Procedia Manufacturing · 2020 · 40 citations · 17 references
ManagementComputer ScienceIndustrial EngineeringAutomationOptimizationSchedulingCombinatorial OptimizationEvolutionary ComputationFlow Shop SchedulingGenetic AlgorithmsProduction SchedulingReal-time OptimizationDispatching RulesFlow ShopHybrid Flow Shop SchedulingPrinted Circuit BoardsReal-time Decision MakingScheduling With Sequence-dependent Setup TimesSequence-dependent Setup TimesSetup Times
The paper shows how assigning different predefined dispatching rules for a predefined number of times at any points in time using a genetic algorithm can solve a hybrid flow shop scheduling problem with sequence-dependent setup times, using the example of a company producing printed circuit boards. The paper describes the implementation of the genetic algorithm, analyses the results for four different data sets and compares them with the results of applying standard dispatching rules. Using a genetic algorithm to assign dispatching rules achieves better solutions than simple dispatching rules often used in industrial practice. The genetic algorithm already achieves good solutions after a few seconds up to a few minutes, which means that this approach can be used for real-time decision making in a cyber-physical system in the age of Industry 4.0.
17
Genetic algorithms in search, optimization, and machine learning
Choice Reviews Online · 1989 · 49.3K citations
Scheduling: Theory, Algorithms, and Systems
Michael Pinedo · IIE Transactions · 1996 · 6.3K citations
S. S. Panwalkar, Wafik H. Iskander · Operations Research · 1977 · 1.3K citations