NDLI: An efficient grouping genetic algorithm for U-shaped assembly line balancing problems with maximizing production rate

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An efficient grouping genetic algorithm for U-shaped assembly line balancing problems with maximizing production rate

Content Provider	Springer Nature Link
Author	Şahin, Murat Kellegöz, Talip
Copyright Year	2017
Abstract	U-type assembly line is one of the important tools that may increase companies’ production efficiency. In this study, two different modeling approaches proposed for the assembly line balancing problems have been used in modeling type-II U-line balancing problems, and the performances of these models have been compared with each other. It has been shown that using mathematical formulations to solve medium and large size problem instances is impractical since the problem is NP-hard. Therefore, a grouping genetic and simulated annealing algorithms have been developed, and a particle swarm optimization algorithm is adapted to compare with the proposed methods. A special crossover operator that always obtains feasible offspring has been suggested for the proposed grouping genetic algorithm. Furthermore, a local search procedure based on problem-specific knowledge was applied to increase the intensification of the algorithm. A set of well-known benchmark instances was solved to evaluate the effectiveness of the proposed and existing methods. Results showed that while the mathematical formulations can only be used to solve small size instances, metaheuristics can obtain high quality solutions for all size problem instances within acceptable CPU times. Moreover, grouping genetic algorithm has been found to be superior to the other methods according to the number of optimal solutions, or deviations from the lower bound values.
Starting Page	213
Ending Page	229
Page Count	17
File Format	PDF
ISSN	18659284
Journal	Memetic Computing
Volume Number	9
Issue Number	3
e-ISSN	18659292
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-07-17
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Assembly line balancing U-shaped assembly lines Grouping genetic algorithm Simulated annealing Production rate ApplicationMathematics/Computational Methods of Engineering Artificial Intelligence (incl. Robotics) Complex Systems Control, Robotics, Mechatronics Bioinformatics Applications of Mathematics
Content Type	Text
Resource Type	Article
Subject	Control and Optimization Computer Science

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