Parallel genetic algorithm for planning safe and optimal route for ship
This addresses route planning for ships, but it appears incremental as it builds on existing evolutionary methods.
The paper tackles the problem of planning safe and optimal routes for ships in obstacle-filled areas by developing a parallel genetic algorithm that optimizes locally optimal routes to minimize arrival time, with results indicating the ability to handle additional restrictions.
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.