Lot-sizing in a foundry using genetic algorithm and repair functions

Authors:
Jerzy Duda
Affiliations:
Faculty of Management, Dept. of Applied Computer Science, AGH University of Science and Technology, Kraków, Poland
Venue:
EvoCOP'05 Proceedings of the 5th European conference on Evolutionary Computation in Combinatorial Optimization
Year:
2005

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Abstract

The paper presents a study of genetic algorithms applied to a lot-sizing problem, which has been formulated for an operational production planning in a foundry. Three variants of genetic algorithm are considered, each of them using special crossover and mutation operators as well as repair functions. The real size test problems, based on the data taken from the production control system, are presented for assessment of the proposed algorithms. The obtained results show that the genetic algorithm with two repair functions can generate good suboptimal solutions in the time, which can be acceptable from the decision maker point of view.