruption environment characterising Nigerian FMCG supply chains, including simultaneous road network uncertainty, demand volatility, fuel price shocks, and supplier reliability variance. Drawing on robust optimisation theory, stochastic programming, and supply chain network design literature, the study constructs an original multi-stage, multi-echelon robust optimisation model that incorporates scenario-based uncertainty sets calibrated to Nigerian FMCG disruption data. Disruption scenarios are parameterised using a combination of historical supply chain performance data from six FMCG firms operating national distribution networks across all geopolitical zones, and Monte Carlo simulation of stochastic disruption events. The model minimises expected network cost across disruption scenarios while satisfying service level constraints, and is validated against actual supply chain performance records. Original contributions include the Nigerian FMCG disruption uncertainty set specification, the multi-stage robust model incorporating contextual stochasticity, and solution algorithm adaptations enabling practical computational tractability. Findings provide optimal network configurations that outperform current hub-and-spoke and regional warehouse designs under simulated disruption conditions. The dissertation advances supply chain operations research methodology for developing country logistics environments and provides actionable network redesign recommendations for FMCG supply chain directors and logistics infrastructure investors in Nigeria. Keywords: supply chain network optimisation, robust optimisation, stochastic disruption, FMCG, Nigeria.
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