Publication | Closed Access
Incorporating risk aversion and fairness considerations into procurement and distribution decisions in a supply chain
38
Citations
53
References
2019
Year
Supply Chain OptimizationEngineeringLogistics OptimizationInventory TheorySupply Chain RiskClosed-loop Supply ChainProcurement PolicyMarket DesignSupply Chain CostThree-tier Supply ChainOperations ResearchInventory ManagementRisk ManagementManagementLogisticsSupply ChainSystems EngineeringSupply Chain ViabilityRisk AversionDecision TheorySupply Chain DesignSupply Chain ManagementSupply Chain ProcurementNot-for-profit Supply ChainSupply ManagementBusinessFairness ConsiderationsPurchasingDecision ScienceSupply Chain Analysis
This paper considers a three-tier supply chain in which a manufacturer uses raw materials sourced from multiple suppliers to produce an item and sells it through multiple distributors. We develop an integrated optimisation model to study supply chain procurement and distribution decisions incorporating the manufacturer’s aversion to risk and the distributors’ concern for fairness in a climate of uncertain supply and demand. Resilient strategies, such as alternative sourcing and transshipment, are also considered when optimising the supply chain cost and service level. To solve the problem, a Monte Carlo simulation-based multi-objective stochastic programming model is built. It uses the CVaR (Conditional Value-at-Risk) and unfairness aversion utility function to reflect the decision maker’s risk aversion and the customer’s concern for fairness, respectively. A Normalised Normal Constraint based algorithm is adopted to obtain the Pareto Frontier. In addition, the numerical analysis provides some valuable insights for supply chain managers.
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