Abstract

A general framework for a combined land use and water management is described. An optimization problem is formulated that combines combinatorial and spatial characteristics. The aim of the planning is to maximize economic benefit, while minimizing water extraction and transportation cost under ecological constraints. A genetic algorithm is employed endowed with a new neighborhood operator. This operator acts on a local level, but it produces global results. Although the computational scheme does not include compactness as a separate objective, compact patterns are produced as emergent results. The algorithm is tested on a fictive area represented as a grid with 15×15 land blocks and, also, on a real-world case study.

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