Invasive Weed Optimization Algorithm for Solving Permutation Flow-Shop Scheduling Problem

被引：14

作者：

Chen, Huan ^{[1
]}

Zhou, Yongquan ^{[1
,2
]}

He, Sucai ^{[1
]}

Ouyang, Xinxin ^{[1
]}

Guo, Peigang ^{[1
]}

机构：

[1] Guangxi Univ Nationalities, Coll Informat Sci & Engn, Nanning 530006, Peoples R China

[2] Guangxi Key Lab Hybrid Computat & IC Design Anal, Nanning 530006, Peoples R China

来源：

JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE | 2013年 / 10卷 / 03期

关键词：

Permutation Flow-Shop Scheduling Problem; Invasive Weed Optimization; Most Position Value Method; Global Exploration Capacity;

D O I：

10.1166/jctn.2013.2759

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

An Invasive Weed Optimization (IWO) scheduling algorithm for solving Permutation Flow-shop Scheduling Problem (PFSP) is proposed. The Most Position Value (MPV) method is used to coding the weed individuals so that fitness values can be calculated. Then, the global exploration capacity of IWO is used to select the best fitness value and its corresponding processing sequence of job by evaluating the fitness of individuals. The results of 6 PFSP benchmarks compared with other algorithms show that PFSP can be effectively solved by IWO with adaptability and robustness.

引用

页码：708 / 713

页数：6

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