An efficient genetic algorithm for single row facility layout
Abstract
The single row facility layout is the NP-Hard problem of arranging facilities
with given lengths on a line, so as to minimize the weighted sum of the distances
between all pairs of facilities. Owing to its computational complexity, researchers
have developed several heuristics to obtain good quality solutions. In this paper, we
present a genetic algorithm called GENALGO to solve large single row facility layout
problem instances. Our algorithm uses standard genetic operators and periodically
improves the fitness of all individuals. Our computational experiments show that our
genetic algorithm yields high quality solutions in spite of starting with an initial population
that is randomly generated. Our algorithm improves the previously best known
solutions for the 19 instances of 58 benchmark instances and is competitive for most
of the remaining ones.
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