Optimum Plant Mix Selection for Urban Home Gardens: an Attempt on Genetic Algorithm and Integer Linear Programming


  • P.H.H.P.N. De Silva Department of Mathematics, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
  • G.H.J. Lanel Department of Mathematics, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.
  • M.K.A. Ariyaratne Department of Computer Science, Faculty of Applied Sciences, University of Sri Jayewardenepura, Nugegoda, Sri Lanka.


Home Gardening , Genetic Algorithm , Integer Linear Programming , Optimum plant mix , Plant diversity , Plantation area


Home gardening is a highly deliberated topic in the current world as a consequence of social, economic, and environmental benefits. Due to the lack of mathematical applications in non-profit-based home gardens, this study is mainly focused on the social and environmental aspects of home gardening rather than focusing on the economic perspective. Therefore, this study was scrutinized in an urban city in Sri Lanka where home gardening is disparate from the economic perspective due to various reasons. In the initial stage of the research process, a novel approach to plant ranking was proposed under the concept of home gardening. The Genetic Algorithm (GA) and Integer Linear Programming (ILP) models were proposed in this study under two scenarios and implemented using both primary and secondary data. Implementation of GA was performed using MATLAB software and parameter values were determined by the trial and error method. The second scenario was accomplished through the ILP model along with sensitivity analysis using Excel Solver. Both methods provided optimum plant mix effectively and efficiently for the selected garden considering a horizontal space.


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How to Cite

P.H.H.P.N. De Silva, Lanel, G., & Ariyaratne, M. (2022). Optimum Plant Mix Selection for Urban Home Gardens: an Attempt on Genetic Algorithm and Integer Linear Programming. International Journal of Applied Sciences: Current and Future Research Trends, 15(1), 101–119. Retrieved from https://ijascfrtjournal.isrra.org/index.php/Applied_Sciences_Journal/article/view/1283