LINE Solver
MATLAB API documentation
Loading...
Searching...
No Matches
solver_mna_open.m
1function [Q,U,R,T,C,X,lG,totiter] = solver_mna_open(sn, options)
2
3config = options.config;
4config.space_max = 32;
5if ~isfield(config, 'dep_scv')
6 config.dep_scv = 'qna'; % 'qna' for Whitt formula, 'etaqa' for QBD joint moments
7end
8
9K = sn.nclasses;
10rt = sn.rt;
11S = 1./sn.rates;
12scv = sn.scv; scv(isnan(scv))=0;
13
14PH = sn.proc;
15I = sn.nnodes;
16M = sn.nstations;
17C = sn.nchains;
18V = cellsum(sn.visits);
19Q = zeros(M,K);
20%QN_1 = Q+Inf;
21
22U = zeros(M,K);
23R = zeros(M,K);
24T = zeros(M,K);
25X = zeros(1,K);
26
27lambda = zeros(1,C);
28
29it = 0;
30pie = {};
31D0 = {};
32
33% get service process
34for ist=1:M
35 switch sn.sched(ist)
36 case {SchedStrategy.FCFS, SchedStrategy.INF,SchedStrategy.PS}
37 for k=1:K
38 pie{ist}{k} = map_pie(PH{ist}{k});
39 D0{ist,k} = PH{ist}{k}{1};
40 if any(isnan(D0{ist,k}))
41 D0{ist,k} = -GlobalConstants.Immediate;
42 pie{ist}{k} = 1;
43 PH{ist}{k} = map_exponential(GlobalConstants.Immediate);
44 end
45 end
46 end
47end
48
49a1 = zeros(M,K);
50a2 = zeros(M,K);
51a1_1 = a1+Inf;
52a2_1 = a2+Inf;
53d2 = zeros(M,1);
54f2 = zeros(M*K,M*K);
55for ist=1:M
56 for jst=1:M
57 if sn.nodetype(sn.stationToNode(jst)) ~= NodeType.Source
58 for r=1:K
59 for s=1:K
60 if rt((ist-1)*K+r, (jst-1)*K+s)>0
61 f2((ist-1)*K+r, (jst-1)*K+s) = 1; % C^2ij,r
62 end
63 end
64 end
65 end
66 end
67end
68lambdas_inchain = cell(1,C);
69scvs_inchain = cell(1,C);
70d2c = [];
71for c=1:C
72 inchain = sn.inchain{c};
73 sourceIdx = sn.refstat(inchain(1));
74 lambdas_inchain{c} = sn.rates(sourceIdx,inchain);
75 scvs_inchain{c} = scv(sourceIdx,inchain);
76 lambda(c) = sum(lambdas_inchain{c}(isfinite(lambdas_inchain{c})));
77 d2c(c) = qna_superpos(lambdas_inchain{c},scvs_inchain{c});
78 T(sourceIdx,inchain') = lambdas_inchain{c};
79
80end
81d2(sourceIdx)=d2c(sourceIdx,:)*lambda'/sum(lambda);
82
83%% main iteration
84
85while (max(max(abs(a1_1-a1))) > options.iter_tol || max(max(abs(a2_1-a2))) > options.iter_tol )&& it <= options.iter_max %#ok<max>
86 it = it + 1;
87 %QN_1 = Q;
88 a1_1 = a1;
89 a2_1 = a2;
90 % update throughputs at all stations
91 if it==1
92 for c=1:C
93 inchain = sn.inchain{c};
94 for m=1:M
95 T(m,inchain) = V(m,inchain) .* lambda(c);
96 end
97 end
98 end
99
100 % superposition
101 for ist=1:M
102 a1(ist,:) = 0;
103 a2(ist,:) = 0;
104 lambda_i = sum(T(ist,:));
105 for jst=1:M
106 for r=1:K
107 for s=1:K
108 a1(ist,r) = a1(ist,r) + T(jst,s)*rt((jst-1)*K+s, (ist-1)*K+r);
