**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 task_end_dates and next_run_date:
            min_task_end_date = min(task_end_dates)
            if next_run_date > min_task_end_date:
                return None
        return next_run_date
    def get_run_dates(self, start_date, end_date=None):
        """
        Returns a list of dates between the interval received as parameter using this
        dag's schedule interval. Returned dates can be used for execution dates.
        :param start_date: the start date of the interval
        :type start_date: datetime
        :param end_date: the end date of the interval, defaults to timezone.utcnow()
        :type end_date: datetime
        :return: a list of dates within the interval following the dag's schedule
        :rtype: list
        """
        run_dates = []
        using_start_date = start_date
        using_end_date = end_date
        
        using_start_date = using_start_date or min([t.start_date for t in self.tasks])
        using_end_date = using_end_date or timezone.utcnow()
        
        
        next_run_date = self.normalize_schedule(using_start_date) if not self.is_subdag else using_start_date
        while next_run_date and next_run_date <= using_end_date:
            run_dates.append(next_run_date)
            next_run_date = self.following_schedule(next_run_date)
        return run_dates
    def normalize_schedule(self, dttm):