Inderscience Publishers

Rational swarm for global optimisation

- By: ,

Courtesy of Inderscience Publishers

In this paper, we propose a novel bio–inspired multi–agent co–operative searching methodology for global optimisation, named Rational Swarm algorithm. It can be used both as a meta–heuristic guiding local search algorithm and as a high–level multi–agent co–operative searching strategy to coordinate multiple agents using meta–heuristics. In this work, the Rational Swarm methodology has been applied to a popular meta–heuristics Simulated Annealing (SA) and a pure local search algorithm Monotonic Sequential Basin Hopping (MSBH). Numerical experiments on various continuous optimisation problems show Rational Swarm can improve the performance of applied meta–heuristics/heuristics in terms of solution quality and robustness under the same computational budget. Convergence analysis gives the theoretical insights about why the proposed Rational Swarm Methodology will work.

Keywords: metaheuristics, cooperative search, global optimisation, swarm intelligence, bio–inspired computation, multi–agent systems, MAS, agent–based systems, multiple agents, simulated annealing, local search, rational swarm

Customer comments

No comments were found for Rational swarm for global optimisation. Be the first to comment!