app-johndpope

I play the piano / family man https://www.instagram.com/johndpope/

Pinned Repositories

Assignments
Assignments Summer 2019 Techincal University of Denmark
Language:Python00
Audio2Face
Language:Python0 0 00
BEIT-PROJECT_01_AUTOMATIC-TIMETABLE-GENERATOR-USING-GENETIC-ALGORITHM
Language:JavaScript0 0 00
cs193p-SwiftUI
The solutions to the assignments of the cs193p course, covering SwiftUI.
Language:Swift00
dexciss
Language:JavaScript0 0 00
dirt
Docker-compose for Tobin Bradley's Dirt Simple API
Language:JavaScript00
doggy-data
Doggy Data Demo
Language:JavaScript00
flp-genetic
A basic genetic algorithm to get nearly ideal solution for the Uncapacitated Facility Location Problem
Language:Python0 0 00
force-directed-layout-algorithms
Force directed layout algorithms for Python
Language:Python00
Genetic-Algorithm
Timetable Generator Using Genetic Algorithm
Language:Jupyter Notebook0 0 00

app-johndpope's Repositories

app-johndpope/Assignments
Assignments Summer 2019 Techincal University of Denmark
Language:Python00
app-johndpope/Audio2Face
Language:Python0 0 00
app-johndpope/BEIT-PROJECT_01_AUTOMATIC-TIMETABLE-GENERATOR-USING-GENETIC-ALGORITHM
Language:JavaScript0 0 00
app-johndpope/cs193p-SwiftUI
The solutions to the assignments of the cs193p course, covering SwiftUI.
Language:Swift00
app-johndpope/dexciss
Language:JavaScript0 0 00
app-johndpope/dirt
Docker-compose for Tobin Bradley's Dirt Simple API
Language:JavaScript00
app-johndpope/doggy-data
Doggy Data Demo
Language:JavaScript00
app-johndpope/flp-genetic
A basic genetic algorithm to get nearly ideal solution for the Uncapacitated Facility Location Problem
Language:Python0 0 00
app-johndpope/force-directed-layout-algorithms
Force directed layout algorithms for Python
Language:Python00
app-johndpope/Genetic-Algorithm
Timetable Generator Using Genetic Algorithm
Language:Jupyter Notebook0 0 00
app-johndpope/googlesheets_to_bq
Language:Python0 0
app-johndpope/heuristics_tsp
Test heuristics (greedy, genetic algorithms...) on Travelling Salesperson Problem. Graphs implemented with NetworkX library.
app-johndpope/honeycode
honeycode apis
Language:Python0 0
app-johndpope/intro-excercises
Excercises as an intro to the python language
Language:Python0 0
app-johndpope/NHLSimulation
A program that takes the most up-to-date stats on every NHL player, and uses these stats to create a simulation of the 2020-2021 NHL Season
app-johndpope/opp-cal
a web app to list opportunities available at different organisations and companies
Language:TypeScript0 0
app-johndpope/pfmindmap
Reactive, scalable mind map visualizer that uses a force-directed layout.
Language:JavaScript0 0
app-johndpope/PH-354-2019-IISc-Assignment-Problems
Solutions to the complete set of assignment problems which I did while crediting Computational Physics course by Prof. Manish Jain at IISc, Physical Sciences department on 2019
Language:Python0 0
app-johndpope/PropagationOptimizationAssignmentsPython
Language:Python0 0
app-johndpope/redimo.go
Use the power of DynamoDB with the ease of the Redis API
Language:Go0 0
app-johndpope/Reliable-FLP
A genetic algorithm for reliable and robust facility location problem
Language:Python0 0
app-johndpope/rocket-simulation
Simulate a rocket launch in two dimensions by calculating forces over a small time increment.
Language:Python0 0
app-johndpope/roster-wizard
An automatic rostering system that can handle skill mix requirements, staff requests and shift sequence rules
Language:Python0 0
app-johndpope/steadycalendar
app-johndpope/Technical_test
Bhavna_cdn_sol
Language:TypeScript0 0
app-johndpope/timetable-generator
Timetable generator for university schedule implemented in Python using genetic algorithms.
app-johndpope/Timetable-Generator-Genetic-Algorithm
Timetable Generation using Genetic Algorithm
Language:Jupyter Notebook0 0
app-johndpope/Timetable_generator
Most colleges have a number of different courses and each course has a number of subjects. Now there are limited faculties, each faculty teaching more than one subjects. So now the time table needed to schedule the faculty at provided time slots in such a way that their timings do not overlap and the time table schedule makes best use of all faculty subject demands. We use a genetic algorithm for this purpose. In our Timetable Generation algorithm we propose to utilize a timetable object. This object comprises of Classroom objects and the timetable for every them likewise a fitness score for the timetable. Fitness score relates to the quantity of crashes the timetable has regarding alternate calendars for different classes. Classroom object comprises of week objects. Week objects comprise of Days. also Days comprises of Timeslots. Timeslot has an address in which a subject, student gathering going to the address and educator showing the subject is related Also further on discussing the imperatives, We have utilized composite configuration design, which make it well extendable to include or uproot as numerous obligations. In every obligation class the condition as determined in our inquiry is now checked between two timetable objects. On the off chance that condition is fulfilled i.e there is a crash is available then the score is augmented by one.
app-johndpope/UCSPy-Engine
(Thesis) An extensible framework for solving the University Course Scheduling Problem.
app-johndpope/WarehouseRL