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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.