Artificial bee colony algorithm with genetic algorithm for job shop scheduling problem

2017 ◽  
Author(s):  
Ye Lvshan ◽  
Yuan Dongzhi ◽  
Yu Weiyu
Keyword(s):  
Genetic Algorithm ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Bee Colony

A hybrid artificial bee colony algorithm for the job-shop scheduling problem with no-wait constraint

2015 ◽  
Vol 21 (5) ◽  
pp. 1193-1202 ◽  
Author(s):  
Shyam Sundar ◽  
P. N. Suganthan ◽  
Chua Tay Jin ◽  
Cai Tian Xiang ◽  
Chong Chin Soon
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Bee Colony ◽  
No Wait

An Improved Artificial Bee Colony Algorithm for Job Shop Problem

2010 ◽  
Vol 26-28 ◽  
pp. 657-660 ◽  
Author(s):  
Bao Zhen Yao ◽  
Cheng Yong Yang ◽  
Juan Juan Hu ◽  
Guo Dong Yin ◽  
Bo Yu
Keyword(s):  
Artificial Bee Colony Algorithm ◽  
Production Management ◽  
Artificial Bee Colony ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Benchmark Problems ◽  
Scheduling Problem ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Bee Colony

Job shop scheduling problem (JSP) plays a significant role for production management and combinatorial optimization. An improved artificial bee colony (IABC) algorithm with mutation operation is presented to solve JSP in this paper. The results for some benchmark problems reveal that IABC is effective and efficient compared to those of other approaches. IABC seems to be a powerful tool for optimizing job shop scheduling problem.

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