Track: Doctoral Dissertation Presentation

Abstract

Purpose-The purpose of this research is to develop a twin objectives formulation considering cost and back order minimization of supply chain operational problem faced by Food Corporation of India (FCI).

Design/methodology/approach-Cost minimization problem is a standard LP (Linear Programming) and we considered the formulation on quadratic objective for the back order minimization problem which turns out to be NLP (Non Linear Programming). We attempt solving NLP using Lagrangian relaxation. Findings-In this paper, few computational results have been given for the representative problems such as overall costs and the total back orders. Based on the empirical investigation, we discover many solutions which are obtained that make tradeoffs between overall cost and total back orders. In different instances of the problem, the proposed formulation with Lagrangian relaxation provides good bound in comparatively less computational time.

Practical implications-These solutions are of practical value to supply chain managers. The paper will be helpful to any industry in making good tradeoffs between total back orders and operational costs.

Originality/value-There is a variety of different approaches that different constraints of the supply chain problem be relaxed to generate different quality solutions. The research provides insight into the differences in the values of Lagrangian relaxation with total back orders and operational costs.