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scientific edition of Bauman MSTU

SCIENCE & EDUCATION

Bauman Moscow State Technical University.   El № FS 77 - 48211.   ISSN 1994-0408

Research and Setting the Modified Algorithm "Predator-Prey" in the Problem of the Multi-Objective Optimization

# 12, December 2016
DOI: 10.7463/1216.0852423
Article file: SE-BMSTU...o181.pdf (1848.94Kb)
authors: A.P. Karpenko1,*, A.V. Pugachev1



1 Bauman Moscow State Technical University, Moscow, Russia

We consider a class of algorithms for multi-objective optimization - Pareto-approximation algorithms, which suppose a preliminary building of finite-dimensional approximation of a Pareto set, thereby also a Pareto front of the problem. The article gives an overview of population and non-population algorithms of the Pareto-approximation, identifies their strengths and weaknesses, and presents a canonical algorithm "predator-prey", showing its shortcomings.
We offer a number of modifications of the canonical algorithm "predator-prey" with the aim to overcome the drawbacks of this algorithm, present the results of a broad study of the efficiency of these modifications of the algorithm. The peculiarity of the study is the use of the quality indicators of the Pareto-approximation, which previous publications have not used. In addition, we present the results of the meta-optimization of the modified algorithm, i.e. determining the optimal values of some free parameters of the algorithm.
The study of efficiency of the modified algorithm "predator-prey" has shown that the proposed modifications allow us to improve the following indicators of the basic algorithm: cardinality of a set of the archive solutions, uniformity of archive solutions, and computation time. By and large, the research results have shown that the modified and meta-optimized algorithm enables achieving exactly the same approximation as the basic algorithm, but with the number of preys being one order less. Computational costs are proportionally reduced.

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