International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XXXV, Part B5. Istanbul 2004 
  
models evaluation because we don't know about any factor 
maps interactions such as Environment Parameters and natural 
factors. 
2.3.4 Genetic Model: Before describing Genetic execution 
routine, it is necessary to introduce some corresponsive 
concepts as below. 
Choromosom : It displays one possible solution for a required 
problem. In site selection problem each set of selected spatial 
units are primary solutions for industrial estates location and 
indicates one Choromosom. Each unite in mentioned set is 
called Gene (Gen, 1997). 
Population : The possible amounts of Choromosoms in each 
generation, correspond to the population. On the other hand, 
population is a set of solutions (Gen, 1997). In industrial 
estates site selection, all selected spatial units of corresponsive 
layer (primary solutions) are called initial population. 
Fitness Degree : With comparing population of new and 
previous generation, fitness degree is determined using fitness 
function. This parameter identifies surviving feasibility in the 
next generation for all of choromosoms (Gen, 1997). For 
Genetic model execution in industrial estates site selection 
chromosomes spatial units values in the new generation are 
compared with corresponding spatial units values in previous 
generation. Then, fitness function is Algebraic comparing 
statement that identifies strong genes for industrial estate 
construction by cutting poor genes out that aren’t accordant to 
function. 
Control Parameters : They are specific conditions such as 
number of generations, number of choromosoms, length of 
choromosoms and model terminating condition that caused 
upper efficiency on model execution routine (Gen, 1997). 
In Genetic model first, initial population are selected. Then, 
factor maps are integrated based on definite integration 
operators (such as index overlay) and second generation is 
generated. After that, with using fitness degree, poor genes are 
appointed and eliminated. Finally, new generation is selected 
as initial population and above procedure is repeated until 
reaching constant state. We can decrease repetitions by 
entering control parameters in the execution routine. 
Therefore, this model is selected for our evaluation because site 
selection is a complex and composite problem with different 
criteria and conditions and genetic algorithm is a good model 
for solving these kinds of problems. 
3 EXECUTION AND EVALUATION OF MODELS 
In this section, we describe regular steps that identify the 
optimum model for industrial estates site selections as shown in 
following flowchart. 
  
Study Area 
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
  
v 
Determination of Efficient Criteria and Factors 
Y 
Data Preparation as Factor Maps 
v 
Data Weighting 
v 
Models Execution 
Y 
Models Evaluation 
v 
  
Finding Optimum Model and Location 
  
  
  
Figure 1. Models execution and evaluation steps 
3.1 Study Area 
Study area characteristics affect on industrial estates factors and 
criteria. More features diversity and spatial data density 
increase factors and criteria. For example, political factors are 
important on boundaries of cach country. In the case of 
political boundary of study area, we usually consider political 
conditions. Therefore, its complete recognition causes better 
selection of effective factors and criteria. 
This area is selected based on some parameters such as 
economic factors, politic strategies, data limitations and land 
physical attributes (Demers, 1992). According to experts' ideas 
of Iranian industrial estates company and necessary factors, 
first, we selected Azarbaijan province at the north-west of Iran. 
Then, a zone that covers a region of 1959.59 (km^2) area and 
located around Tabrize (capital of the east Azarbaijan province) 
was used as our study area. According to Figure 2, there are 
good density of data in our selected study area. 
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This area consist of different GIS ready layers with scale of 
1:25000 produced by NCC (National Cartographic Center of 
Iran) and edited to be GIS ready data by K.N.Toosi University 
of Technology. 
  
    
  
  
   
    
  
  
   
    
    
   
  
   
   
  
  
  
  
  
  
    
  
  
  
  
  
   
    
    
   
   
   
  
  
  
  
  
  
   
  
  
   
  
    
  
  
  
  
   
  
  
  
  
   
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