GA Based FGP for Resource Allocation in Farming

GA Based FGP for Resource Allocation in Farming

Bijay Baran Pal (University of Kalyani, India)
Copyright: © 2014 |Pages: 17
DOI: 10.4018/978-1-4666-5202-6.ch093
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Background

The different MP approaches for crop production planning have been widely used since Heady (1954) demonstrated the use of linear programming (LP) for land allocation problems in agricultural system. The constructive optimization models for optimal production of crops have been deeply studied (Wheeler & Russell, 1977; Glen, 1987) in the past.

Key Terms in this Chapter

Fuzzy Programming: Fuzzy programming is the modeling aspects of optimization problems in which parameter values are defined in an inexact way owing to impression in human judgments as well as inherent impression in parameters themselves.

Stochastic Programming: Stochastic programming is an optimization technique for solving problems with probabilistically defined uncertain data.

Farm Planning: Proper allocation of cultivable land and utilization of various productive resources for optimal yielding of several seasonal crops.

Goal Programming: Goal programming is an optimization technique to solve problems with multiplicity of objectives, which are generally incommensurable and they often conflict each other in a decision making horizon.

Genetic Algorithm: Genetic algorithm is a global solution search approach and based on the mechanics of natural selection and natural genetics.

Fractional Programming: Special field of study in the area of mathematical programming, where certain objectives appear in the form of ratios for optimizing them.

Fuzzy Goal Programming: Fuzzy goal programming is an extension of conventional goal programming to solving multiobjective decision problems with imprecisely defined model parameters.

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