Infeasible Status and -Inf optimal value when I use MOSEK solver

1

My problem involves SOC constraints. When I operate the programme, the output shows Infeasible Status and -Inf optimal value. I really do not know what’s the mistakes of my code. Who can help me? The details about the output are shown as:

Calling Mosek 8.0.0.60: 4450 variables, 1938 equality constraints
For improved efficiency, Mosek is solving the dual problem.

MOSEK Version 8.0.0.60 (Build date: 2017-3-1 13:09:33)
Copyright © MOSEK ApS, Denmark. WWW: mosek.com
Platform: Windows/64-X86

MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col ‘’ (651) of matrix ‘A’.
MOSEK warning 710: #1 (nearly) zero elements are specified in sparse col ‘’ (723) of matrix ‘A’.
MOSEK warning 710: #2 (nearly) zero elements are specified in sparse col ‘’ (852) of matrix ‘A’.
MOSEK warning 710: #2 (nearly) zero elements are specified in sparse col ‘’ (924) of matrix ‘A’.
MOSEK warning 710: #4 (nearly) zero elements are specified in sparse col ‘’ (2326) of matrix ‘A’.
MOSEK warning 710: #4 (nearly) zero elements are specified in sparse col ‘’ (2330) of matrix ‘A’.
MOSEK warning 710: #2 (nearly) zero elements are specified in sparse col ‘’ (2331) of matrix ‘A’.
MOSEK warning 710: #2 (nearly) zero elements are specified in sparse col ‘’ (2335) of matrix ‘A’.
MOSEK warning 710: #6 (nearly) zero elements are specified in sparse col ‘’ (2341) of matrix ‘A’.
MOSEK warning 710: #6 (nearly) zero elements are specified in sparse col ‘’ (2345) of matrix ‘A’.
Warning number 710 is disabled.
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1026).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1027).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1028).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1029).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1030).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1031).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1032).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1033).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1034).
MOSEK warning 57: A large value of 5.0e+009 has been specified in cx for variable ‘’ (1035).
Warning number 57 is disabled.
Problem
Name :
Objective sense : min
Type : CONIC (conic optimization problem)
Constraints : 1938
Cones : 808
Scalar variables : 4450
Matrix variables : 0
Integer variables : 0

Optimizer started.
Conic interior-point optimizer started.
Presolve started.
Linear dependency checker started.
Linear dependency checker terminated.
Eliminator started.
Freed constraints in eliminator : 36
Eliminator terminated.
Eliminator - tries : 1 time : 0.00
Lin. dep. - tries : 1 time : 0.00
Lin. dep. - number : 0
Presolve terminated. Time: 0.02
Optimizer - threads : 4
Optimizer - solved problem : the primal
Optimizer - Constraints : 1083
Optimizer - Cones : 808
Optimizer - Scalar variables : 3515 conic : 2844
Optimizer - Semi-definite variables: 0 scalarized : 0
Factor - setup time : 0.01 dense det. time : 0.00
Factor - ML order time : 0.01 GP order time : 0.00
Factor - nonzeros before factor : 5182 after factor : 9351
Factor - dense dim. : 0 flops : 2.45e+005
ITE PFEAS DFEAS GFEAS PRSTATUS POBJ DOBJ MU TIME
0 3.0e+000 3.6e+006 2.0e+008 0.00e+000 -1.304670427e+013 0.000000000e+000 1.0e+000 0.03
1 1.7e+000 2.0e+006 8.6e+007 -1.00e+000 -1.304670891e+013 2.887641129e+003 5.7e-001 0.05
2 4.2e-001 4.9e+005 1.0e+007 -1.00e+000 -1.304675388e+013 6.942858172e+002 1.4e-001 0.05
3 1.3e-001 1.5e+005 1.7e+006 -1.00e+000 -1.304698191e+013 1.128382913e+003 4.2e-002 0.05
4 5.4e-002 6.3e+004 4.6e+005 -1.00e+000 -1.304745310e+013 2.268092315e+003 1.8e-002 0.05
5 1.8e-002 2.1e+004 9.3e+004 -1.00e+000 -1.304900792e+013 2.494568702e+003 6.0e-003 0.06
6 7.6e-003 8.9e+003 2.5e+004 -1.00e+000 -1.305229305e+013 1.206513090e+003 2.5e-003 0.06
7 2.1e-003 2.5e+003 3.7e+003 -1.00e+000 -1.306583266e+013 6.787879534e+002 7.0e-004 0.06
8 5.4e-004 6.3e+002 4.6e+002 -1.00e+000 -1.311040617e+013 3.751377664e+001 1.8e-004 0.06
9 1.5e-004 1.7e+002 6.7e+001 -1.01e+000 -1.315043073e+013 -2.895655984e+002 4.9e-005 0.06
10 3.8e-005 4.5e+001 8.9e+000 -1.00e+000 -1.314795385e+013 -4.654488013e+002 1.3e-005 0.06
11 1.0e-005 1.2e+001 1.3e+000 -1.00e+000 -1.316515934e+013 -5.892896757e+002 3.4e-006 0.06
12 3.3e-006 3.8e+000 2.2e-001 -1.00e+000 -1.321239120e+013 -6.462972245e+002 1.1e-006 0.08
13 1.2e-006 1.4e+000 5.0e-002 -1.00e+000 -1.332090459e+013 -6.728525069e+002 4.0e-007 0.08
14 4.3e-007 5.0e-001 1.0e-002 -1.00e+000 -1.363198320e+013 -6.953034491e+002 1.4e-007 0.08
Interior-point optimizer terminated. Time: 0.08.

