0LAUK0 2015 01 Simulation
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The simulation test several different scheduling strategies and validate the outcome by evaluating the general happiness.
Simulator
Discrete Event Simulation based on React.NET framework.
Source code is available on GitHub under GPL V3 license.
Compiled binary is available from dropbox
Hints: Use mouse wheel to switch between charts and click on bars will show detailed data.
Simulator Setup
The simulator consists of 2 parts, logic and GUI.
Logic
The logic is implemented upon Discrete Event Simulation Frame by using React.NET and compiled into a dll for later integration.
http://reactnet.sourceforge.net/index.html
The simulation logic has 3 process running.
- Simulator
- The simulator process is responsible for spawn all other processes and act as environment by adding passengers to bus stops.
- Passenger
- The passenger process is responsible for counting the on/off time.
- Bus
- The bus process is responsible to drive alone the destination list provided by the scheduler.
The scheduler is an interface which will be called by the Bus process each iteration for updating the destination list.
GUI
The GUI is written in C# using WPF for fast demonstration purpose. The data is displayed by using Modern UI Charts library.
http://modernuicharts.codeplex.com/
All the simulation result is saved in SimResult class. After the simulation done the GUI will process this result and put it into DataViewer class for visualization.
Assumption and Approximations
There are three factors we used to calculate the general satisfaction.
- Waiting time
- The weight is 8.05.
- Crowdeness
- The weight is 7.97.
- Travel time
- The weight is 7.29.
These weight are taken from the survey result of people who take bus often.
The crowdness of each passenger is normalized to 0.0 - 1.0 by evaluating PassengerNumber/MaxPassengerNumber.
The waiting time is also normalized to 0.0 - 1.0 by WaitingTime/MaxWaitingTime.
We assume the max waiting time is 15 min. After 15 min the passenger feels totally disappointed.
The Travel time is normalized to 0.0 - 1.0 like waiting time by setting Max Travel Time to one hour.
In this way we obtained a normalized general happiness from 0% to 100%.
Dynamic Scheduler
Due to the time limitation only a simple dynamic scheduler is implemented.
The algorithm make decisions like follow:
1. Check if there's shortcut available from current bus stop
2. iterate over all available shortcuts and check if people on the bus want to go to the skipped bus stops
3. iterate over all available shortcuts and check if people from skipped bus stops want to get on the bus
4. if all conditions are met, choose the shortcut that skip more bus stops.