由具有变量的比较索引（集合的元素）引起的AMPL ecopy（）错误 [英] AMPL ecopy() error causing by comparison indices (element of set) with variable
本文介绍了由具有变量的比较索引（集合的元素）引起的AMPL ecopy（）错误的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！
问题描述
我是另一个错误，如下所示：
I another bug as you can see below:
Error at _cmdno 8 executing "solve" command
(file ./script/runConfiguration.run, line 5, offset 127):
error processing constraint c1a[2,'o1',1]:
unexpected type 0x14205 in ecopy()
我想是导致与c1a约束中的索引（集合元素）比较的问题。
I guess that the problem causing comparison with the index (element of set) variable in c1a constraint. Is it possible to avoid this bug?
我的新放大器模型：
#sets
#-------------------------------------------------------------------------------------
set K; #index of nodes with group of clients
set N; #nodes
set E; #edges
set O; #objects
#parameters
#-------------------------------------------------------------------------------------
param d {K,O}; #demands for object o
param t {K,O} symbolic; #destination nodes
param r {N,K} binary; #1 if node n is ancestor of node k, 0 otherwise
param a {N,E} binary; #1 if edge begins in vertex, 0 otherwise
param b {N,E} binary; #1 if edge ends in vertex, 0 otherwise
param c {E}; #cost of using an edge
param Hmax; #available capacity for allocation object in proxy servers
#variables
#-------------------------------------------------------------------------------------
var f {N,O} binary; #1 if object saved at node k, 0 otherwise
var x {E,K,O}; #value of the demand realised over edge for object
var s {K,O} symbolic in N; #source nodes
#goal function
#-------------------------------------------------------------------------------------
#The function minimizes cost of routing
#By saving copies at CDN proxies we minimizing all traffic from all demands
#with all objects
minimize goal:
sum{e in E}
sum{k in K}
sum{o in O}
(x[e,k,o]*c[e]);
#constraints
#-------------------------------------------------------------------------------------
subject to c1a {k in K, o in O, n in N: n!=t[k,o]}:
(s[k,o]==n)
==>
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) =
d[k,o]*(1-f[k,o]);
subject to c1b {k in K, o in O, n in N: n!=t[k,o]}:
(s[k,o]!=n)
==>
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) =
0;
subject to c1c {k in K, o in O, n in N: n==t[k,o]}:
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) =
-d[k,o]*(1-f[k,o]);
subject to c2:
sum{k in K}
sum{o in O}
f[k,o] <= Hmax;
subject to c3 {k in K, o in O}:
sum{n in N}
r[n,k]*f[n,o] <= 2;
subject to c4 {o in O}:
f[1,o]=1;
subject to c5 {k in K, o in O}:
s[k,o]=
2-sum{n in N}(r[n,k]*f[n,o])
+(sum{n in N}
(r[n,k]*f[n,o])-1)
*(sum{i in K}(r[i,k]*f[i,o]*i));
subject to c0 {e in E, k in K, o in O}:
x[e,k,o]>=0;
这是非常简单的数据：
#Data file for 'CDN allocation copies' problem simple example
#indices
set K := 2 3 4; #index of nodes with group of clients
set N := 1 2 3 4; #nodes
set E := 1_2 2_3 2_4; #edges
set O := o1; #objects
#parameters
param d (tr): #demands for object o
2 3 4 :=
o1 0 512 512;
#opt= 63 + 75 = 138
param t (tr): #destination nodes
2 3 4 :=
o1 2 3 4;
param r (tr): #1 if node n is ancestor of node k, 0 otherwise
1 2 3 4 :=
2 1 0 0 0
3 1 1 0 0
4 1 1 0 0;
param a (tr): #1 if edge begins in vertex, 0 otherwise
1 2 3 4 :=
1_2 1 0 0 0
2_3 0 1 0 0
2_4 0 1 0 0;
param b (tr): #1 if edge ends in vertex, 0 otherwise
1 2 3 4 :=
1_2 0 1 0 0
2_3 0 0 1 0
2_4 0 0 0 1;
param c := #cost of using an edge
1_2 3
2_3 1
2_4 1;
param Hmax := 1; #available capacity for allocation object in proxy servers
此数据文件描述了具有4个具有此类拓扑的节点的网络：
This data file describe network with 4 nodes with topology like this:
1
|
2
/ \
3 4
这很容易猜测最好的解决方案是仅保存节点2的内容。对象函数= 1024并且f_2，o1 = 1。
It is easy to guess that the best solution is to save only the content of the node 2. The object function = 1024 and f_2,o1=1.