MOSEK DUAL INFEASIBILITY REPORT.

Problem status: The problem is dual infeasible
Optimizer terminated. Time: 0.08

Interior-point solution summary
Problem status : DUAL_INFEASIBLE
Solution status : DUAL_INFEASIBLE_CER
Primal. obj: -1.8932700620e+006 nrm: 2e+007 Viol. con: 2e+000 var: 0e+000 cones: 0e+000
Optimizer summary
Optimizer - time: 0.08
Interior-point - iterations : 14 time: 0.08
Basis identification - time: 0.00
Primal - iterations : 0 time: 0.00
Dual - iterations : 0 time: 0.00
Clean primal - iterations : 0 time: 0.00
Clean dual - iterations : 0 time: 0.00
Simplex - time: 0.00
Primal simplex - iterations : 0 time: 0.00
Dual simplex - iterations : 0 time: 0.00
Mixed integer - relaxations: 0 time: 0.00

Status: Infeasible
Optimal value (cvx_optval): -Inf

1 Like
2

Here, I also paste my code:

clc
clear all
close all
K = 4;
E = 3;
wk=[-100 0 50 180; -100 100 0 180];
we=[-180 20 160;0 170 -100];
dh=100;
V_max=50;
T = 5;
delta_t=0.5;
N = T/delta_t;
luo_0 = 10^(-60/10);
delta = 1e-6;
epsluo_u = 1e-14;
siga = 10000;
k_oula = 0.58;
f_max = 510^9;
fTD_max = 310^9;
C_k = 10^3;
k_TD=1e-27;
Pk_max = 0.00110^(30/10);
Pu_J_max = 0.00110^(30/10);
H_J=60;
H_H=100;
kesi = 0.5;
qr_J=zeros(2,N);
qr_H=zeros(2,N);
sitaslot=linspace(0,2pi,N);
r_H=20;
r_J=20;
qr_J = [r_Jsin(sitaslot);r_Jcos(sitaslot)];
qr_H = [r_Hsin(sitaslot+pi);r_Hcos(sitaslot+pi)];
p_kr = 0.01Pk_maxones(K,N);
p_jr = 0.01Pu_J_maxones(1,N);
alpha_km_r = zeros(KK,N);
D_khr = zeros(K,N);
D_jer = zeros(E,N);
D_jhr = zeros(1,N);
D_ke = zeros(K,E);
for n=1:N
for k=1:K
D_khr(k,n) = H_H^2 + norm(qr_H(:,n)-wk(:,k)).^2;
end
for e=1:E
D_jer(e,n) = H_J^2 + norm(qr_J(:,n)-we(:,e)).^2;
end
D_jhr(n) = (H_J-H_H)^2 + norm(qr_J(:,n)-qr_H(:,n)).^2;
end
belta_k_r = D_khr;

for k=1:K
for e=1:E
D_ke(k,e) = norm(wk(:,k)-we(:,e))^2;
end
end
D_mhr = D_khr;
for k=1:K
for n=1:N
alpha_km_r((k-1)K+1 : Kk, n) = (D_khr(:,n) > D_khr(k,n));
end
end
alpha_mk_r = 1 - alpha_km_r;
alpha_ke1 = zeros(KK,N);
alpha_ke2 = zeros(KK,N);
alpha_ke3 = zeros(KK,N);
g_ke = zeros(KE,N);

