TY - GEN
T1 - The Concept of Genetic Algorithm Application for Scheduling Operations with Multi-resource Requirements
AU - Paprocka, Iwona
AU - Kalinowski, Krzysztof
AU - Balon, Barbara
N1 - Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2021
Y1 - 2021
N2 - The paper presents the concept of a genetic algorithm for solving the problem of scheduling production processes, in which there are operations requiring the interaction of resources from at least two, different groups of competences. The considered system is based on flexible flow shop and the objective function is associated with minimizing the flow time of tasks. The general schedule generation procedure using the genetic algorithm is presented. Three sub-chromosomes are proposed for describing an individual. First of them represents a precedence feasible order of production tasks. Numbers of parallel machines are coded by the second sub-chromosome of the individual. Numbers of production employees able to execute operation on the set of parallel machines are coded by the third sub-chromosome. The order crossover and shift mutation procedures are described for the proposed chromosome differentiation and selection. Implementation of the developed concept enables parallel planning of positions and human resources (or any groups of resources) and improve practical usability in relation to hierarchical methods of resource planning.
AB - The paper presents the concept of a genetic algorithm for solving the problem of scheduling production processes, in which there are operations requiring the interaction of resources from at least two, different groups of competences. The considered system is based on flexible flow shop and the objective function is associated with minimizing the flow time of tasks. The general schedule generation procedure using the genetic algorithm is presented. Three sub-chromosomes are proposed for describing an individual. First of them represents a precedence feasible order of production tasks. Numbers of parallel machines are coded by the second sub-chromosome of the individual. Numbers of production employees able to execute operation on the set of parallel machines are coded by the third sub-chromosome. The order crossover and shift mutation procedures are described for the proposed chromosome differentiation and selection. Implementation of the developed concept enables parallel planning of positions and human resources (or any groups of resources) and improve practical usability in relation to hierarchical methods of resource planning.
KW - Genetic algorithm
KW - Multi-resources planning
KW - Production scheduling
UR - https://www.scopus.com/pages/publications/85091303241
U2 - 10.1007/978-3-030-57802-2_33
DO - 10.1007/978-3-030-57802-2_33
M3 - Conference contribution
AN - SCOPUS:85091303241
SN - 9783030578015
T3 - Advances in Intelligent Systems and Computing
SP - 342
EP - 351
BT - 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020
A2 - Herrero, Álvaro
A2 - Cambra, Carlos
A2 - Urda, Daniel
A2 - Sedano, Javier
A2 - Quintián, Héctor
A2 - Corchado, Emilio
PB - Springer Science and Business Media Deutschland GmbH
T2 - 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2020
Y2 - 16 September 2020 through 18 September 2020
ER -