Study and Analysis of Swarm Intelligence Techniques for Solving Combinatorial Optimization Problems

Abstract

Background: Computer science is the most interesting branch of engineering newlineand technology. It deals with the computers, different computational problems, and newlinetheir solutions. Being a huge branch of science, it again has so many sub-branches newlineinside it. The artificial intelligence is one of them. As the name indicates, the newlineartificial intelligence is the branch of computer science which has aim of making newlinemachines think, behave and train like humans. Numerous approaches are there in newlineartificial intelligence to solve the combinatorial optimization problems. One of the newlinemost interesting ways is the swarm intelligence techniques to solve the newlinecombinatorial optimization problem. newlineAim: The objective of this research is to device a swarm intelligence-based newlinetechnique to solve optimization problems. The approach takes the inspiration from newlinethe real-world behavior of the bloodhound breed of dogs. This breed of dogs has got newlinethe highest number of smell receptors and can trace the odor image for more than 3- newlinehours. The proposed approach performs the searching operation the same way as the newlinebloodhound breed. The main objective is to get the best solution in less amount of newlinetime than the existing approaches. newlineMethodology: The bloodhound searching Algorithm is completely relying on newlinethe behavior of the bloodhound breed of the dogs. The bloodhound has got the newlinehighest number of smell receptors (which are responsible for the smelling capability newlineof an organism). An image odor is created in the brain of the bloodhound which newlineremains in its brain for more than 130 miles. Based on this being the focus to solve newlineTABLE OF CONTENTS newlinethe problem, following is the list of variables which are used to solve the problem. newlineTo test the approach, firstly, traveling salesman problem is used as test bed. newlineResults,Discussion and Conclusion: The bloodhound-based approach (BHSA) newlinefor solving the combinatorial optimization problem takes its inspiration from the newlinebloodhound breed of the dogs which has the highest number of smell receptors newlinepresent in their nasal cavity.