for e=1:E
for k=1:K
if e==1
for n=1:N
alpha_ke1((k-1)K+1 : Kk, n) = (D_ke(:,e) > D_ke(k,e));
end
end
if e==2
for n=1:N
alpha_ke2((k-1)K+1 : Kk, n) = (D_ke(:,e) > D_ke(k,e));
end
end
if e==3
for n=1:N
alpha_ke3((k-1)K+1 : Kk, n) = (D_ke(:,e) > D_ke(k,e));
end
end
end
end

for k=1:K
for e=1:E
for n=1:N
g_ke(k + (e-1)K, n) = luo_0D_ke(k,e)^(-1.5)*kesi;
end
end
end
h_khr = luo_0./D_khr;
h_mhr = h_khr;
h_jhr = luo_0./D_jhr;
h_jer = luo_0./D_jer;
pai_1kr = zeros(K,N);
temp1 = p_kr.*h_mhr;
for k=1:K
if k==1
temp2=alpha_km_r(1:K,:).*temp1;
pai_1kr(1,:slight_smile: = sum(temp2)+ h_jhr.p_jr + epsluo_u;
end
if k==2
temp3=alpha_km_r(K+1:2K,:).temp1;
pai_1kr(2,:slight_smile: = sum(temp3)+ h_jhr.p_jr + epsluo_u;
end
if k==3
temp4=alpha_km_r(2K+1:3K,:).temp1;
pai_1kr(3,:slight_smile: = sum(temp4) + h_jhr.p_jr + epsluo_u;
end
if k==4
temp5=alpha_km_r(3K+1:4K,:).*temp1;
pai_1kr(4,:slight_smile: = sum(temp5)+ h_jhr.*p_jr + epsluo_u;
end
end
gamma_khr = p_kr.*h_khr./(pai_1kr);
t_kr = gamma_khr;
bar_pai_1kr = D_khr;
pai_2kr = t_kr.*pai_1kr;
bar_pai_2mr = p_kr.*h_khr;
bar_pai_3jh_r = p_jr.*h_jhr;
yita_1mr=D_khr;
yita_2mr=D_jhr;

bar_t_ke1_r = zeros(K,N);
bar_t_ke2_r = zeros(K,N);
bar_t_ke3_r = zeros(K,N);
Kesi_ke1_r = zeros(K,N);
Kesi_ke2_r = zeros(K,N);
Kesi_ke3_r = zeros(K,N);
bar_Kesi_je_r = zeros(E,N);

for k=1:K
bar_t_ke1_r(k,:slight_smile: = p_kr(k,:).*g_ke(k,:)./(sum( p_kr.*alpha_ke1((k-1)K+1:kK,:).*g_ke(1:K,:slight_smile: ) + p_jr.*h_jer(1,:slight_smile: + epsluo_u); %for e1
Kesi_ke1_r(k,:slight_smile: = sum( p_kr.*alpha_ke1((k-1)K+1:kK,:).*g_ke(1:K,:slight_smile: ) + p_jr.*h_jer(1,:slight_smile: + epsluo_u;
bar_t_ke2_r(k,:slight_smile: = p_kr(k,:).*g_ke(k+K,:)./(sum( p_kr.*alpha_ke2((k-1)K+1:kK,:).g_ke(K+1:2K,:slight_smile: ) + p_jr.*h_jer(2,:slight_smile: + epsluo_u);%for e2
Kesi_ke2_r(k,:slight_smile: = sum( p_kr.*alpha_ke2((k-1)K+1:kK,:).g_ke(K+1:2K,:slight_smile: ) + p_jr.*h_jer(2,:slight_smile: + epsluo_u;
bar_t_ke3_r(k,:slight_smile: = p_kr(k,:).g_ke(k+2K,:)./(sum( p_kr.alpha_ke3((k-1)K+1:kK,:).g_ke(2K+1:3K,:slight_smile: ) + p_jr.*h_jer(3,:slight_smile: + epsluo_u);%for e3
Kesi_ke3_r(k,:slight_smile: = sum( p_kr.alpha_ke3((k-1)K+1:kK,:).g_ke(2K+1:3K,:slight_smile: ) + p_jr.*h_jer(3,:slight_smile: + epsluo_u;
end

