A genetic algorithm for bin packing and line balancing

The authors present an efficient genetic algorithm for two NP-hard problems, the bin packing and the line balancing problems. They define the two problems precisely and specify a cost function suitable for the bin packing problem. It is shown that the classic genetic algorithm performs poorly on grouping problems and an encoding of solutions of fitting these problems is presented. Efficient crossover and mutation operators are introduced for bin packing. The modification necessary to fit these operators for line balancing is given. Results of performance tests on randomly generated data are included. The line balancing tests cover real-world problem sizes. The results and areas of further research are discussed