# CLEAR MEMORY
reset ;

# LOAD MODEL
model 'bath_exp.mod' ;

# LOAD DATA
data  'bath_exp.dat' ; 

# Approximation grid
 
let q  := q0 + 1;
param dL := L / q0  ;
param nL := ( Mbar - M0 ) div  L  ;
param q1 := 1+( ( Mbar - nL * L - M0 ) div dL );
let n := q * nL + q1 + 1 ;
param M1 := Mbar - nL * L ; 

for { i in 1..q1  } { 
  for { j in 0 .. nL+1 } {
     let B[i+j*q] := M0 + (i-1) * dL + j * L;
     }
  }

for {j in 0 .. nL+1 } {  
   let B[q1+1+j*q] := M1 + j * L ;
   }

for { i in q1+2..q } {
  for { j in 0 .. nL } {
     let B[i + j * q] := B[q1] + dL * (i - (q1+1)) + j * L;
     }
  }


display t[n+q] , util_exp;


# Provide correct path to solver
option solver 'conopt' ;

option conopt_options 'outlev=3';
option display_width 100 ;


objective last_arrival_time;

solve;

# The exponential utility
objective util_exp ; 

solve ;

var tt {i in 1..n} = t[i+q] ;

option display_width 120 ;
display t[1], t[n], t[n+q] , util_exp, util_exp / P,P;

display  B, e, k, v, ue_exp, ux_exp, t,tt > 'bath_exp.csv' ;

end;