In this post, we delve into solving the Capacitated Vehicle Routing Problem (CVRP) by transitioning from traditional routing models to the advanced Mixed Integer Programming (MIP) approach. We'll start with the basics of creating a routing model using Google OR-Tools and then explore how to formulate and solve the CVRP using MIP for more optimized solutions. Whether you're new to vehicle routing or looking to enhance your optimization techniques, this comprehensive guide provides the insights and code examples you need.

This post demonstrates solving the Facility Location Problem (FLP) using OR-Tools and Micronaut. It covers defining the solver, variables, constraints, and objective function in Java. The implementation includes creating a Micronaut service and controller to handle file uploads, process the data, and compute the optimal solution. The example input file format and expected outputs are also illustrated, providing a complete guide to implementing and testing the FLP solution.

In this post, I explore solving a Traveling Salesman Problem (TSP) involving 200 cities using genetic algorithms within a Micronaut framework. Leveraging techniques like inversion, insertion, and swap mutations, I illustrate how to maintain genetic diversity and improve solution quality over generations. The implementation showcases significant performance improvements compared to previous solvers. This approach combines simulated annealing, genetic algorithms, and local search to tackle complex optimization challenges effectively.

Solve the Travelling Salesman Problem using Choco-solver and convert it into a powerful API with Micronaut. Explore the efficient solution and its integration for optimal city tours.