A chance constraint based low carbon footprint supply chain configuration for an FMCG product

Abstract

Purpose Green supply chain management and new product innovation and diffusion have become quite popular and act as a rich source of providing competitive advantage for companies to trade without further deteriorating environmental quality. However, research on low-carbon footprint supply chain configuration for a new product represents a comparably new trend and needs to be explored further. Using relatively simple models, the purpose of this paper is to demonstrate how carbon emissions concerns, such as carbon emission caps and carbon tax scheme, could be integrated into an operational decision, such as product procurement, production, storage and transportation concerning new fast-moving consumer goods (FMCG) product introduction. Design/methodology/approach The situation titled “low-carbon footprint supply chain configuration problems” is mathematically formulated as a multi-objective optimization problem under the dynamic and stochastic phenomenon concerning receiver’s demand requirements and production plant capacity constraints. Further, the effects of demand and capacities’ uncertainties are modeled using the chance constraint approach proposed by Charnes and Cooper (1959, 1963). Findings Various cases have been validated using the case example of a new FMCG product manufacturer. To validate the proposed models, data are generated randomly and solved using optimization software LINGO 10.0. Originality/value The attempt is novel in the context of considering the dynamic and stochastic phenomenon with respect to demand center’s requirements and manufacturing plant’s capacity constraints with regard to the low-carbon footprints supply chain configuration of a new FMCG product.