Teeradej Wuttipornpun. Hybrid genetic algorithm and tabu search for finite capacity material requirement planning system in assembly flow shop with alternative work centres. (). มหาวิทยาลัยเทคโนโลยีพระจอมเกล้าพระนครเหนือ. สำนักหอสมุดกลาง. : , 2014.
Hybrid genetic algorithm and tabu search for finite capacity material requirement planning system in assembly flow shop with alternative work centres
Noted:
Grant Source King Mongkut's University of Technology North Bangkok 2013.
Abstract:
This report is an attempt of the research title Hybrid genetic algorithm and tabu search
for finite capacity material requirement planning (FCMRP) system in assembly flow
shop with alternative work centres. The research has been granted in 2013 fiscal year
with the total budget of 100,000 Baht (STRI-GEN-56-07). The study team consists of
Dr. Teeradej Wuttipornpun from Department of Industrial Engineering, KMUTNB and
Watcharapan Sukkerd, a Ph.D. student at KMUTNB. This report is a final research
report of the research activities during the 12-month period.
The objective of this research is to propose a hybrid algorithm for FCMRP system
in assembly flow shop with alternative work centres. It is an improvement of the
existing algorithm developed by Wuttipornpun and Yenradee (2014). The improvement
concept is to change from a constructive search adapted in the existing algorithm to an
improvement search in order to determine a better solution. The result shows that the
proposed algorithm greatly outperforms the existing algorithm in 2014 in both total cost
and makespan criteria. The computational time of the proposed algorithm is not more
than 30 minutes which is acceptable for the planner.
There are two major contributions from this research, which are the contributions
to related industries and FCMRP theory. For the related industries, we propose an
alternative method to obtain a better solution for the planner. For the FCMRP theory, a
new hybrid metaheuristic algorithm in assembly flow shop with specific characteristics
is proposed in order to increase a number of effective algorithms in this area