NEW APPROACHES FOR SOLVING TRAVELLING SALESMAN PROBLEMS USING AGENTS SWARM INTELLIGENCE BEHAVIOR MODEL
Journal Title: Współpraca Europejska - Year 2015, Vol 5, Issue 5
Abstract
The paper is dedicated to new approaches for solving one of combinatorial optimization tasks – the Travelling Salesman Problem (TSP) using developed computer system which is based on collective agents swarm behavior model. For creation of swarm behavior model with indirect communication between agents ant colony algorithm with its developed modifications was used. Developed approaches enable to solve following types of TSPs: dynamic TSP, static (classical) TSP, and dynamic asymmetrical TSP (DATSP) in conditions of partly unknown input data. Aiming to increase an accuracy of results, local optimization methods were used. Solving of DATSP in conditions of partly unknown input data is one of the important tasks, it is related to practical usage: routing tasks in a real-life computer networks. Developed approaches are able to solve problems which appear during DATSP solving in conditions of partly unknown input data.
Authors and Affiliations
Oleksandr Muliarevych, Vadim Golembo
Keywords
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