Merits of using chromosome representations and shadow chromosomes in genetic algorithms for solving scheduling problems.
Chi-Shiuan LinI-Ling LeeMuh-Cherng WuPublished in: Robotics Comput. Integr. Manuf. (2019)
Keyphrases
- genetic algorithm
- scheduling problem
- genetic operators
- job shop scheduling problem
- fitness function
- evolutionary algorithm
- simulated annealing
- tabu search
- job shop scheduling
- genetic algorithm ga
- neural network
- search heuristics
- metaheuristic
- crossover and mutation
- flowshop
- single machine
- crossover operator
- binary strings
- artificial neural networks
- multi objective
- fuzzy logic
- combinatorial optimization
- evolution strategy
- search algorithm for solving
- genetic programming
- mutation operator
- memetic algorithm
- higher level
- processing times
- genetic search
- distributed constraint satisfaction problems
- evolutionary computation
- symbolic representation
- parallel machines
- np hard
- setup times
- light source
- job shop
- lower bound