Open AccessItem delivery simulation using genetic algorithm
Author(s) -
I Nyoman Switrayana,
Andrew Brian Osmond,
Annisa Aditsania
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1201/1/012060
Subject(s) - travelling salesman problem , shortest path problem , mathematical optimization , computer science , path (computing) , genetic algorithm , constrained shortest path first , operations research , yen's algorithm , service (business) , k shortest path routing , algorithm , dijkstra's algorithm , mathematics , computer network , theoretical computer science , marketing , business , graph
In sending items, time and costs can be minimized by selecting the shortest path. The problem of choosing the shortest path is often known as Travelling Salesman Problem (TSP). TSP in this study was not only concerned with distance but also the priority of places to be visited. Priority parameters in this research are a sign that each place has a value to be visited first than another place. This priority can also be assumed as a type of delivery service that can be chosen by the customer. Priority is divided into three groups, but it can also be more than that according to the needs of a shipping service provider. Delivery of multiple destinations in one area can be delivered with a single trip based on their priority. Search optimization of the shortest path is modeled with genetic algorithms. Hamilton path is the output of the simulation.