Or-tools : CVRP multiple time window with multiple location

Question

I am using or-tools to solve a CVRP with multiple time window, and multiple location. Meaning that a customer can move during the day. I can't achieve to add constraint like if i deliver the customer once i don't need to deliver him again in his next/previous location. For now i tried defined Sets of delivery but i'm not sure to really understand how it works.

def solve(self):
        print("INIT SOLVER")
        self.manager = pywrapcp.RoutingIndexManager(len(self.data['time_matrix']), self.data["num_vehicles"], self.data['depot'])
        self.routing = pywrapcp.RoutingModel(self.manager)

        def time_callback(from_index, to_index):
            # Convert from self.routing variable Index to time matrix NodeIndex.
            from_node = self.manager.IndexToNode(from_index)
            to_node = self.manager.IndexToNode(to_index)
            return self.data['time_matrix'][from_node][to_node]

        def demand_callback(from_index):
            # Convert from self.routing variable Index to demands NodeIndex.
            from_node = self.manager.IndexToNode(from_index)
            return self.data['demands'][from_node]

        transit_callback_index = self.routing.RegisterTransitCallback(time_callback)
        self.routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

        #transit_callback_index = self.routing.RegisterTransitCallback(self.distance_callback)
        #self.routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)

        demand_callback_index = self.routing.RegisterUnaryTransitCallback(demand_callback)
        self.routing.AddDimensionWithVehicleCapacity(demand_callback_index,0,  # null capacity slack
            self.data['vehicle_capacities'],  # vehicle maximum capacities
            True,  # start cumul to zero
            'Capacity')

        time = 'Time'
        self.routing.AddDimension(transit_callback_index, 30,  self.T, False, time)
        time_dimension = self.routing.GetDimensionOrDie(time)

        #SETTING UP TIME WINDOWS
        for location_idx, time_window in enumerate(self.data['time_windows']):
            if location_idx == self.data['depot']:
                continue
            index = self.manager.NodeToIndex(location_idx)
            time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])



        depot_idx = self.data['depot']
        for vehicle_id in range(self.data['num_vehicles']):
            index = self.routing.Start(vehicle_id)
            time_dimension.CumulVar(index).SetRange(
                self.data['time_windows'][depot_idx][0],
                self.data['time_windows'][depot_idx][1])

        for i in range(self.data['num_vehicles']):
            self.routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(self.routing.Start(i)))
            self.routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(self.routing.End(i)))

        #DEFINING CUSTOMER CLUSTER
        print(self.data["index"])
        for i in self.data['index']:
            print(i)
            delivery_node = i.copy()
            delivery_index = []
            for z in delivery_node:
                delivery_index.append(self.manager.NodeToIndex(z))
            delivery_disjunction_index = self.routing.AddDisjunction(delivery_index, -1)
            self.routing.AddPickupAndDeliverySets(0, delivery_disjunction_index)
        print("Done")

        search_parameters = pywrapcp.DefaultRoutingSearchParameters()
        search_parameters.first_solution_strategy = (
        routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
        #search_parameters.local_search_metaheuristic = (
        #routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)
        #search_parameters.time_limit.FromSeconds(10)

        print("Start solver")

        self.solution = self.routing.SolveWithParameters(search_parameters)

        if self.solution:
            self.display_solution()```