A Hybrid Genetic Algorithm for the One-Dimensional Minimax Bin-Packing Problem with Assignment Constraints

  • Mariona VilàEmail author
  • Jordi Pereira
Part of the Lecture Notes in Economics and Mathematical Systems book series (LNE, volume 682)


In this paper, the one-dimensional minimax bin-packing problem with assignment constraints is studied. Among other applications, this problem is used in test-splitting, which consists in assigning several sets of questions into different questionnaires so that every one of these questionnaires contains one question from each one of the original sets. Questions have a weight associated, which typically corresponds to a measure of their difficulty, and the objective is to split the questions among the questionnaires in such a way that the weights are distributed as evenly as possible. We propose a hybrid genetic algorithm for solving this problem, which is then tested on a benchmark set of practically-sized instances. The results show its efficiency in solving large size instances from the literature.


Genetic Algorithm Simulated Annealing Hybrid Genetic Algorithm Simulated Annealing Procedure Assignment Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Escola Universitària d’Enginyeria Tècnica IndustrialUniversitat Politècnica de CatalunyaBarcelonaSpain
  2. 2.Departamento de Ingeniería IndustrialUniversidad Católica del NorteAntofagastaChile

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