A mathematical optimisation model for analysis of minimal cropland expansion in agro value chains

Abstract

Increasing population, accelerated urbanisation and rise in income generation have led to the increased concern on sustainable production and consumption of food. This has put severe stress on farmers and plantation owners to rapid expansion of crop lands and plantations to meet the demand. However, the expansion has resulted in large scale unplanned deforestation. The proposed work presents a Mixed Integer Linear Programming (MILP) model to strategies for minimal crop land and plantation expansion based on the predicted future demand of agro-products. The proposed model is based on the concept which used previously to strategies operation of utility systems. In this work, the proposed model is used to determine the minimal lands for expansion (if required) when there is an increased demand. However, if the demand of the agro-product is projected to decrease, then the model identifies the optimised excess existing crop land(s) or plantation(s) that can be removed from the value chain. Based on the optimised result, the cost involved in expansion (i.e., deforestation and planting costs, etc.) and the transport cost can be determined. The selection of truck capacity for the optimised logistics of the agro products from the cropland to the processing facility can also be determined. By minimising the total cost (expansion cost and transport cost), the area of expansion and transportation distance can be minimised to meet the increased demand requirement, thereby resulting in lesser environmental impact. Note that, the model provides strategic optimisation for expansion of croplands and tactical optimisation for the logistics between crop lands and processing facility. A palm oil value chain is solved in this work to illustrate the proposed model. Five different scenarios with increasing and decreasing palm oil demands were solved and their respective results are discussed. The scenarios analyse the expansion in different types of lands — grasslands, tropical forests and peat forests. It is noted that the model selected grasslands over the other land types due to their least expansion cost and Land Use Change (LUC) tax rates; showing that the proposed approach promotes sustainability through cost. At higher palm oil demands scenario, apart from grasslands, tropical or peat forest lands are also seletected for expansion. Sensitivity analysis of increasing palm oil demand on expansion cost and LUC tax rates on total cost is also presented.