Spatial Optimization and Resource Allocation in a Cellular Automata Framework
Epaminondas G. Sidiropoulos, Dimitrios G. Fotakis · InTech eBooks · 2011
Land management is a complex activity associated with the determination of land uses, the placement of activities and facilities and the distribution of resources over extensive territories with a view to satisfying one or more criteria of economical and/or ecological character. It follows from this descriptive definition that in land management it is not sufficient to distribute goods or commodities to a number of beneficiaries, but, mainly, to carry out planning with respect to space and location, thus intervening and shaping the local geography of economical and environmental characteristics. An important part of land management is land use planning, in which a given area is divided into land blocks with each one of them being assigned a specific land use, taken from a set of possible land uses. The search for suitable combinations of land uses, so as to attain given objectives, constitutes a computationally intensive optimization problem. A related problem concerns spatial resource allocation, in which one or several resources have to be allocated to each one of the described land blocks, again in order to attain preset objectives and possibly satisfy constraints. The sought for distribution and nature of these resources bears a strong relation to the land uses of the respective blocks. This fact gives rise to even more difficult, but also more realistic optimization problems. A basic resource to be managed is water. Allocating water may not simply involve its unit price, but also the estimation of transportation and extraction costs. In the latter case physical modeling of groundwater movement and pumping is needed and this contributes to the complexity and nonlinearity of the problem. This fact makes the present problem different from the typical allocation problems. Problems of land use planning and water allocation combined with water extraction have been presented by Sidiropoulos & Fotakis (2009) and Fotakis (2009) and are reviewed in this chapter, along with new results concerning a cellular – genetic approach. Genetic algorithms and cellular automata will be the basic tools to be implemented in the present approach. Genetic algorithms are well-known biologically-inspired meta-heuristics. Their properties and characteristics are described in textbooks such as Michalewicz (1992) and Goldberg (1989). Applications abound in the literature. Cellular automata date back to von Neumann. Their fundamental importance was demonstrated by Wolfram (2002). They have been used as a background for modeling a great diversity of natural, as well as social and economic systems. Cellular automata have been used for simulating natural phenomena. Also, numerous applications have been