Parallel Multi-objective Memetic Algorithm for Competitive Facility Location

被引：3

作者：

Lancinskas, Algirdas ^{[1
]}

Zilinskas, Julius ^{[1
]}

机构：

[1] Vilnius Univ, Inst Math & Informat, LT-08663 Vilnius, Lithuania

来源：

PARALLEL PROCESSING AND APPLIED MATHEMATICS (PPAM 2013), PT II | 2014年 / 8385卷

关键词：

Facility location; Multi-objective optimization; Memetic algorithms; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHM; NSGA-II; OPTIMIZATION;

D O I：

10.1007/978-3-642-55195-6_33

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A hybrid genetic algorithm for global multi-objective optimization is parallelized and applied to solve competitive facility location problems. The impact of usage of the local search on the performance of the parallel algorithm has been investigated. An asynchronous version of the parallel genetic algorithm with the local search has been proposed and investigated by solving competitive facility location problem utilizing hybrid distributed and shared memory parallel programming model on high performance computing system.

引用

页码：354 / 363

页数：10

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