该模型尝试求解Strorage容量分配问题，我在另一篇文章中对此进行了描述：
解决CDN时出现错误分配规则
Whis model try to solve Strorage Capacity Allocation problem, which I described in another my post: Bug when solving CDN allocation rule
推荐答案
我和我的朋友们发现了重新定义CDN SCAP问题的解决方案，如下所示对于CPLEX解析器：
I with my friends found solution for redefine CDN SCAP problem as it shown below, which is applicable for CPLEX resolver:
#Model for 'CDN allocation copies' problem
#sets
#-------------------------------------------------------------------------------------
set K; #index of nodes with group of clients
set N; #nodes
set E; #edges
set O; #objects
#parameters
#-------------------------------------------------------------------------------------
param d {K,O}; #demands for object o
param t {K,O} symbolic; #destination nodes
param r {N,K} binary; #1 if node n is ancestor of node k, 0 otherwise
param a {N,E} binary; #1 if edge begins in vertex, 0 otherwise
param b {N,E} binary; #1 if edge ends in vertex, 0 otherwise
param c {E}; #cost of using an edge
param Hmax; #available capacity for allocation object in proxy servers
#variables
#-------------------------------------------------------------------------------------
var f {N,O} binary; #1 if object saved at node k, 0 otherwise
var x {E,K,O} >= 0; #value of the demand realised over edge for object
var s {K,O} binary; #source nodes
#goal function
#-------------------------------------------------------------------------------------
#The function minimizes cost of routing
#By saving copies at CDN proxies we minimizing all traffic from all demands
#with all objects
minimize goal:
sum{e in E}
sum{k in K}
sum{o in O}
(x[e,k,o]*c[e]);
#constraints
#-------------------------------------------------------------------------------------
subject to c1a {k in K, o in O, n in N: n==1}:
s[k,o] = 0
==>
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) -
d[k,o]*(1-f[k,o]) = 0
else
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) =
0;
subject to c1b1 {k in K, o in O, n in N: n!=t[k,o] and n!=1}:
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) -
r[n,k]*d[k,o]*(1-f[k,o]) <= 0;
subject to c1b2 {k in K, o in O, n in N: n!=t[k,o] and n!=1}:
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) -
r[n,k]*d[k,o]*s[k,o] <= 0;
subject to c1b3 {k in K, o in O, n in N: n!=t[k,o] and n!=1}:
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) -
r[n,k]*d[k,o]*f[n,o] <= 0;
subject to c1c {k in K, o in O, n in N: n==t[k,o]}:
sum{e in E}
(a[n,e]*x[e,k,o]) -
sum{e in E}
(b[n,e]*x[e,k,o]) =
-d[k,o]*(1-f[k,o]);
subject to c2:
sum{k in K}
sum{o in O}
f[k,o] <= Hmax;
subject to c3 {k in K, o in O}:
sum{n in N}
r[n,k]*f[n,o] <= 2;
subject to c4 {o in O}:
f[1,o]=1;
subject to c5 {k in K, o in O}:
s[k,o]=sum{n in N}(r[n,k]*f[n,o])-1;
这篇关于由具有变量的比较索引（集合的元素）引起的AMPL ecopy（）错误的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！
查看全文
