[求助]MATLAB中GA工具箱VECTORIZE 是干什么

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[求助]MATLAB中GA工具箱VECTORIZE 是干什么的？ 我是一个新手，对matlab不怎么熟练，正在学习ga，请教一些问题，谢谢～
MATLAB中GA工具箱第一个DEMO的最后一个方面的讲到的vectorize是干什么？
该程序源代码如下
%% Vectorizing your fitness function
% Consider the previous fitness function again:
%
% f(x) = a * (x(1)^2 - x(2)) ^2 + (b - x(1))^2;
%
% By default, the GA solver only passes in one point at a time to the
% fitness function. However, sometimes speed up can be achieved if the
% fitness function is vectorized to take a set of points and return a set
% of function values.
%
% For example if the solver wants to evaluate a set of five points in one
% call to this fitness function, then it will call the function with a
% matrix of size 5-by-2, i.e. , 5 rows and 2 columns (recall 2 is the number
% of variables).
%
% Create an M-file called vectorized_fitness.m with the following code:
%
% function y = vectorized_fitness(x,a,b)
% y = zeros(size(x,1),1); %Pre-allocate y
% for i = 1:size(x,1)
% x1 = x(i,1);
% x2 = x(i,2);
% y(i) = a * (x1^2 - x2) ^2 + (b - x1)^2;
% end
%
% This vectorized version of the fitness function takes a matrix x with
% an arbitrary number of points, the rows of x, and returns a column
% vector y of length the same as the number of rows of x.
%
% We need to specify that the fitness function is vectorized using the
% options structure created using GAOPTIMSET. The options structure is
% passed in as the third argument.

FitnessFunction = @(x) vectorized_fitness(x,100,1);
numberOfVariables = 2;
options = gaoptimset('Vectorized','on');
[x,fval] = ga(FitnessFunction,numberOfVariables,options)

是否是进行初始化？（其中x是一个N维向量，一开始的值是初始值）但是GA需要初始化吗？

另外我在《测试智能信息处理》中看到一个对Griewangk函数的极小化
程序1：Griewangk函数
function[eval]=gw(sol)
numv=size(sol,2);
x=sol*(1:numv);
for i=1:numv
multi=multi*cos(x(i)/sqrt(i));
end
eval=sum(x.^2/4000)-multi+1;

程序2:Griewangk函数适应度代码
function[sol,eval]=gwmin(sol,options)
numv=size(sol,2)-1;
x=sol(1:numv);
eval=gw(x);
eval=-eval;

遗传算法求解：
bounds=ones(6,1)*[-512 512];
[p,endPop,bestSols,trace]=ga(bounds,'gwmin');
plot(trace(:,1),trace(:,3),'b-')
hold on
plot(trace(:,1),trace(:,2),'b-')
xlabel('Generation');
ylabel=('Fitness');

输出解的变化和种群平均值变化并输出最优解
p=0.002
-0.004
-0.003
0.006
-0.0022
0.0002

我的疑问：在程序2:Griewangk函数适应度代码中的options是什么？我没有输入啊？
sol是解的值吗？eval是适应度函数吗？
我在matlab中进行到[p,endPop,bestSols,trace]=ga(bounds,'gwmin');
就没法进行了：提示
??? Error using ==> gads\private\validate>validNumberofVariables
Number of variables (NVARS) must be a positive number.

Error in ==> gads\private\validate at 43
validNumberofVariables(o.GenomeLength);

Error in ==> ga at 153
[GenomeLength,FitnessFcn,options] = validate(GenomeLength,FitnessFcn,options);
请问是什么意思啊？
另外最优解p有那么多，他们都代表解吗？因为他么都趋近于零所以最优解p=0对吗？

但是为什么vectorize就只输出一个解呢？
谢谢！