Progressive Preference Articulation for Decision Making in Multi-Objective Optimisation Problems.

Rostami, S., Neri, F. and Epitropakis, M., 2017. Progressive Preference Articulation for Decision Making in Multi-Objective Optimisation Problems. Integrated Computer-Aided Engineering. (In Press)

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Abstract

This paper proposes a novel algorithm for addressing multi-objective optimisation problems, by employing a progressive preference articu- lation approach to decision making. This enables the interactive incorporation of problem knowledge and decision maker preferences during the optimisation process. A novel progressive preference articulation mechanism, derived from a statistical technique, is herein proposed and implemented within a multi-objective framework based on evolution strategy search and hypervolume indicator selection. The proposed algo- rithm is named the Weighted Z-score Covariance Matrix Adaptation Pareto Archived Evolution Strategy with Hypervolume-sorted Adaptive Grid Algorithm (WZ-HAGA). WZ-HAGA is based on a framework that makes use of evolution strategy logic with covariance matrix adaptation to perturb the solutions, and a hypervolume indicator driven algorithm to select successful solutions for the subsequent generation. In order to guide the search towards interesting regions, a preference articulation procedure composed of four phases and based on the weighted z-score approach is employed. The latter procedure cascades into the hypervolume driven algorithm to perform the selection of the solutions at each generation. Numerical results against five modern algorithms representing the state-of-the-art in multi-objective optimisation demonstrate that the pro- posed WZ-HAGA outperforms its competitors in terms of both the hypervolume indicator and pertinence to the regions of interest.

Item Type:Article
ISSN:1069-2509
Uncontrolled Keywords:multi-objective optimisation ; many-objective optimisation ; evolution strategy ; selection mechanisms ; preference articulation
Group:Faculty of Science & Technology
ID Code:29286
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:02 Jun 2017 15:54
Last Modified:02 Jun 2017 15:54

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