Plant selection is an important element in landscaping planning and design. Based on previously conducted research it is reported that 44-50 percent savings in landscape annual operating costs can be made when applying optimization techniques in the selection of plant types. Nonetheless, a lack in the existence of optimization tools that minimize operating and replacement costs has hampered achieving such savings. Current practice is characterized by landscape architects making their plant selection based on their individual judgment and past experience with aesthetics playing a vital role in such decisions. This paper describes the framework for a Sustainable Environmental Friendly Optimizer for Urban Landscaping (SEOUL) that is capable of supporting architects in delivering landscape designs that are both aesthetically pleasing while being cost effective and environmentally friendly. The system creates such a selection based on inputs provided by the landscape designers of preset fields in a web-based platform to reflect their design intent. These fields have been chosen based on field research with architects, suppliers and contractors. These fields include: Plant Classification, Plants Type, Spread, Life Cycle, Height, Root, Salt Tolerance, Draught Tolerance, Bloom Season, Base Color, Flower Color and Fruit Color. Such inputs by the user are then processed through an optimizer and plant database in order to provide the most appropriate plant selection. The optimizer has been built using a knapsack dynamic programming model; this allows for the rapid solving of the multi-objective problem to reach a set of plants that minimize the cost, as well as the water consumption. Furthermore, testing of the application was conducted to ensure that the application meets its value added objectives.