for e=1:E
bar_Kesi_je_r(e,:slight_smile: = p_jr.h_jer(e,:);
end
tau_je_r = D_jer;
alpha_km_wave = zeros(KK,N);
lamada1_km = 1ones(KK,N);
lamada2_km = 1ones(KK,N);
lamada3_km = 1ones(KK,N);

for k=1:K
   alpha_km_wave= (alpha_km_r+alpha_km_r.^2+siga*lamada1_km+siga*lamada2_km.*alpha_km_r)./(1 + alpha_km_r.^2); % step 1: solve lpha_k_wave by fixed other variables
end
 
cvx_solver Mosek   
cvx_begin 
variable Sk   
variable sita_1k_opt(K,N)  
variable sita_2k_opt(K,N) 
variable sita_3k_opt(K,N) 
variable tk_opt(K,N) 
variable pj_opt(1,N)
variable pk_opt(K,N) 
variable bar_tke_opt(K*E,N) 
variable alpha_km_opt(K*K,N)
variable fk_opt(K,N) 
variable qH(2,N)  
variable qJ(2,N)
variable pai_1k_opt(K,N)
variable pai_2k_opt(K,N)
variable bar_pai_1k_opt(K,N)
variable bar_pai_2m_opt(K,N)
variable bar_pai_3jh_opt(1,N)
variable yita_1m_opt(K,N)
variable yita_2m_opt(1,N)
variable Rk_loc_opt(K,N)
variable Kesi_ke_opt(K*E,N)
variable tau_ke_opt(E,N)
variable bar_Kesi_je_opt(E,N)
variable belta_k_opt(K,N)

expression alpha_mk_opt(K*K,N)
alpha_mk_opt = 1-alpha_km_opt;

maximize (Sk)

subject  to

      Sk >= 0;
    
    1/N*sum(sita_1k_opt + Rk_loc_opt,2) >= Sk;
    sita_1k_opt <= sita_2k_opt - sita_3k_opt;        
    
    -sita_2k_opt >= rel_entr_quad(1,1 + tk_opt)/log(2);    

    sita_3k_opt >= log2(1+bar_t_ke1_r) + 1/log(2)./(1+bar_t_ke1_r).*(bar_tke_opt((1-1)*K+1:1*K,:)-bar_t_ke1_r);   
    sita_3k_opt >= log2(1+bar_t_ke2_r) + 1/log(2)./(1+bar_t_ke2_r).*(bar_tke_opt((2-1)*K+1:2*K,:)-bar_t_ke2_r);  
    sita_3k_opt >= log2(1+bar_t_ke3_r) + 1/log(2)./(1+bar_t_ke3_r).*(bar_tke_opt((3-1)*K+1:3*K,:)-bar_t_ke3_r);        

