**Apache Airflow version**: 2.0.0


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): N/A

**Environment**: 

- **Cloud provider or hardware configuration**: local/aws
- **OS** (e.g. from /etc/os-release): Ubuntu 18.04.5 LTS
- **Kernel** (e.g. `uname -a`): 5.4.0-1032-aws
- **Install tools**: pip
- **Others**:

**What happened**:
I did a fresh Airflow 2.0.0 install. With this version, when I manually trigger a DAG, Airflow skips the next scheduled run.
<!-- (please include exact error messages if you can) -->

**What you expected to happen**:
Manual runs do not interfere with the scheduled runs prior to Airflow 2. 
<!-- What do you think went wrong? -->

**How to reproduce it**:
Create a simple hourly DAG. After enabling it and the initial run, run it manually. It shall skip the next hour. Below is an example, where the manual run with execution time of 08:17 causes the scheduled run with execution time of 08:00 to skip. 
![image](https://user-images.githubusercontent.com/26160471/103457719-c7193480-4d12-11eb-82cb-42efaedc9ef4.png)


airflow/models/dag.py
for node in list(graph_unsorted.values()):
                for edge in node.upstream_list:
                    if edge.task_id in graph_unsorted:
                        break
                
                else:
                    acyclic = True
                    del graph_unsorted[node.task_id]
                    graph_sorted.append(node)
                    if include_subdag_tasks and isinstance(node, SubDagOperator):
                        graph_sorted.extend(node.subdag.topological_sort(include_subdag_tasks=True))
            if not acyclic:
                raise AirflowException(f"A cyclic dependency occurred in dag: {self.dag_id}")
        return tuple(graph_sorted)
    @provide_session
    def set_dag_runs_state(
        self,
        state: str = State.RUNNING,
        session: Session = None,
        start_date: Optional[datetime] = None,
        end_date: Optional[datetime] = None,
    ) -> None:
        query = session.query(DagRun).filter_by(dag_id=self.dag_id)
        if start_date:
            query = query.filter(DagRun.execution_date >= start_date)
        if end_date:
            query = query.filter(DagRun.execution_date <= end_date)
        query.update({DagRun.state: state})
    @provide_session
    def clear(