Incorporating the Credit Constraint in a Linear Programming Model: A Case Study of a Rural Farmer in Zimbabwe

Abstract

The available working capital required to finance purchase of inputs on a farm like seeds for instance, can be an important constraint on a farm. Some working capital may be available from the farm family‘s savings. The farmer may have an option for increasing his working capital by borrowing. In this study, a linear programming model was developed in order to determine the optimal crop combination for a rural farmer. The linear programming model incorporated the credit constraint. The objective was to maximize income. Crops considered were maize, soya beans, cotton and tobacco. Tobacco gained acreage by 291.33%.Soya beans and cotton lost acreage completely. Maize lost acreage by 73.5%. The optimal income increased from $9,877.00 to $22,774.60. The optimal income showed an improvement of 130.58% compared to the farmer‘s existing plan. The results show that LP model solutions are worthy implementing because they increase income.

Genetic Algorithm Approach to a Multiobjective Land Allocation Model

“…Kakhki, Sahnoushi, and Abadi (2009) adopted a LP model to find the optimal cropping pattern, in Taybad of Khorasn Razavi state in Iran. Majeke and Majeke (2010) developed an LP planning model for a Farm Resource Allocation Problem and applied to a Case Study of small scale commercial farmers in Zimbabwe. Anderson and Farle (1983) adopted GP approach to select diets to meet the specific nutritional requirements.…”