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

Federico Zuiani, Massimiliano Vasile

Research output: Contribution to conferencePaper

4 Citations (Scopus)

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.

Conference

ConferenceBioinspired Optimization Methods and their Applications, BIOMA 2012
CountrySlovenia
CityBohinj
Period24/05/1225/05/12

Fingerprint

Multiobjective optimization
Decomposition
Trajectories

Keywords

  • multi-objective optimisation
  • multi-agent paradigm
  • memetic algorithms

Cite this

Zuiani, F., & Vasile, M. (2012). Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps. Paper presented at Bioinspired Optimization Methods and their Applications, BIOMA 2012, Bohinj, Slovenia.
Zuiani, Federico ; Vasile, Massimiliano. / Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps. Paper presented at Bioinspired Optimization Methods and their Applications, BIOMA 2012, Bohinj, Slovenia.
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Zuiani, F & Vasile, M 2012, 'Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps' Paper presented at Bioinspired Optimization Methods and their Applications, BIOMA 2012, Bohinj, Slovenia, 24/05/12 - 25/05/12, .

Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps. / Zuiani, Federico; Vasile, Massimiliano.

2012. Paper presented at Bioinspired Optimization Methods and their Applications, BIOMA 2012, Bohinj, Slovenia.

Research output: Contribution to conferencePaper

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AU - Vasile, Massimiliano

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N2 - This paper presents a novel formulation of Multi Agent CollaborativeSearch for multiobjective optimization. A population of agents combinesglobal exploration heuristics and moves to explore the neighborhood ofeach agent. In this novel formulation the selection process is based onthe Tchebycheff decomposition of the multiobjective optimization probleminto single objective optimization problems in combination with theuse of the dominance index. The decomposition allows the implementationof Monotonic Basin Hopping steps that improve convergence onsingle funnel structures. The novel agent-based algorithm is tested ona 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.

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Zuiani F, Vasile M. Multi-agent collaborative search with Tchebycheff decomposition and monotonic basin hopping steps. 2012. Paper presented at Bioinspired Optimization Methods and their Applications, BIOMA 2012, Bohinj, Slovenia.