Starting with a set range of values for bagPrice and refundAmount that would be multiplied with the production price of each bag, we started with 24 combinations in total to get back different points.
To find the highest points on each curve we choose to use look at the score differences in incremental changes, taking the solution with the largest score, creating new incremental changes and submitting it again until we found the largest score.
After that we reduced all orders to 0, and wanted to create a compromise between CO2 emissions and negativeCustomerScore, whichever had the smallest impact to create the optimal score over 365 days.
The algorithm was peer-programmed together with Isak Gerre.
This is the StarterKit for Considition 2022 which will help you get going as quickly as possible with the competition.
- The Main Program: This is where we run the main parts. There is an example solver implemented, Solver, which you can try out of the box.
- The Game Layer: A wrapper between the API and the Main Program. Helps you with formatting the input to the API.
- The API: A representation of the REST-API that the game is played with. Can be used directly or through the Game Layer.
- Solver: This is the out of the box solver you can change, take inspiration from or just replace with your own solver.
- Scoring: An explanation of the factors that determine the score.
The competition itself and how the evaluation of the solutions work is described in more in detail on Considition.com/rules.
Run npm install and run main.js
The Main Program is simple. Each run of the program does the following:
- Fetches the desired map
- Creates a solution with the selected solver
- This is where you can implement your solution. Optimize the solver to maximize your score.
- Submits the score to be validated and if approved, evaluated and posted for the competition.
- Prints the final score, game id to keep track of your best attempts, and a link if you want to see a visualisation of the game.
Solver is a very simple iterator to determine how many orders should be put each day with three simple suggested approaches. The refundChoice is set to "True", a bag price of 10 and a refund of 1. The training maps simulates 31 days and the others 365 days.
The game layer has all the functions you need to play the game.
The Game
- New Game Gets the properties of the selected map in a GameResponse, such as its packages and the vehicle dimensions.
- Submit Game Submits your game for validation and evaluation. If solution is valid, it returns a SubmitResponse with the scoring of your game.
The definition of the API and what it returns can be found on https://api.considition.com/swagger/index.html, or on https://Considition.com/rules. To see the visualization of your solution you can either follow the link in the game response or go to https://visualizer.considition.com and enter your gameId
After submitting a game through Submit game a validator will check so that the submission is valid, afterwards the score will be calculated according to the following criteria’s:
- Total score = The final score, as a result by Customer score - CO2 score
- Customer score = A sum of all positive and negative customer reviews
- CO2 score = The pollution from bag production and bag transports Through trial and error and within the timeframe stated above, you can attempt to plan the orders as many times as you want with different bag types to create the best possible algorithm.