    for n=1:N
        for k=1:K
            if k==1 % k = 1
                i=[2 3 4];
                norm([sum((alpha_km_r(i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(i,n)-bar_pai_2m_opt(i,n))/4 - (alpha_km_r(i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2  - epsluo_u/2 - 1/2 + pai_1k_opt(k,n)/2, ...
                    (alpha_km_opt(2,n)+bar_pai_2m_opt(2,n))/2, (alpha_km_opt(3,n)+bar_pai_2m_opt(3,n))/2, (alpha_km_opt(4,n)+bar_pai_2m_opt(4,n))/2 ]) <= sum((alpha_km_r(i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(i,n)-bar_pai_2m_opt(i,n))/4 ...
                    - (alpha_km_r(i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2  +  pai_1k_opt(k,n)/2- epsluo_u/2  + 1/2;                   
            end
            if k==2
               i=[1 3 4];
                norm([sum((alpha_km_r(K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(K+i,n)-bar_pai_2m_opt(i,n))/4 - (alpha_km_r(K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2 - epsluo_u/2 - 1/2 + pai_1k_opt(k,n)/2, ...
                    (alpha_km_opt(5,n)+bar_pai_2m_opt(1,n))/2, (alpha_km_opt(7,n)+bar_pai_2m_opt(3,n))/2, (alpha_km_opt(8,n)+bar_pai_2m_opt(4,n))/2 ]) <= sum((alpha_km_r(K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(K+i,n)-bar_pai_2m_opt(i,n))/4 ...
                    - (alpha_km_r(K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2  +  pai_1k_opt(k,n)/2 - epsluo_u/2 + 1/2 ;      
            end
            if k==3
                i=[1 2 4];
                norm([sum((alpha_km_r(2*K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(2*K+i,n)-bar_pai_2m_opt(i,n))/4 - (alpha_km_r(2*K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2 - epsluo_u/2 - 1/2 + pai_1k_opt(k,n)/2, ...
                    (alpha_km_opt(9,n)+bar_pai_2m_opt(1,n))/2, (alpha_km_opt(10,n)+bar_pai_2m_opt(2,n))/2, (alpha_km_opt(12,n)+bar_pai_2m_opt(4,n))/2 ]) <= sum((alpha_km_r(2*K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(2*K+i,n)-bar_pai_2m_opt(i,n))/4 ...
                    - (alpha_km_r(2*K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2  +  pai_1k_opt(k,n)/2 - epsluo_u/2 + 1/2;  
            end
            if k==4
                i=[1 2 3];
                norm([sum((alpha_km_r(3*K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(3*K+i,n)-bar_pai_2m_opt(i,n))/4 - (alpha_km_r(3*K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2 - epsluo_u/2 - 1/2 + pai_1k_opt(k,n)/2, ...
                    (alpha_km_opt(13,n)+bar_pai_2m_opt(1,n))/2, (alpha_km_opt(14,n)+bar_pai_2m_opt(2,n))/2, (alpha_km_opt(15,n)+bar_pai_2m_opt(3,n))/2 ]) <= sum((alpha_km_r(3*K+i,n)-bar_pai_2mr(i,n)).*(alpha_km_opt(3*K+i,n)-bar_pai_2m_opt(i,n))/4 ...
                    - (alpha_km_r(3*K+i,n)-bar_pai_2mr(i,n)).^2/8)-bar_pai_3jh_opt(n)/2 + pai_1k_opt(k,n)/2 - epsluo_u/2 + 1/2 ;  
            end
        end
    end

%
for n=1:N
for k=1:K
norm([(tk_opt(k,n)+pai_1k_opt(k,n))/2,(t_kr(k,n)-pai_1kr(k,n))(tk_opt(k,n)-pai_1k_opt(k,n))/4 - (t_kr(k,n)-pai_1kr(k,n))^2/8 + pai_2k_opt(k,n)/2 - 1/2 ]) <=…
(t_kr(k,n)-pai_1kr(k,n))(tk_opt(k,n)-pai_1k_opt(k,n))/4 - (t_kr(k,n)-pai_1kr(k,n))^2/8 + pai_2k_opt(k,n)/2 + 1/2;

             norm([(pai_2k_opt(k,n)+bar_pai_1k_opt(k,n))/2,(pai_2kr(k,n)-bar_pai_1kr(k,n))*(pai_2k_opt(k,n)-bar_pai_1k_opt(k,n))/4 - (pai_2kr(k,n)-bar_pai_1kr(k,n))^2/8 + pk_opt(k,n)*luo_0/2 - 1/2 ]) <=...
                (pai_2kr(k,n)-bar_pai_1kr(k,n))*(pai_2k_opt(k,n)-bar_pai_1k_opt(k,n))/4 - (pai_2kr(k,n)-bar_pai_1kr(k,n))^2/8 + pk_opt(k,n)*luo_0/2 + 1/2;
        
            norm([(bar_pai_2m_opt(k,n)-yita_1m_opt(k,n))/2,(bar_pai_2mr(k,n)+yita_1mr(k,n))*(bar_pai_2m_opt(k,n)+yita_1m_opt(k,n))/4 - (bar_pai_2mr(k,n)+yita_1mr(k,n))^2/8 - pk_opt(k,n)*luo_0/2 - 1/2 ]) <=...
                (bar_pai_2mr(k,n)+yita_1mr(k,n))*(bar_pai_2m_opt(k,n)+yita_1m_opt(k,n))/4 - (bar_pai_2mr(k,n)+yita_1mr(k,n))^2/8 - pk_opt(k,n)*luo_0/2 + 1/2;
        end
    end

%
%
for n=1:N
for k=1:K
for e=1:E
if e==1
norm([(Kesi_ke_opt(k,n)-bar_tke_opt(k,n))/2,(Kesi_ke1_r(k,n)+bar_t_ke1_r(k,n))*(Kesi_ke_opt(k,n)+bar_tke_opt(k,n))/4 - (Kesi_ke1_r(k,n)+bar_t_ke1_r(k,n))^2/8 - pk_opt(k,n)g_ke(k,n)/2 - 1/2 ]) <=…
(Kesi_ke1_r(k,n)+bar_t_ke1_r(k,n))(Kesi_ke_opt(k,n)+bar_tke_opt(k,n))/4 - (Kesi_ke1_r(k,n)+bar_t_ke1_r(k,n))^2/8 - pk_opt(k,n)*g_ke(k,n)/2 + 1/2;

