Abstract
The supply chain inventory planning is well studied and analyzed in the literature considering various costs and other factors. However, social factor is largely overlooked although, it is important like cost factors which generally come from sourcing, production, storage and distribution. In the current work, a mathematical model for supply chain inventory was developed with four objectives (i.e., cost, local development, steadiness in employment and investment in green technology). The first objective is related to the total cost, which includes mostly inventory, manufacturing, and re-manufacturing related costs. The other two objectives are related to social aspects which focus on improvement in local development and steadiness in employment. The fourth objective is related to environmental aspect which focuses on the right time to invest in environmentally friendly machinery and technologies. The proposed model has the capability to obtain the optimal number of products to be manufactured and re-manufactured, number of inventories, number of employees to recruit and lay-off within a certain region in each quarter of the year, and decision on time to invest in green technology or pay govt. penalty, considering the upcoming demand in each quarter. The weighted sum method is applied to solve the multi-objective optimization problem.
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Dhingra, A., Poonia, V., Kulshrestha, R. (2022). A Multi-objective Mathematical Model for Socially Responsible Supply Chain Inventory Planning. In: Sharma, D.K., Jain, M. (eds) Data Analytics and Artificial Intelligence for Inventory and Supply Chain Management. Inventory Optimization. Springer, Singapore. https://doi.org/10.1007/978-981-19-6337-7_3
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