Title: A new Metropolis optimisation method, the cross-section particle collision algorithm: some preliminary results

Authors: Wagner F. Sacco; Ana Carolina Rios-Coelho

Addresses: Instituto de Engenharia e Geociências, Universidade Federal do Oeste do Pará, Av. Vera Paz, s/n, Santarém, PA 68135-110, Brazil ' Instituto de Engenharia e Geociências, Universidade Federal do Oeste do Pará, Av. Vera Paz, s/n, Santarém, PA 68135-110, Brazil

Abstract: In this work, we introduce a new Metropolis algorithm, which is an enhancement of the recent Particle Collision Algorithm (PCA), loosely inspired by the neutron interactions in a reactor. This novel method is called the Cross-Section Particle Collision Algorithm (CSPCA), as it incorporates the concept of cross-section from Reactor Physics, in the sense that points in the search space and their respective fitness-function values are analogous to the neutron cross-sections which are used to express the likelihood of interaction between an incident neutron and a target nucleus. CSPCA is compared against the original PCA and two state-of-the-art metaheuristics, differential evolution and big bang-big crunch. These methods are applied to the turbine balancing problem, which is an NP-hard (i.e. non-deterministic polynomial-time hard) combinatorial optimisation problem that can be used to assess the potential of an algorithm to be applied to Fuel Management Optimisation (FMO). CSPCA performs better than its opponents, showing potential to be used not only in FMO, but also in other nuclear science and engineering optimisation problems.

Keywords: Metropolis algorithms; particle collision algorithm; combinatorial optimisation; random keys; fuel management optimisation; cross-section; reactor physics; metaheuristics; differential evolution; big bang-big crunch; turbine balancing; nuclear energy; nuclear power.

DOI: 10.1504/IJNEST.2016.076354

International Journal of Nuclear Energy Science and Technology, 2016 Vol.10 No.1, pp.59 - 71

Received: 02 Nov 2015
Accepted: 01 Mar 2016
Published online: 04 May 2016 *

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