Planning, Design and Operation of Sustainable and Efficient Multi-Product Rice Value Chains Using Multi-Objective Spatio-Temporal Optimisation

The rice value chain, especially in the Philippines, has a lot of potential for improvement in terms of sustainability and efficiency, as well as additional value creation by effectively utilising the by-products from rice production. Rice straw and rice hull that pose disposal problems can be used as low-carbon sources of energy. Rice bran and rice hull ash, which are currently considered, as wastes are finding uses in the animal feed and cement industries, respectively. Generating multiple products will lead to a complex decision-making process in supply chains especially in the case of rice crop which is vital in the Philippines’ food security. Thus, systematic planning techniques are needed to address important decisions along the stages in rice value chains.
In this study, a mixed integer linear programming (MILP) model was developed for planning, design and operation of multi-product rice value chains. A value chain considers all activities from planting, cultivating and harvesting of the crop to distributing the products to customers. In order to capture the spatial-dependencies of the problem, such as the candidate locations for rice plantations and processing facilities, and location of demands, the Philippines is represented as a grid of 50 km squares. The model considers a long planning horizon, out to 2050, in order to model the staged investment in and retirement of technologies. It also captures seasonal variations in rice yield/productivity and changes in demands for rice and the by-products from rice production. The model determines interdependent decisions such as where to locate the plantations and processing facilities, when to invest in them and what size/capacity; what products to produce, how to transport and store resources, centralised or distributed production, among others. Different objectives are considered such as maximisation of profit and minimisation of GHG emissions. Pareto sets are generated in order to determine optimal solutions that represent a balance between economic gain and environmental protection. Case studies using the Philippine rice sectors are used to illustrate the capability of the model for providing useful insights on planning, design and operation of multi-product rice value chains.