Priority rules for job shops with weighted tardiness costs
Management Science
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Proceedings of the 33nd conference on Winter simulation
Using Ranking and Selection to "Clean Up" after Simulation Optimization
Operations Research
A Weighted Modified Due Date Rule for Sequencing to Minimize Weighted Tardiness
Journal of Scheduling
Evolutionary Scheduling: A Review
Genetic Programming and Evolvable Machines
Computers and Industrial Engineering
Towards improved dispatching rules for complex shop floor scenarios: a genetic programming approach
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolutionary Computation for Modeling and Optimization
Evolutionary Computation for Modeling and Optimization
Evolutionary synthesis of multi-agent systems for dynamic dial-a-ride problems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Computers and Industrial Engineering
Nonlinear optimization to generate non-overlapping random dot patterns
Proceedings of the Winter Simulation Conference
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Dispatching rules play an important role especially in semiconductor manufacturing scheduling, because these fabrication facilities are characterized by high complexity and dynamics. The process of developing and adapting dispatching rules is currently a tedious, largely manual task. Coupling Genetic Programming (GP), a global optimization meta-heuristic from the family of Evolutionary Algorithms, with a stochastic discrete event simulation of a complex manufacturing system we are able to automatically generate dispatching rules for a scenario from semiconductor manufacturing. Evolved dispatching rules clearly outperform manually developed rules from literature.