With the trend towards greater product customization and shorter delivery time,
the use of mixed model assembly lines is increasing. A line balancing approach is
needed that can address the complex nature of the mixed model line and produce near optimal
solutions to problems of realistic size. Due to the combinatorial nature of the line
balancing problem, exact solution techniques are limited to small problems. Heuristic
methods, on the other hand, are often too simplistic to find good solutions. Furthermore,
many of the existing techniques cannot be expanded to handle the mixed model problem.
Simulated Annealing (SA) is a search methodology which has exhibited good
results when applied to combinatorial optimization problems. In fact, researchers have
found that SA is able to find near-optimal solutions while its processing time increases
only as a polynomial function of problem size. However, none of the applications found
in the literature fully explore the technique's ability to handle a highly-constrained
problem such as line balancing.
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