Abstract
Abstract In this chapter, we consider a problem of balancing transfer lines with multi-spindle machines. The problem has a number of distinct features in comparison with the well-studied assembly line balancing problem, such as parameterized operation times, non-strict precedence constraints, and parallel operations execution. We propose a mixed-integer programming (MIP)-based greedy randomized adaptive search procedure (GRASP) and a genetic algorithm (GA) for this problem using a MIP formulation. Both algorithms are implemented in GAMS using the CPLEX MIP solver and compared to problem-specific heuristics on randomly generated instances of different types. The results of computational experiments indicate that on large-scale problem instances the proposed methods have an advantage over the methods from literature for finding high quality solutions. The MIP-based recombination operator that arranges the elements of parent solutions in the best possible way is shown to be useful in the GA.
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Keywords
- Genetic Algorithm
- Greedy Randomize Adaptive Search Procedure
- Assembly Line Balance
- Assembly Line Balance Problem
- Greedy Function
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Acknowledgements
The authors thank Michael R. Bussieck for helpful discussions on better usage of GAMS potential. The research is supported by the Russian Foundation for Basic Research, grant 07-01-00410.
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Dolgui, A., Eremeev, A., Guschinskaya, O. (2009). MIP-based GRASP and Genetic Algorithm for Balancing Transfer Lines. In: Maniezzo, V., Stützle, T., Voß, S. (eds) Matheuristics. Annals of Information Systems, vol 10. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1306-7_7
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