Abstract

This paper examines a comprehensive supply chain planning and differential pricing problem with carbon emissions considering (inbound and outbound) transportation policies. It also incorporates customers' preferences regarding prices and products’ environmental attributes in a market-segmented setting. Furthermore, supply uncertainties (induced by COVID-19 epidemic) are incorporated into the supply chain resource allocation problem. A novel scenario-based mixed-integer non-linear programming model is developed to deal with challenges. Subsequently, an optimal tactical plan is obtained by employing two-stage stochastic programming and convex analysis, which are enhanced by the interval Hessian matrix. Our findings suggest that failing to account for supply uncertainty could lead to intolerable losses and compromise the sustainability of the business.

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