                    Kesi_ke_opt((e-1)*K+k,n) <= sum(alpha_ke1((k-1)*K+1:k*K,n).*g_ke(1:K,n)) + bar_Kesi_je_opt(e,n) + epsluo_u;
                    
                end
                if e==2
                     norm([(Kesi_ke_opt(K+k,n)-bar_tke_opt(K+k,n))/2,(Kesi_ke2_r(k,n)+bar_t_ke2_r(k,n))*(Kesi_ke_opt(K+k,n)+bar_tke_opt(K+k,n))/4 - (Kesi_ke2_r(k,n)+bar_t_ke2_r(k,n))^2/8 - pk_opt(k,n)*g_ke(K+k,n)/2 - 1/2 ]) <=...
                        (Kesi_ke2_r(k,n)+bar_t_ke2_r(k,n))*(Kesi_ke_opt(K+k,n)+bar_tke_opt(K+k,n))/4 - (Kesi_ke2_r(k,n)+bar_t_ke2_r(k,n))^2/8 - pk_opt(k,n)*g_ke(K+k,n)/2 + 1/2;
                    
                     Kesi_ke_opt((e-1)*K+k,n) <= sum(alpha_ke2((k-1)*K+1:k*K,n).*g_ke(1+K:2*K,n)) + bar_Kesi_je_opt(e,n) + epsluo_u;
                end
                if e==3
                    norm([(Kesi_ke_opt(2*K+k,n)-bar_tke_opt(2*K+k,n))/2,(Kesi_ke3_r(k,n)+bar_t_ke3_r(k,n))*(Kesi_ke_opt(2*K+k,n)+bar_tke_opt(2*K+k,n))/4 - (Kesi_ke3_r(k,n)+bar_t_ke3_r(k,n))^2/8 - pk_opt(k,n)*g_ke(2*K+k,n)/2 - 1/2 ]) <=...
                        (Kesi_ke3_r(k,n)+bar_t_ke3_r(k,n))*(Kesi_ke_opt(2*K+k,n)+bar_tke_opt(2*K+k,n))/4 - (Kesi_ke3_r(k,n)+bar_t_ke3_r(k,n))^2/8 - pk_opt(k,n)*g_ke(2*K+k,n)/2 + 1/2;
                    
                     Kesi_ke_opt((e-1)*K+k,n) <= sum(alpha_ke3((k-1)*K+1:k*K,n).*g_ke(1+2*K:3*K,n)) + bar_Kesi_je_opt(e,n) + epsluo_u;
                end
            end      
        end  
    end
    
    for n=1:N 
              norm([(bar_pai_3jh_opt(n) - yita_2m_opt(n))/2,(bar_pai_3jh_r(n)+yita_2mr(n))*(bar_pai_3jh_opt(n)+yita_2m_opt(n))/4 - (bar_pai_3jh_r(n)+yita_2mr(n))^2/8 - pj_opt(n)*luo_0/2 - 1/2 ]) <=...
              (bar_pai_3jh_r(n)+yita_2mr(n))*(bar_pai_3jh_opt(n)+yita_2m_opt(n))/4 - (bar_pai_3jh_r(n)+yita_2mr(n))^2/8 - pj_opt(n)*luo_0/2 + 1/2;                   
          for e=1:E
                 norm([(bar_Kesi_je_opt(e,n)+tau_ke_opt(e,n))/2,(bar_Kesi_je_r(e,n)-tau_je_r(e,n))*(bar_Kesi_je_opt(e,n)-tau_ke_opt(e,n))/4 - (bar_Kesi_je_r(e,n)-tau_je_r(e,n))^2/8 + pj_opt(n)*luo_0/2 - 1/2 ]) <=...
              (bar_Kesi_je_r(e,n)-tau_je_r(e,n))*(bar_Kesi_je_opt(e,n)-tau_ke_opt(e,n))/4 - (bar_Kesi_je_r(e,n)-tau_je_r(e,n))^2/8 + pj_opt(n)*luo_0/2  + 1/2;  
          end
    end
    
