A Meta-Heuristics Based Decision Support System for Optimal Crop Planning

Abstract

This paper presents a meta-heuristic based decision support system to support farmers with optimal strategic decision making in the crop planning system. The analysis and modelling of crop planning decision making process are attractive for producing formalized knowledge on cropping plans in an agricultural farm. The formalization of the decision making process is generally becoming a crucial focal point for developing decision support systems that go beyond the limitation of formerly developed prescriptive approaches. The methodology of this research strikes a balance between mathematical formulations of crop planning problems and effective implementation of crop planning decision models. The new approach used to solve this problem is applicable to both medium and large scale farming; it is also integrated a systemic framework to build better decision support systems in agriculture.

A novel methodology for optimal land allocation for agricultural crops using Social Spider Algorithm

“…In agriculture, optimization can be performed on irrigation, crop planning, land, soil, labour, transportation, climate, weed, fertilizer and pesticides. Various objectives and constraints can be considered for every type of optimization (Adekanmbi, 2014).…”

Peer Review #1 of "A novel methodology for optimal land allocation for agricultural crops using Social Spider Algorithm (v0.2)"

“…In agriculture, optimization can be performed on irrigation, crop planning, land, soil, labour, transportation, climate, weed, fertilizer and pesticides. Various objectives and constraints can be considered for every type of optimization [Oluwole Adekanmbi (2014c)].…”