Artificial Life system for optimization of nonconvex functions

Taiji Satoh, Akihiko Uchibori, Kanya Tanaka

Research output: Contribution to conferencePaper

6 Citations (Scopus)

Abstract

This paper presents a distributed algorithm for optimization of nonconvex multimodal functions. In recent years, new distributed algorithms based on Artificial Life (ALife) system has been studied and its potential power has been demonstrated. In this paper, therefore, the frame work of ALife system is employed into a function minimization. This paper also proposes a hybrid algorithm in which ALife system is incorporated with the local search method for finding good start points for the local search. Since the proposed method utilizes no gradient information, it can be applied to very wide class of optimization problems. The effectiveness of the proposed method is demonstrated through some numerical tests.

Original languageEnglish
Pages2390-2393
Number of pages4
Publication statusPublished - 1 Dec 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 10 Jul 199916 Jul 1999

Conference

ConferenceInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period10/07/9916/07/99

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Satoh, T., Uchibori, A., & Tanaka, K. (1999). Artificial Life system for optimization of nonconvex functions. 2390-2393. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .