Metadata-Version: 2.1
Name: fliscopt
Version: 0.1.0
Summary: Flight scheduling optimization using Genetic Algorithm variants and other algorithms. 
Home-page: UNKNOWN
Author: Ankit Grover, Jones Granatyr
Author-email: agrover112@gmail.com
License: MIT
Platform: linux
Platform: macos
Platform: unix
Requires-Python: >=3.8
Description-Content-Type: text/markdown
License-File: LICENSE

# Fliscopt 


FLight SCheduling OPTimization(fliscopt) is an simple optimization library for flight scheduling and related problems in the discrete domain.The library supports plotting,asynchronous multiprocessing and unimodal optimization benchmarks.
The following repository contains code for the paper "XYZ" . The experiments were performed in **PyPy3.7** and **CPython 3.8.10.**

Following algorithms have been implemented and test as of date:
**Algorithms**:
- Hill Climbing
- Random Search
- Simulated Annealing
- Genetic Algorithm
- Genetic Algorithm in Reverse Mode
- Genetic  Algorithm with Reversals
- Iterated Chaining

 


# Getting Started

Install the library using pip:
```
pip install flicsopt
```

## For PyPy users
The instructions for setup are mentioned in setup directory. Alternatively, you can setup using this bash script. A requirements file is provided just in case.
The script creates and activates an PyPy conda  environment with all libraries and dependencies.
```
cd ./setup.sh
source setup.sh
```

# Testing
After adding any new algorithm, you can run the tests to check if the code is working properly.
```
./run_tests.sh
```
# Results

## Experimental Results
Results were compared by using the same seeds. The following table shows the results for the experiments.
(Will be shortly added)

## Accessing results
After running the experiments, the results are stored in the results directory. The results are stored in the following format in subdirectories:
```
.
├── multi_proc
│   ├── ackley_N2
│   │   ├── genetic_algorithm_results.csv
│   │   ├── genetic_algorithm_reversed_results.csv
│   │   ├── genetic_algorithm_with_reversals_results.csv
│   │   ├── hill_climb_results.csv
│   │   ├── random_search_results.csv
│   │   └── simulated_annealing_results.csv
│   ├── booth/....
|   |
|   |
│   └── zakharov
│       ├── genetic_algorithm_results.csv
│       ├── genetic_algorithm_reversed_results                  
│       ├── genetic_algorithm_with_reversals_results.csv
│       ├── random_search_results.csv
│       └── simulated_annealing_results.csv
├── plots
│   ├── ackley_N2
│   ├── fitness_function
│   │   ├── hill_climb.png
│   │   └── random_search.png
│   ├── flight_scheduling
│   │   ├── simulated_annealing.png
│   │   ├── sol_chaining.png
│   │   └── sol_chaining_a1.png
│   └── griewank
```





# Contributing Guidelines
Refer [Contributing.md](./CONTRIBUTING.md) and Project Board for mode details.
# References
[1] []
[2] []    


