def exp_1_nash():
net = MinTTTComplacencyProblem.load('../../networks/exps/exp1/net_w_demand.json')
left = net.link_by_name('left')
right = net.link_by_name('right')
left.flow = .75
left.rho = left.fd.rho_cong(left.flow)
right.flow = 1 - left.flow
right.rho = right.fd.rho_ff(right.flow)
source = net.link_by_name('source')
sink = net.link_by_name('sink')
source.flow = 1.0
source.rho = source.fd.rho_ff(source.flow)
sink.flow = 1.0
sink.rho = source.fd.rho_ff(sink.flow)
net.dump('../../networks/exps/exp1/net_nash.json')
def exp_1_opt():
"""
show that you can add constraints on the fly, and that this increases the objective when you force large densities
"""
net = MinTTTComplacencyProblem.load('../../networks/exps/exp1/net_w_demand.json')
prog = net.get_program()
prog.cr_print()
prog.cr_solve()
print 'obnjective', prog.cr_objective()
left = net.link_by_name('left')
prog.add_constraint(
net.cr_geq(left.v_dens, left.fd.v * left.fd.q_max * 1.2)
)
prog.cr_print()
prog.cr_solve()
print 'obnjective', prog.cr_objective()
for link in net.get_links():
link.flow = link.v_flow.value
link.rho = link.v_dens.value
net.d3ize()
print net.check_feasible()
def exp_1_nash_feasible():
net = MinTTTComplacencyProblem.load('../../networks/exps/exp1/net_nash.json')
print 'is feasible: ', net.check_feasible()
for route in net.all_routes():
print 'route', route
print route.travel_time()
for link in net.get_links():
print 'link', link
print 'flow', link.flow
print 'rho', link.rho
print 'net tt', net.total_travel_time()
program = net.get_program()
left = net.link_by_name('left')
program.add_constraint(net.cr_geq(left.v_dens,left.fd.rho_crit()*1.5))
program.cr_print()
program.cr_solve()
net.realize()
for link in net.get_links():
print 'link', link
print 'flow', link.flow
print 'rho', link.rho
print 'net tt', net.total_travel_time()
