optBathtub/continuous/ampl/exp/bath_exp.mod

# MODEL PARAMETERS
param P    ;
param K    ;
param vf   ;
param M0   ;
param Mbar ;
param TMAX ;
param L    ;
param T0   := M0 / vf ; 

param n ;
param q ;

# APPROXIMATION GRID
param B {i in 1..n+q};
param q0 ;
# EXPONENTIAL UTILITY FUNCTION
param A0 ;
param a1 ;
param B0 ;
param b1 ;

# A SMALL VALUE
param eps  ;


# GENERATE INITIAL SOLUTION WITH UNIFORM ENTRIES
var e {i in 1..n} >= 0.0 ; 

var k  { i in 1..n+q-1 }  # traffic density
       = sum {j in max(1,i-q+1)..min(i,n)} e[j];
       
var v  { i in 1..n+q-1 } # traffic speed
       = vf * (1 - P * k[i] / K );

var Dt { i in 1..n+q-1 } # travel time from B[i] to B[i+1]
       = ( B[i+1] - B[i] ) / v[i];

var t  { i in 1..n+q } = # clock time at B[i]
       if i = 1 then T0
       else t[i-1] + Dt[i-1] ;


# EXPONENTIAL UTILITY FUNCTION
var ue_exp {i in 1..n}
       =  (A0/a1) * ( 1 - exp (-a1 * t[i] ) );

var ux_exp {i in 1..n}
       =  (B0/b1) * ( 1 -exp (- b1 * ( TMAX - t[i+q] ) ) );

maximize util_exp: sum{i in 1..n} ( ue_exp[i] + ux_exp[i] )  * e[i] * P ;


# MINIMIZE THE SHORTEST END TIME OF THE RUSH HOUR
minimize last_arrival_time: t[n+q] ; 


# CONSTRAINTS OF THE PROBLEM 
  # 1. All agents enter the bathtub
subject to entry : sum{i in 1..n}  e[i] == 1.0 ;

  # 2. Jam capacity should not be reached
subject to capacity { i in q .. n } : k[i] <= K / P - eps ;