Optimizing the production of a Zea mays - Grevillea robusta alley cropping system with the WaNuLCAS model using a tabu search heuristic.
Published: 2004
Language: eng
Number of pages: 94
Description: The Water, Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) and an intelligent optimization technique, namely a Tabu Search metaheuristic were employed to select the optimum management practices for a Grevillea robusta and Zea mays (maize) alley cropping system. This agroforestry system was simulated for Embu Research Station in the Central Highlands of Kenya where G. robusta is commonly grown. The objectives for this land-use system were to maximum tree and crop production and Net Present Value (NPV). The maize production was constrained not to fall below 75% of the first crop of a sole cropped maize cropping system. The decision variables that were determined included; the tree planting density, pruning management and fertilizer application in the even-aged alley cropping system. The WaNuLCAS model simulated crop growth successful but was found inadequate for tree growth. The Tabu search heuristic was found ideal for optimizing this alley cropping system.
Notes: Advisers:  Vic Timmer; David Martell.

Thesis (M.Sc.F.)--University of Toronto, 2004.

Electronic version licensed for access by U. of T. users.

Source: Masters Abstracts International, Volume: 43-03, page: 0749.

MICR copy on microfiche (2 microfiches).