MIP-based GRASP and Genetic Algorithm for Balancing Transfer Lines
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.
KeywordsGenetic Algorithm Greedy Randomize Adaptive Search Procedure Assembly Line Balance Assembly Line Balance Problem Greedy Function
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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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