Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Genetic search methods in air traffic control
Computers and Operations Research
Evolutionary Scheduling: A Review
Genetic Programming and Evolvable Machines
Holonic Job Shop Scheduling Using a Multiagent System
IEEE Intelligent Systems
Development of scheduling strategies with Genetic Fuzzy systems
Applied Soft Computing
Scheduling jobs on parallel machines with setup times and ready times
Computers and Industrial Engineering
Fuzzy rule generation for adaptive scheduling in a dynamic manufacturing environment
Applied Soft Computing
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Genetic programming heuristics for multiple machine scheduling
EuroGP'07 Proceedings of the 10th European conference on Genetic programming
Hybrid metaheuristics in combinatorial optimization: A survey
Applied Soft Computing
Dynamic scheduling with genetic programming
EuroGP'06 Proceedings of the 9th European conference on Genetic Programming
Genetic programming and evolutionary generalization
IEEE Transactions on Evolutionary Computation
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This paper investigates the use of genetic programming in automated synthesis of scheduling heuristics for an arbitrary performance measure. Genetic programming is used to evolve the priority function, which determines the priority values of certain system elements (jobs, machines). The priority function is used within an appropriate meta-algorithm for a given environment, which forms the priority scheduling heuristic. The evolved solutions are compared with existing scheduling heuristics and found to perform similarly to or better than existing algorithms. We intend to show that this approach is particularly useful for combinations of scheduling environments and performance measures for which no adequate scheduling algorithms exist.