# Parallel genetic algorithm for planning safe and optimal route for ship

## TL;DR

This paper introduces a parallel genetic algorithm that efficiently plans safe, optimal routes for ships navigating areas with obstacles, improving route quality and computation speed.

## Contribution

It presents a novel parallel genetic algorithm approach for route planning, combining local optimization with global search for safety and efficiency.

## Key findings

- The algorithm effectively finds routes with minimal arrival time.
- It can incorporate additional route restrictions.
- The method outperforms some existing solutions in route quality.

## Abstract

The paper represents an algorithm for planning safe and optimal routes for transport facilities with unrestricted movement direction that travel within areas with obstacles. Paper explains the algorithm using a ship as an example of such a transport facility. This paper also provides a survey of several existing solutions for the problem. The method employs an evolutionary algorithm to plan several locally optimal routes and a parallel genetic algorithm to create the final route by optimising the abovementioned set of routes. The routes are optimized against the arrival time, assuming that the optimal route is the route with the lowermost arrival time. It is also possible to apply additional restriction to the routes.