Files
Abstract
The development of a third world country requires a conscious balance between different planning and policy issues, such as population growth rate, gross national income, self reliance and long-term sustainable ecological development. This paper reports on a cross-disciplinary project to design a decision support system (DSS) that aims to assist government policy makers in planning the regional agricultural development of the Bungoma region in Kenya. Contrary to previous research, which has taken the perspective of a central planner and a static market, this model extends the scope by introducing the market mechanisms and price subsidies. The model is based on the Agro-Ecological Zones (AEZ) model, a previously developed non-interactive optimization model that provides an agro-ecological and economic assessment of various types of land uses, including cash-crops, food production, grazing, forestation and farming. This paper maintains the decision analytic scope of the AEZ model to explicitly incorporate a multicriteria decomposition optimization formulation that facilitates a direct trade-off analysis between the various decision criteria within a user-interactive decision support modeling framework. The model uses in-depth information about the Bungoma region, extracted from a large scale FAO database on Kenya that includes information on various climate and soil characteristics (e.g., thermal and moisture regime, soil type, slope class) and socio-economic data (e.g., projected growth rate and product demand patterns) for 90,000 agro-ecological cells. At each stage of the analysis, our system offers the decision maker several alternative planning strategies with different suggested land uses for over 100 different types of crops, fuelwood and livestock land utilization types of evaluation, allowing the decision maker to take into account trade-offs between a number of planning and policy criteria, including food output, net revenue, gross value of output, self sufficiency, production costs, arable land use and degree of erosion.