A MOEA/D-based multi-objective optimization algorithm for remote medical

被引：15

作者：

Lin, Shufu ^{[1
]}

Lin, Fan ^{[1
]}

Chen, Haishan ^{[1
]}

Zeng, Wenhua ^{[1
]}

机构：

[1] Xiamen Univ, Software Sch, Xiamen, Peoples R China

来源：

NEUROCOMPUTING | 2017年 / 220卷

关键词：

Remote medical; Resource assignment; Differential mutation; Selection strategy; Multi-objective optimization; Test problems; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM;

D O I：

10.1016/j.neucom.2016.01.124

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Remote medical resources configuration and management involves complex combinatorial Multi-Objective Optimization problem, whose computational complexity is a typical NP problem. Based on the MOEA/D framework, this paper applies the two-way local search strategy and the new selection strategy based on domination amount and proposes the IMOEA/D framework, following which each individual produces two individuals in mutation. In this paper, by using a new selection strategy, the parent individual is compared with two mutated offspring individuals, and the more excellent one is selected for the next generation of evolution. The proposed algorithm IMOEA/D is compared with eMOEA, MOEA/D and NSGA-II, and experimental results show that for most test functions, IMOEA/D proposed is superior to the other three algorithms in terms of convergence rate and distribution. (C) 2016 Elsevier B.V. All rights reserved.

引用

页码：5 / 16

页数：12

共 31 条

[21] Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces
Storn, R
Price, K
[J]. JOURNAL OF GLOBAL OPTIMIZATION, 1997, 11 (04) : 341 - 359
[22] An efficient multi-objective evolutionary algorithm for energy-aware QoS routing in wireless sensor network
Su, Sheng
Yu, Haijie
Wu, Zhenghua
[J]. INTERNATIONAL JOURNAL OF SENSOR NETWORKS, 2013, 13 (04) : 208 - 218
[23] A survey of simulated annealing as a tool for single and multiobjective optimization
Suman, B.
Kumar, P.
[J]. JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY, 2006, 57 (10) : 1143 - 1160
[24] Wang S., 2013, J COMPUT INF SYST, V9, P855
[25] Wu Z.F., 2009, RES DIFFERENTIAL EVO
[26] JADE: Adaptive Differential Evolution With Optional External Archive
Zhang, Jingqiao
Sanderson, Arthur C.
[J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2009, 13 (05) : 945 - 958
[27] Zhang Q-F, 2009, IEEE C EV COMP
[28] MOEA/D: A multiobjective evolutionary algorithm based on decomposition
Zhang, Qingfu
Li, Hui
[J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2007, 11 (06) : 712 - 731
[29] Multiobjective evolutionary algorithms: A comparative case study and the Strength Pareto approach
Zitzler, E
Thiele, L
[J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 1999, 3 (04) : 257 - 271
[30] Performance assessment of multiobjective optimizers: An analysis and review
Zitzler, E
Thiele, L
Laumanns, M
Fonseca, CM
da Fonseca, VG
[J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2003, 7 (02) : 117 - 132

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