Need to design an algorithm
Budget: $10 – $30 USD
A dataset contains X items, each with an associated weight. The aim is to find a unique assignment of the X items into the K cluster so that:
Constraints 1: All the K clusters contain the same (if not same then as balanced as possible) number of items.
Constraints 2: The average weight should be the same (almost the same) in clusters.
Extra information: the weights are [0, 1]. X, K will be given as input and they are integer numbers.
Goal: Convert/transform this problem into a well-known problem (For example bin packing, Multiple Knapsacks or any variant of any existing algorithm) and implement.
PS: The main requirement is to convert/transform this problem into a well-known problem. Implementation is a secondary requirement. The preferred implementation language is Python.
Thank you in advance.
Constraints 1: All the K clusters contain the same (if not same then as balanced as possible) number of items.
Constraints 2: The average weight should be the same (almost the same) in clusters.
Extra information: the weights are [0, 1]. X, K will be given as input and they are integer numbers.
Goal: Convert/transform this problem into a well-known problem (For example bin packing, Multiple Knapsacks or any variant of any existing algorithm) and implement.
PS: The main requirement is to convert/transform this problem into a well-known problem. Implementation is a secondary requirement. The preferred implementation language is Python.
Thank you in advance.