Open AccessEmergency Service Search using Ant Colony Optimization Algorithm and AHP-TOPSIS Method
Author(s) -
Muhammad Rivani Ibrahim,
Jatmiko Endro Suseno,
Bayu Surarso
Publication year - 2021
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 - 10.1088/1742-6596/1943/1/012104
Subject(s) - topsis , ant colony optimization algorithms , computer science , analytic hierarchy process , ant , service (business) , operations research , mathematical optimization , algorithm , engineering , mathematics , business , computer network , marketing
Ant Colony Optimization (ACO) algorithm has a good ability in route search, ACO’s ability to leave traces on routes that have been traced and find the nearest route to reach the destination location, but now the nearest distance search is not only about distance problems but many things must be considered, like travel time and others, especially in emergency conditions require the fastest route to provide help when an accident, disaster, etc. AHP-TOPSIS method is used to support the ACO in finding the best route based on the criteria. The purpose of this research is to implement the ACO algorithm supported with AHP-TOPSIS to find the quickest path on the search for emergency services. ACO supported with Google Maps will provide a route from the emergency service location to the user location, that the value will be put to TOPSIS as a value to increase the decision based on the ranking. AHP is used as the basis of the priority values of each attribute such as time, distance, health facilities, and the nearest ambulance. This value will be inserted into TOPSIS as a priority value. TOPSIS provides emergency services by condition and provides the fastest emergency service route recommendations