109 a2(ist,r) = a2(ist,r) + (1/lambda_i) * f2((jst-1)*K+s, (ist-1)*K+r)*T(jst,s)*rt((jst-1)*K+s, (ist-1)*K+r);
110 end
111 end
112 end
113 end
114
115 % update flow trhough queueing station
116 for ind=1:I
117 if sn.isstation(ind)
118 ist = sn.nodeToStation(ind);
119
120 switch sn.sched(ist)
121 case SchedStrategy.INF
122 for r=1:K
123 for s=1:K
124 d2(ist,s) = a2(ist,s);
125 end
126 end
127 for c=1:C
128 inchain = sn.inchain{c};
129 for k=inchain
130 T(ist,k) = a1(ist,k);
131 U(ist,k) = S(ist,k)*T(ist,k);
132 Q(ist,k) = T(ist,k).*S(ist,k)*V(ist,k);
133 R(ist,k) = Q(ist,k)/T(ist,k);
134 end
135 end
136 case SchedStrategy.PS
137 for c=1:C
138 inchain = sn.inchain{c};
139 for k=inchain
140 TN(ist,k) = lambda(c)*V(ist,k);
141 UN(ist,k) = S(ist,k)*TN(ist,k);
142 end
143 %Nc = sum(sn.njobs(inchain)); % closed population
144 Uden = min([1-GlobalConstants.FineTol,sum(UN(ist,:))]);
145 for k=inchain
146 %QN(ist,k) = (UN(ist,k)-UN(ist,k)^(Nc+1))/(1-Uden); % geometric bound type approximation
147 QN(ist,k) = UN(ist,k)/(1-Uden);
148 RN(ist,k) = QN(ist,k)/TN(ist,k);
149 end
150 end
151 case {SchedStrategy.FCFS}
152 mu_ist = sn.rates(ist,1:K);
153 mu_ist(isnan(mu_ist))=0;
154 rho_ist_class = a1(ist,1:K)./(GlobalConstants.FineTol+sn.rates(ist,1:K));
155 rho_ist_class(isnan(rho_ist_class))=0;
156 lambda_ist = sum(a1(ist,:));
157 mi = sn.nservers(ist);
158 rho_ist = sum(rho_ist_class) / mi;
159 if rho_ist < 1-options.tol
160 if strcmp(config.dep_scv, 'etaqa') && mi == 1
161 % ETAQA-based departure SCV via QBD joint moments
162 try
163 % fit aggregate arrival MAP from parametric info
164 arri_agg = APH.fitMeanAndSCV(1/lambda_ist, sum(a2(ist,:))).getProcess;
165 serv_agg = APH.fitMeanAndSCV(1/sum(mu_ist(mu_ist>0).*a1(ist,mu_ist>0))/lambda_ist, ...
166 sum(a1(ist,:).*scv(ist,:))/lambda_ist).getProcess;
167 JM = qbd_depproc_jointmom(arri_agg, serv_agg, [1,0; 2,0]);
168 E1 = JM(1); E2 = JM(2);
169 d2(ist) = (E2 - E1^2) / E1^2;
170 catch
171 % fall back to QNA formula on failure
172 for k=1:K
173 mubar(ist) = lambda_ist ./ rho_ist;
174 c2(ist) = -1;
175 for r=1:K
176 if mu_ist(r)>0
177 c2(ist) = c2(ist) + a1(ist,r)/lambda_ist * (mubar(ist)/mi/mu_ist(r))^2 * (scv(ist,r)+1 );
178 end
179 end
180 end
181 d2(ist) = 1 + rho_ist^2*(c2(ist)-1)/sqrt(mi) + (1 - rho_ist^2) *(sum(a2(ist,:))-1);
182 end
183 else
184 % QNA Whitt formula
185 for k=1:K
186 mubar(ist) = lambda_ist ./ rho_ist;
187 c2(ist) = -1;
188 for r=1:K
189 if mu_ist(r)>0
190 c2(ist) = c2(ist) + a1(ist,r)/lambda_ist * (mubar(ist)/mi/mu_ist(r))^2 * (scv(ist,r)+1 );
191 end
192 end
