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Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps

Zuiani, Federico and Vasile, Massimiliano (2012) Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps. In: Bioinspired Optimization Methods and their Applications, BIOMA 2012, 2012-05-24 - 2012-05-25.

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Abstract

This paper presents a novel formulation of Multi Agent Collaborative Search for multiobjective optimization. A population of agents combines global exploration heuristics and moves to explore the neighborhood of each agent. In this novel formulation the selection process is based on the Tchebycheff decomposition of the multiobjective optimization problem into single objective optimization problems in combination with the use of the dominance index. The decomposition allows the implementation of Monotonic Basin Hopping steps that improve convergence on single funnel structures. The novel agent-based algorithm is tested on a standard benchmark and on a real space trajectory design problem. Its performance is compared against a number of state-of-the-art multiobjective optimization algorithms.

Item type: Conference or Workshop Item (Paper)
ID code: 40478
Keywords: multi-objective optimisation, multi-agent paradigm, memetic algorithms, Mechanical engineering and machinery, Motor vehicles. Aeronautics. Astronautics, Mechanical Engineering, Aerospace Engineering, Computational Mechanics
Subjects: Technology > Mechanical engineering and machinery
Technology > Motor vehicles. Aeronautics. Astronautics
Department: Faculty of Engineering > Mechanical and Aerospace Engineering
Technology and Innovation Centre > Advanced Engineering and Manufacturing
Depositing user: Pure Administrator
Date deposited: 18 Jul 2012 15:02
Last modified: 03 Mar 2017 05:55
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URI: https://strathprints.strath.ac.uk/id/eprint/40478
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