    for n=1:N
        for k=1:K
            norm([H_H,(qH(:,n)-wk(:,k))', (bar_pai_1k_opt(k,n)-1)/2 ]) <= (bar_pai_1k_opt(k,n)+1)/2;
            
            yita_1m_opt(k,n) <= H_H^2 + norm(qr_H(:,n)-wk(:,k))^2 + 2*(qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)); 
        end
    end
          
    for n=1:N
        for k=1:K   
            if k==1
                Tem=[2 3 4];
                for index=1:3
                    ii=Tem(index);
                        norm([(belta_k_opt(k,n)+alpha_km_opt((k-1)*K+ii,n))/2,(belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                          (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 - 1/2 ]) <= belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n)*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                          (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 + 1/2;     
                end
            end     
            if k==2
                Tem=[1 3 4];
                for index=1:3
                    ii=Tem(index);
                    norm([(belta_k_opt(k,n)+alpha_km_opt((k-1)*K+ii,n))/2,(belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 - 1/2 ]) <= belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n)*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 + 1/2; 
                end
            end
            if k==3
                Tem=[1 2 4];
                 for index=1:3
                     ii=Tem(index);
                    norm([(belta_k_opt(k,n)+alpha_km_opt((k-1)*K+ii,n))/2,(belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 - 1/2 ]) <= belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n)*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 + 1/2; 
                end
            end
            if k==4
                Tem=[1 2 3];
                 for index=1:3
                     ii=Tem(index);
                    norm([(belta_k_opt(k,n)+alpha_km_opt((k-1)*K+ii,n))/2,(belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 - 1/2 ]) <= belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n)*(belta_k_opt(k,n)-alpha_km_opt((k-1)*K+ii,n))/4 - (belta_k_r(k,n)-alpha_km_r((k-1)*K+ii,n))^2/8 + (qr_H(:,n)-wk(:,k))'*(qH(:,n)-qr_H(:,n)) +...
                      (norm(qr_H(:,n)-wk(:,k))^2)/2 +  H_H^2/2 + 1/2; 
                end
            end   
        end
    end
    

    
    for n=1:N
        for k=1:K   
            norm([H_H,(qH(:,n)-wk(:,k))', (belta_k_opt(k,n)-1)/2 ]) <= (belta_k_opt(k,n)+1)/2;
        end
        yita_2m_opt(n) <= (H_H-H_J)^2 + norm(qr_H(:,n)-qr_J(:,n))^2 + 2*(qr_H(:,n)-qr_J(:,n))'*(qH(:,n)-qr_H(:,n)) - 2*(qr_H(:,n)-qr_J(:,n))'*(qJ(:,n)-qr_J(:,n));
        for e=1:E
            norm([H_J,(qJ(:,n)-we(:,e))', (tau_ke_opt(e,n)-1)/2 ]) <= (tau_ke_opt(e,n)+1)/2; 
        end 
    end
    
    for n=1:N-1
         norm(qH(:,n+1)-qH(:,n)) <= V_max*delta_t;
         norm(qJ(:,n+1)-qJ(:,n)) <= V_max*delta_t;
    end
 
    log2(1+t_kr)+1/log(2)./(1+t_kr).*(tk_opt-t_kr) <= fk_opt/C_k/1e6;
     Rk_loc_opt <= fTD_max/C_k/1e6;
    0<=fk_opt;
    fk_opt<=f_max;
    0<=pj_opt;
    pj_opt<=Pu_J_max;
    0<=pk_opt;
    pk_opt<=Pk_max;
    0 <= alpha_km_opt;
    alpha_km_opt <= 1;
    qH(:,1)==qH(:,end);
    qJ(:,1)==qJ(:,end);   
cvx_end
3

Your problem has been assesses as primal infeasible (dual infeasibility reported by Mosek refers to the dual problem which CVX provided it).

Start of by paying attention to scaling, as evidenced by Mosek;'s warnings.Once you have improved that, if the problem is still reported infeasible, carry out the guidance in.Debugging infeasible models - YALMIP

4

Hi, Yu! Do you solve this problem? My problem is almost the same as yours. How did you solve it? Our warning code is all the same. Looking forward to your reply!

5

@yifan19 Did you carry out the suggestions in my post above?

6

Yes. I am studying on that website and have some ideas.

7

sorry, this link doesn’t available now, can you update the new link?

8

Link has been updated.