标签：procedure form angular distrib ios store community use represent
Concepts：
1）combination of random and deterministic approaches 随机和确定性方法的组合
2）the concept of clustering 聚类的概念
3）the concept of a systematic evolution of a complex of points spanning the space, in the direction of global improvement 在全局优化的方向，
跨空间点的复杂系统演化的概念
4） the concept of competitive evolution 竞争进化的概念
SCE=CRS with the concept of competitive evolution + complex shuffling
The philosophy: The ampled points(s in number) constitute a population. The population is partitioned into several communities(complexes), each of which is permitted to evolve independently. After a certain number of generations, the communities are forced to mix, and new communities are formed though a process of shuffling. This procedure enhances survivability by a sharing of the information gained independently by each community.
Step 0. Initialize. p>=1 : number of complexes m>=n+1 : number of points in each complex. the sample size s=p*m.
Step 1. Generate Sample. Sample s points x1,...,xs in the feasible space omega. Compute the function value fi at each point xi.
Step 2. Rank Points. Sort the s points in order of increasing function value. Store them in an arry D={xi,fi, i=1,...,s}, so that i=1 represents the point with the smallest function value.
Step 3. Partition into Complexes. Partition D into p complexes A1,...,AP, each containing m points, such that:
Ak={xkj,fkj| xkj=xk+p(j-1), fkj=fk+p(j-1), j=1,...,m)} .
Step 4. Evolve Each Complex. Evolve each complex Ak, k=1,...,p according to the competitive complex evolution(CCE) algorithm outlined separately.
Step 5. Shuffle Complexes. Replace A1,...,AP into D, such that D={Ak, k=1,...,p}. Sort D in order of increasing function value.
Step 6. Check Convergence. If the convergence criteria are satisfied, stop; otherwise, return to Step 3.
The competitive complex evolution(CCE) algorithm required for the evolution of each complex in Step 4 of the SCE method is presented below
Step 0. Initialize. Select q, α, and β， where 2<=q<=m, α>=1, and β>=1.
Step 1. Assign Weights. Assign a triangular probability distribution to Ak;
pi=2(m+1-i)/m(m+1), i=1,...,m.
The point xk1 has the highest probability, ρ1=2/m+1. The point xkm has the lowest probability, ρm=2/m(m+1).
Step 2. Select Parents. Randomly choose q distinct points 随机选择q个不同点 u1,...,uq from Ak according to the probability distribution specified above(根据上面指定的概率分布) the q points define a subcomplex. Store them in array B={ui,vi, i=1,...,q}, where vj is the function value associated with point uj. Store in L the locations of Ak which are used to construct B.
Step 3. Generate Offspring.
Step 4. Replace Parents by Offspring. Replace B into Ak using the original locatios stored in L. Sort Ak in order of increasing function value.
Step 5. Iterate. Repeat Steps 1 though 4 β times, where β>=1 is a user-specified parameter which determines how many offspring should be generated.
SCE
标签：procedure form angular distrib ios store community use represent
原文地址：http://www.cnblogs.com/tomatokely/p/7748137.html
