Improving a distributed agent-based Ant Colony Optimization for Solving Traveling Salesman Problem
Aleksandar Kaplar, Milan Vidaković, Nikola Luburić, Mirjana Ivanović
Abstract
Aleksandar Kaplar, Milan Vidaković, Nikola Luburić, Mirjana Ivanović
Abstract
Optimization of a large-scale Traveling Salesman Problem, which is a well-known NP-hard problem in combinatorial optimization, is a time-consuming problem. A modern approach to dealing with such time-consuming problems is with the use of distributed computing, which can significantly improve the speed of the problem-solving algorithm. In this paper, we discuss the design approaches for an agent-based distributed algorithm and their benefits. Based on further analysis and experiments, we have improved our previous agent-based Ant Colony Optimization algorithm for Solving Traveling Salesman Problem using Siebog multiagent middleware.
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Optimization of a large-scale Traveling Salesman Problem, which is a well-known NP-hard problem in combinatorial optimization, is a time-consuming problem. A modern approach to dealing with such time-consuming problems is with the use of distributed computing, which can significantly improve the speed of the problem-solving algorithm. In this paper, we discuss the design approaches for an agent-based distributed algorithm and their benefits. Based on further analysis and experiments, we have improved our previous agent-based Ant Colony Optimization algorithm for Solving Traveling Salesman Problem using Siebog multiagent middleware.
Key concepts: Travelling salesman problem, Ant colony optimization algorithms, 2-opt, Computer science, Extremal optimization, Mathematical optimization, Combinatorial optimization, Multi-agent system