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Multi-echelon, Multi-period Supply Chain Master Planning in the Food Process Industry: A Sustainability Concept

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Abstract

This work presents a multi-echelon, multi-period supply chain master planning in the process industry; with a concept of sustainability, carried out on a real-life case study located in Port Harcourt in the South–South region of Nigeria. A supply chain master panning model (SCMPM) takes into account the most effective and efficient method to fulfil customer order and demand over a mid-term planning horizon; it also takes of bottlenecks by assigning demands to production. A mixed integer, multi-objective optimization deterministic model was formulated which aimed at minimizing the overall system costs, emissions, social factors and customers order fulfilment in the supply chain. The Cplex solver of GAMS, with branch and cut algorithm, was used on an Intel processor with 2.30 GHz speed to run the model. The results obtained from the model with real industry data from the case study gave the objective function values as 324, 854, 340 Naira for economic factor, 26.455 tonnes of CO2 emission (170.50 g CO2), for environmental factor, while those of the social factor and allowable backorder gave 10.433 and 105 units of product, respectively. The results showed the feasibility of the formulated models and the importance to have an effective master planning supply chain decision model in place. A significant correlation between four conflicting objectives was achieved by using the weighted-sum approach and the analytic hierarchy process (AHP) thereby converting them to a single linear optimization model.

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Data Availability Statements

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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Correspondence to Daniel O. Aikhuele.

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David, D.U., Aikhuele, D.O., Ughehe, P.O. et al. Multi-echelon, Multi-period Supply Chain Master Planning in the Food Process Industry: A Sustainability Concept. Process Integr Optim Sustain 6, 497–512 (2022). https://doi.org/10.1007/s41660-022-00229-3

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