Simultaneous concept-based evolutionary multi-objective optimization

Gideon Avigad

doi:10.1016/j.asoc.2009.11.009

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Simultaneous concept-based evolutionary multi-objective optimization

2011-01-01

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Gideon Avigad

Amiram Moshaiov *

DOI：10.1016/j.asoc.2009.11.009

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Abstract

En 中文

In contrast to traditional multi-objective problems the concept-based version of such problems involves sets of particular solutions, which represent predefined conceptual solutions. This paper addresses the concept-based multi-objective problem by proposing two novel multi objective evolutionary algorithms. It also compares two major search approaches. The suggested algorithms deal with resource sharing among concepts, and within each concept, while simultaneously evolving concepts towards a Pareto front by way of their representing sets. The introduced algorithms, which use a simultaneous search approach, are compared with a sequential one. For this purpose concept-based performance indicators are suggested and used. The comparison study includes both the computational time and the quality of the concept-based front representation. Finally, the effect on the computational time of both the concept fitness evaluation time and concept optimality, for both the sequential and simultaneous approaches, is highlighted. (c) 2009 Elsevier B.V. All rights reserved.

Keywords:

Multi-objective optimization

Elitism

Niching

Crowding

Fitness sharing

Species

Parallel GA

Co-evolution

Engineering design

Conceptual design

Competing sub-populations

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