SOLVING A MULTI-OBJECTIVE FLEXIBLE JOB SHOP SCHEDULING PROBLEM WITH TIMED PETRI NETS AND GENETIC ALGORITHM

2010 ◽  
Vol 02 (02) ◽  
pp. 221-237 ◽  
Author(s):  
HEJIAO HUANG ◽  
TAIPING LU
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling ◽  
Crossover And Mutation

The method presented in this paper is used to solve flexible job shop scheduling problem (JSP) with multiple objectives, which is much more complex than the classical JSP. Based on timed Petri net model, genetic algorithm is applied to solve the scheduling problems. The chromosomes are composed by sequences of transitions, the crossover and mutation operations are based on transition sequences. The experiment result shows that a definite solution to a specific flexible job shop scheduling problem can be found.

scholarly journals Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

2018 ◽  
Vol 2018 ◽  
pp. 1-32 ◽  
Author(s):  
Muhammad Kamal Amjad ◽  
Shahid Ikramullah Butt ◽  
Rubeena Kousar ◽  
Riaz Ahmad ◽  
Mujtaba Hassan Agha ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Future Research ◽  
Flexible Job Shop ◽  
Scheduling Problem ◽  
Scheduling Problems ◽  
Flexible Job Shop Scheduling ◽  
Job Shop Scheduling Problem ◽  
Shop Scheduling

Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA) techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

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