Nash-Pareto Genetic Algorithm for the Frequency Assignment Problem

被引：5
|
作者：
Laidoui, Fatma
Bessedik, Malika
Si-Tayeb, Fatima Benbouzid
Bengherbia, Nawfel
Khelil, Massyl Yacine
机构：
来源：
KNOWLEDGE-BASED AND INTELLIGENT INFORMATION & ENGINEERING SYSTEMS (KES-2018) | 2018年 / 126卷
关键词：
Game theory; Nash equilibrium; Pareto-optimality; genetic algorithm; multi-objective optimization; Frequency Assignment Problem; CHANNEL ASSIGNMENT;
D O I：
10.1016/j.procs.2018.07.262
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a hybrid multi-objective genetic algorithm which combines the main notion of game theory Nash equilibrium with Pareto-optimality to solve the multi-objective Frequency Assignment Problem (FAP) in mobile networks. The game is coupled with genetic algorithm to accelerate convergence and produce Nash equilibrium and Pareto non-dominated solutions simultaneously. The proposed hybrid approach produces high quality solutions as proved by several performed tests and corroborated by the comparison with the most referred multi-objective optimization algorithms such as NSGA-II and SPEA2 on well-known Philadelphia and COST259 FAP instances. Furthermore, the effect of some parameters is discussed. (C) 2018 The Authors. Published by Elsevier Ltd.
引用
收藏
页码：282 / 291
页数：10
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