Targeted Showering Optimization: Training Irrigation Tools to Solve Crop Planning Problems.

Muhammad Luqman; Muhammad Saeed; Javaid Ali; Muhammad Farhan Tabassam; Tariq Mahmood

doi:10.21162/PAKJAS/19.7910

Author(s)

Muhammad Luqman Department of Mathematics, University of Management and Technology,Lahore,Pakistan

Muhammad Saeed Department of Mathematics, University of Management and Technology,Lahore,Pakistan

Javaid Ali Department of Mathematics, University of Management and Technology,Lahore,Pakistan

Muhammad Farhan Tabassam Department of Mathematics, University of Management and Technology,Lahore,Pakistan

Tariq Mahmood Department of Electronics Engineering, University of Engineering and Technology,Taxila, Chakwal,Pakistan

Abstract

Optimization can play an important role in supporting agricultural community not only in designing and manufacturing mechanical equipment but also in optimal crop planning. The related optimization models are not necessarily linear due to varying resources and complex environmental processes. The traditional linear programming techniques may not be practical in such situations. Metaheuristics are powerful approaches to solve complex nonlinear models. Metaheuristics are developed by transforming dynamics of natural phenomena to artificial intelligence computational environment. Realizing the potential adaptability of working principles of irrigation tools, this paper develops a novel optimization algorithm called Targeted Showering Optimization (TSO) algorithm which aims to solve linear, nonlinear and multi-objective optimization problems arising in agriculture, engineering and other scientific areas. In the present work, the design of TSO algorithm has been elaborated in detail and is followed by the performance evaluation of TSO algorithm by applying it to six well-known benchmark functions. The obtained results reveal that the developed method finds the best quality solutions of at least four benchmark functions in just 100 iterations and in additional 100 iterations it supersedes other nature inspired algorithms. To show the applicability of the proposed method in agriculture, a case study regarding the model of optimal crop rotation in Slovenian organic farming has been solved by TSO. The results of optimization models of crop rotation produced by TSO are also promising and provide a clear trade-off between total income and the nitrogen off-take when the maximization of total income and minimization of nitrogen off-take are dealt simultaneously.

Publication Details

Page(s) 225-235

DOI 10.21162/PAKJAS/19.7910

Published Journal: Pakistan Journal of Agricultural Sciences, Volume: 56, Issue: 1, Year: 2019

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Keywords

linear and nonlinear programming, nature inspired algorithms, shadow price, Artificial showering, optimal crop rotation