A new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems |
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Authors: | U?ur Özcan Bilal Toklu |
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Affiliation: | 1. Department of Industrial Engineering, Sel?uk University, 42075, Sel?uklu, Konya, Turkey 2. Department of Industrial Engineering, Gazi University, 06570, Maltepe, Ankara, Turkey
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Abstract: | This paper presents a new hybrid improvement heuristic approach to simple straight and U-type assembly line balancing problems
which is based on the idea of adaptive learning approach and simulated annealing. The proposed approach uses a weight parameter
to perturb task priorities of a solution to obtain improved solutions. The weight parameters are then modified using a learning
strategy. The maximization of line efficiency (i.e., the minimization of the number of stations) and the equalization of workloads
among stations (i.e., the minimization of the smoothness index or the minimization of the variation of workloads) are considered
as the performance criteria. In order to clarify the proposed solution methodology, a well known problem taken from literature
is solved. A computational study is conducted by solving a large number of benchmark problems available in the literature
to compare the performance of the proposed approach to the existing methods such as simulated annealing and genetic algorithms.
Some test instances taken from literature are also solved by the proposed approach. The results of the computational study
show that the proposed approach performs quite effectively. It also yields optimal solutions for all test problems within
a short computational time. |
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Keywords: | Assembly line balancing Adaptive learning approach Simulated annealing |
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