Modelling and optimisation of Indian traditional agriculture supply chain to reduce post-harvest loss and CO2 emission

Purpose - The purpose of this paper is to reduce the post-harvest loss occurring through respiration and CO2 emission produce by the selected produces, during logistics. This paper proposes a supply chain (SC) structure for the Indian traditional agriculture SC planning model to reduce post-harvest loss and mixed closed transportation to reduce CO2 emission. Design/methodology/approach - The Indian agriculture SC structure is modeled and solved by genetic algorithm using a MATLAB Optimization toolbox. The respiration rate is measured by a static method. These values are applied in an SC planning model and the post-harvest loss and its corresponding CO2 emission are estimated. Findings - This paper proposes a supply structure for the Indian traditional agriculture SC to reduce the post-harvest loss; the experiments measured the respiration rate to estimate the CO2 emission. The mixed closed transportation method is found to be suitable for short-purpose domestic transportation. Research limitations/implications - The optimized supply structure leads to unemployment through eliminating the intermediaries. Therefore, further research encourages the conversion of intermediaries into hub instead of eliminating them. Practical implications - This paper includes implications for the development of Indian traditional agriculture SC by an optimized supply structure and novel transportation method for the selected agriculture produces based on compatibility. Originality/value - This paper identified that the agriculture produces respiration can also emit the CO2. The closed transportation method can reduce the CO2 emission of produces respiration than traditional open transportation.