The Grey Situation Decision Analysis on Regional Distribution of Grain and Oil Crops------ A Case Study of Sichuan Province in China : In Respective of Food Supply

Regional crops distribution is an import subject for developing modern agriculture now. Based on existing distribution of 7 grain and oil crops in Sichuan province, this paper chose 5 economic evaluation indexes to discuss the regional distribution of grain and oil corps in Sichuan with the method of grey situation decision. According to the row decision and column decision, this paper shows that the sorting result of the advantage grain and oil crops in 21 cities and prefectures of Sichuan province and the adaptability sorting result of 7 grain and oil crops in each region in Sichuan province, which provides scientific basis for the distribution of grain and oil industry in Sichuan province.

Along with the unification of urban area and countryside, and the urbanization, food safety has already become an urgent issue.Sichuan province, as an agricultural giant in middle China, has excellent natural and geographical conditions for developing agriculture.The development of grain and oil industry is meaningful for realizing regional food safety.Sichuan province must raise 6.8% of Chinese population by 4.2% of national cultivated lands.More people with less cultivated lands gives more pressure on the cultivated lands.To stabilize the areas of cultivated lands for crops and implement a scientific regional distribution of grain and oil crops, by improving the unit yield, is meaningful for driving the development of grain and oil industry, releasing the contradiction between population and lands, realizing optimal agricultural structure, and transferring rural surplus labor powers.This paper adopts the grain situation decision model from the grain system theory, takes 7 grain and oil crops in Sichuan province as objects, based on existing grain and oil production distribution in 21 cities (states) in Sichuan province, select 5 economic evaluation indexes, analyze the comparative advantages of different regions in grain and oil production, and discusses the regional distribution of grain and oil crops in Sichuan province, with the hope of offering scientific basis for the structure adjustment of grain and oil industry in Sichuan province.

The gray situation decision analysis method
The gray situation decision (Julong Deng, 2005) is a decision analysis method that uses a mathematic language and makes decisions match up with incidents by taking all decision factors into consideration.The gray situation decision is maybe single-objective decision or multi-objective decision.This paper adopts the multi-objective decision.Its mathematical principle and process are as follow.

Construct the decision matrix
Suppose there are m incidents in the gray situation decision, namely i a (i = 1, 2, ……, m); In correspondence to m incidents, there are n decisions, namely j b (j = 1, 2, ……, n).Name the combination of incident i a and decision j b as situation ij s = ( i a , j b ).It means the j decision ( j b ) is for the i incident ( i a ).The effect measurement value of situation ij s is ij r .Every element in the decision matrix is a decision unit, namely: (1)

The effect measurement
The effect measurement is to quantitatively measure the effect generated from the situation.It is a specific measurement of practical effect of the situation by comparative analysis.The effect measurement includes three types, namely: (1) The top effect measurement, Here, ij u is the practical effect value of situation ij s .max u is the maximum practical effect value of all situations i j s .min u is the minimum practical effect value of all situations i j s .0 u is an appointed medium value.
In practice, it is the nature of decision objective that determines the type of measurement.If we pursues for the largest objective value, we can select the top effect measurement.If we want the smallest objective value, we can adopt the bottom effect measurement.If we prefer to a proper value, we can take the medium effect measurement.

The matrix for calculating the integrated effect measurement
Suppose the situation has p objectives.The effect value of objective k is ( ) k ij r and its decision unit is (2) Here in this matrix, ij r is the integrated effect measurement value of situation ij s .It is the final effect value by integrating multiple objectives.If we endow with each objective with average weight, the calculation is:

Make decision
According to the multi-objective integrated decision matrix, we can use two ways to select the situation with the most excellent effect, or select the maximum integrated effect measurement value ij r among the matrix ( )  M .
(1) Row decision.Select the largest integrated effect measurement value

Select evaluation indexes
This paper aims at studying the regional distribution of grain and oil crops in Sichuan province.The crops include rice, wheat, corn, legume, potato, rapeseed, and peanut.Select five evaluation indexes displayed in table 1.According to data in Sichuan Statistical Yearbook in recent four years (Statistics Bureau of Sichuan Province, 2004-2007), we calculate the decision matrix and finally get the integrated effect measurement matrix.

Results of model calculation
According to the similarities of time sequence, get the average of each index based on data of 2003 to 2006.Firstly, calculate the decision matrix of the five evaluation indexes based on model (1).Then, calculate the integrated effect measurement matrix based on model (2).In calculation, we endow the five indexes with average weights.Finally, we get the table 2 (display only integrated effect measurement values).

Make decision
Make decision according to the results of gray situation decision and identify the crops with comparative advantages in different regions.Results are in table 3 (three crops for each region).
Made decision according to the results of gray situation decision and get the sequence of 7 grain and oil crops according to their comparative advantages in the 21 cities (states) in Sichuan province.Table 4 displays the results (list six regions for each crop).

Conclusion
This paper analyzes the regional distribution of grain and oil crops in Sichuan province by the gray situation decision analysis method.Based on data calculation, this paper orders the sequence of grain and oil crops according to their comparative advantages in the 21 cities (states) in Sichuan province.Results show that structures of grain and oil crops with comparative advantages in different regions are similar.Most regions possess comparative advantages in rice, wheat, and corn.The reason may lie in the relatively sound basis of land crops.By ordering the sequence of 7 grain and oil crops' regional integrated measurements in Sichuan province, establish the most appropriate regions for planting 7 grain and oil crops respectively in Sichuan province.By comparing the research result and existing regional distribution of grain and oil crops, we find that existing distribution strays away from this research result to certain degree.Present regional distribution of grain and oil crops is unscientific.
Considering the large population but less cultivated lands, to improve the regional distribution of grain and oil crops in Sichuan province is urgent and also an important issue for establishing regional development programs.In the overall programming distribution in Sichuan province, establish the regional adaptability of each grain and oil crop and increase the planting areas in the region with high adaptability.In the regional programming distribution, establish the comparative advantage of each grain and oil crop in one region and increase the planting area of the crop with high comparative advantage.This paper rightly offers scientific basis for the regional distribution of grain and oil crops in Sichuan province.We should coordinate different relationships, and implement the regional distribution scientifically and reasonably, hoping to realize the goal of ensuring food safety, releasing pressures from limited lands, transferring rural surplus labor powers, optimizing agricultural structure, and driving rural economic development.
can construct the multi-objective integrated decision matrix, namely:

ijr
from the each row of the multi-objective integrated decision matrix ( ) M .The situation ij s is the best, what means the decision j b is the best choice for the incident i a .(2) Column decision.Select the largest integrated effect measurement value ij r from each column of the multi-objective integrated decision matrix ( ) M .The situation ij s is the best, what means the incident i a is most appropriate incident for the decision j b .

Table 1 .
The evaluation indexes for the regional comparison of grain and oil crops in Sichuan province.