**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
if end_date or not self.allow_future_exec_dates:
            end_date = end_date or timezone.utcnow()
            tis = tis.filter(TaskInstance.execution_date <= end_date)
        if state:
            if isinstance(state, str):
                tis = tis.filter(TaskInstance.state == state)
            else:
                
                if None in state:
                    if all(x is None for x in state):
                        tis = tis.filter(TaskInstance.state.is_(None))
                    else:
                        not_none_state = [s for s in state if s]
                        tis = tis.filter(
                            or_(TaskInstance.state.in_(not_none_state), TaskInstance.state.is_(None))
                        )
                else:
                    tis = tis.filter(TaskInstance.state.in_(state))
        tis = tis.order_by(TaskInstance.execution_date).all()
        return tis
    @property
    def roots(self) -> List[BaseOperator]:
        """Return nodes with no parents. These are first to execute and are called roots or root nodes."""
        return [task for task in self.tasks if not task.upstream_list]
    @property
    def leaves(self) -> List[BaseOperator]:
        """Return nodes with no children. These are last to execute and are called leaves or leaf nodes."""
        return [task for task in self.tasks if not task.downstream_list]
    def topological_sort(self, include_subdag_tasks: bool = False):