Management Science
Quality Engineering Using Robust Design
Quality Engineering Using Robust Design
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Expert Systems with Applications: An International Journal
A simulated annealing heuristic for the capacitated location routing problem
Computers and Industrial Engineering
A framework for evolutionary optimization with approximate fitnessfunctions
IEEE Transactions on Evolutionary Computation
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It is known that two interrelated problems called as line balancing and model sequencing should be solved simultaneously for an efficient implementation of a mixed-model U-shape assembly line in a JIT (Just in Time) environment. On the other hand, three versions of assembly line balancing problem can be identified: Type I, Type II, and Type E. There are only two articles (Kara, Ozcan, & Peker, 2007a and Hamzadayi & Yildiz, 2012) related to simultaneous balancing and sequencing of mixed-model U-lines for minimizing the number of stations (Type 1 problem) by ignoring the fixed model sequence in the current literature. In this paper, a simulated annealing algorithm is proposed for solving a problem of type 1 by ignoring the fixed model sequence. Accordingly, simulated annealing based fitness evaluation approach proposed by Hamzadayi and Yildiz (2012) is enhanced by adding the tabu list, and inserted into the proposed algorithm. Implementation difficulties experienced in meta-heuristics based on solution modification for solving these types of problems are demonstrated. 'Absolute deviation of workloads' (ADW) is quite frequently used as performance criteria in the literature. It is found that ADW is an insufficient performance criterion for evaluating the performance of the solutions, and this is showed by means of an illustrative example. The parameters of the proposed algorithm are reviewed for calibrating the algorithm by means of Taguchi design of experiments. Performance of the proposed approach is tested through a set of test problems. The results of computational experiments indicate that the proposed approach is an effective method in solving simultaneous line balancing/model sequencing problems for mixed-model U-lines for minimizing the number of stations.