Algorithms-Metaheuritics

A project made for the college where we solve a problem using 3 different algorithms and we study how far do they get and which one gets the best solution

Inactive repository

This repository was a college project where we learned about different metaheuristics algorithms and we needed to create different approachs to a single problem, I developed most of the code, which is based on the classes notes. I can remember there was a problem with one of the algorithms so don't take this as an example

Code

Its core implementation its here

• Solution: its 1 array that show which doctor is the patient assigned, and an auxiliar array which shows how many patients does a doctor have assigned so we can check their limit easily.
• Population: its where most operands are made, it has a list of solutions and it contains the genetic and memetic main operands.
  Then we have the different implementations that use this core implementation we have:
• Genetic
• Memetic
• Simulated Annealing

I use Main.java to test these different implementations,it has some static attributes at the start so you can choose which algorithms to execute, if you want a debug mode it also contains a generateData method so we initialize some patients and some doctors

Problem:

A health insurance company wants to make an optimal allocation of its customers to the doctors of general medicine available in a given city. You want to minimize the displacement that each patient should make from home to the doctor's office assigned by the company. Recruitment of a specific doctor to attend patients of the company has a certain fixed cost, which is regardless of the number of patients assigned to you. It should be noted that each physician you will have a maximum number of patients that you will be able to treat.

The company requests that a tool be implemented that intelligently decides which patients will be treated. doctors who must be hired from all available in the city. In addition you will need to decide the list of patients who will be assigned to each contracted physician, taking into account that the company wishes to give you coverage to all your patients minimizing the costs of hiring doctors.
Translated with www.DeepL.com/Translator

Problema:

Una compañía de seguros médicos desea realizar una asignación óptima de sus clientes a los médicos de medicina general disponibles en una determinada ciudad. Se desea minimizar el desplazamiento que cada paciente debería hacer desde su domicilio a la consulta del médico asignado por la compañía. La contratación de un médico concreto para que atienda a pacientes de la compañía tiene un coste fijo determinado, que es independiente del número de pacientes que le sean asignados. Hay que tener en cuenta que cada médico tendrá un número máximo de pacientes a los que podrá atender.

La compañía solicita que se implemente una herramienta que decida de forma inteligente cuáles son los médicos que se deben contratar de todos los disponibles en la ciudad. Además deberá decidir la lista de pacientes que serán asignados a cada médico contratado, teniendo en cuenta que la compañía desea darle cobertura a todos sus pacientes minimizando los costes de contratación de los médicos.