193 end
194 d2(ist) = 1 + rho_ist^2*(c2(ist)-1)/sqrt(mi) + (1 - rho_ist^2) *(sum(a2(ist,:))-1);
195 end
196 else
197 for k=1:K
198 Q(ist,k) = sn.njobs(k);
199 end
200 d2(ist) = 1;
201 end
202 for k=1:K
203 T(ist,k) = a1(ist,k);
204 U(ist,k) = T(ist,k) * S(ist,k) /sn.nservers(ist);
205
206 end
207 end
208
209 else % not a station
210 switch sn.nodetype(ind)
211 case NodeType.Fork
212 line_error(mfilename,'Fork nodes not supported yet by QNA solver.');
213 end
214 end
215 end
216
217
218 % splitting - update flow scvs
219 for ist=1:M
220 for jst=1:M
221 if sn.nodetype(sn.stationToNode(jst)) ~= NodeType.Source
222 for r=1:K
223 for s=1:K
224 if rt((ist-1)*K+r, (jst-1)*K+s)>0
225 f2((ist-1)*K+r, (jst-1)*K+s) = 1 + rt((ist-1)*K+r, (jst-1)*K+s) * (d2(ist)-1);
226 end
227 end
228 end
229 end
230 end
231 end
232end
233
234
235for ind=1:I
236 if sn.isstation(ind)
237 ist = sn.nodeToStation(ind);
238 switch sn.sched(ist)
239 case {SchedStrategy.FCFS}
240 mu_ist = sn.rates(ist,1:K);
241 mu_ist(isnan(mu_ist))=0;
242 rho_ist_class = a1(ist,1:K)./(GlobalConstants.FineTol+sn.rates(ist,1:K));
243 rho_ist_class(isnan(rho_ist_class))=0;
244 lambda_ist = sum(a1(ist,:));
245 mi = sn.nservers(ist);
246 rho_ist = sum(rho_ist_class) / mi;
247 if rho_ist < 1-options.tol
248 for k=1:K
249 if a1(ist,k)==0
250 arri_class = map_exponential(Inf);
251 else
252 arri_class = APH.fitMeanAndSCV(1/a1(ist,k),a2(ist,k)).getProcess; % MMAP repres of arrival process for class k at node ist
253 %arri_class = Erlang.fit(1/a1(ist,k),a2(ist,k)).getProcess;
254 %arri_class = map_exponential(1/a1(ist,k));
255 arri_class = {arri_class{1},arri_class{2},arri_class{2}};
256 end
257 if k==1
258 arri_node = arri_class;
259 else
260 arri_node = mmap_super(arri_node,arri_class, 'default');
261
262 %arri_node = mmap_super_safe({arri_node,arri_class}, config.space_max, 'default'); % combine arrival process from different class
263 end
264 end
265 Qret = cell(1,K);
266 [Qret{1:K}] = MMAPPH1FCFS({arri_node{[1,3:end]}}, {pie{ist}{:}}, {D0{ist,:}}, 'ncMoms', 1);
267 Q(ist,:) = cell2mat(Qret);
268 else
269 for k=1:K
270 Q(ist,k) = sn.njobs(k);
271 end
272 end
273 for k=1:K
274 R(ist,k) = Q(ist,k) ./ T(ist,k);
275 end
276 end
277
278 end
279end
280
281C = sum(R,1);
282Q = abs(Q);
283Q(isnan(Q))=0;
284U(isnan(U))=0;
285R(isnan(R))=0;
286C(isnan(C))=0;
287X(isnan(X))=0;
288lG = 0;
289totiter = it;
290end
291
292
293function [d2]=qna_superpos(lambda,a2)
294a2 = a2(isfinite(lambda));
295lambda = lambda(isfinite(lambda));
296d2 = a2(:)'*lambda(:) / sum(lambda);
297end