Paper Info
Title
Invasive weed optimization algorithm for optimization no-idle flow shop scheduling problem.
Abstract
In this paper, an invasive weed optimization (IWO) scheduling algorithm is presented for optimization no-idle flow-shop scheduling problem (NFSP) with the criterion to minimize the maximum completion time (makespan). Firstly, a simple approach is put forward to calculate the makespan of job sequence. Secondly, the most position value (MPV) method is used to code the weed individuals so that fitness values can be calculated. Then, use the global exploration capacity of IWO to select the best fitness value and its corresponding processing sequence of job by evaluating the fitness of individuals. The results of 12 different scale NFSP benchmarks compared with other algorithms show that NFSP can be effectively solved by IWO with stronger robustness.
Year
DOI
Venue
2014
10.1016/j.neucom.2013.05.063
Neurocomputing
Keywords
Field
DocType
No-idle flow shop scheduling problem,Invasive weed optimization,Makespan,Most position value method,Global exploration capacity,Robustness
Weed,Mathematical optimization,Job shop scheduling,Scheduling (computing),Idle,Flow shop scheduling,Robustness (computer science),Optimization algorithm,Mathematics
Journal
Volume
ISSN
Citations 
137
0925-2312
29
PageRank 
References 
Authors
0.77
19
3
Name
Order
Citations
PageRank
Yongquan Zhou143148.08
Huan Chen2722.75
Guo Zhou3541.81