Affiliation:
1. Computer Science and Engineering Department, University of Kurdistan-Hewler, Erbil, Kurdistan, Iraq
2. Department of Information Technology, University of Human Development, Sulaymaniyah, Kurdistan, Iraq
Abstract
AbstractSwarm Intelligence is a metaheuristic optimization approach that has become very predominant over the last few decades. These algorithms are inspired by animals' physical behaviors and their evolutionary perceptions. The simplicity of these algorithms allows researchers to simulate different natural phenomena to solve various real-world problems. This paper suggests a novel algorithm called Donkey and Smuggler Optimization Algorithm (DSO). The DSO is inspired by the searching behavior of donkeys. The algorithm imitates transportation behavior such as searching and selecting routes for movement by donkeys in the actual world. Two modes are established for implementing the search behavior and route-selection in this algorithm. These are the Smuggler and Donkeys. In the Smuggler mode, all the possible paths are discovered and the shortest path is then found. In the Donkeys mode, several donkey behaviors are utilized such as Run, Face & Suicide, and Face & Support. Real world data and applications are used to test the algorithm. The experimental results consisted of two parts, firstly, we used the standard benchmark test functions to evaluate the performance of the algorithm in respect to the most popular and the state of the art algorithms. Secondly, the DSO is adapted and implemented on three real-world applications namely; traveling salesman problem, packet routing, and ambulance routing. The experimental results of DSO on these real-world problems are very promising. The results exhibit that the suggested DSO is appropriate to tackle other unfamiliar search spaces and complex problems.Highlights Donkey and Smuggler Optimization Algorithm (DSO) is a novel optimization algorithm. The DSO is inspired by Donkeys' behaviors. It has been evaluated against other algorithms. DSO solves different problems such as TSP, packet routing, and ambulance routing. The outcomes on the tests exhibit a greater manipulation of DSO. The outcomes prove that DSO has a greater searching ability.
Funder
University of Kurdistan Hewler
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computer Graphics and Computer-Aided Design,Human-Computer Interaction,Engineering (miscellaneous),Modeling and Simulation,Computational Mechanics
Cited by
56 articles.
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