Priority rules for job shops with weighted tardiness costs
Management Science
Job shop scheduling by simulated annealing
Operations Research
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
Evolution based learning in a job shop scheduling environment
Computers and Operations Research - Special issue on genetic algorithms
A fast taboo search algorithm for the job shop problem
Management Science
Decomposition methods for large job shops
Computers and Operations Research
Order acceptance using genetic algorithms
Computers and Operations Research
Computing minimal doubly resolving sets of graphs
Computers and Operations Research
A single-machine bi-criterion learning scheduling problem with release times
Expert Systems with Applications: An International Journal
Algorithms for a realistic variant of flowshop scheduling
Computers and Operations Research
A hybrid immune simulated annealing algorithm for the job shop scheduling problem
Applied Soft Computing
Hierarchical Iterated Local Search for the Quadratic Assignment Problem
HM '09 Proceedings of the 6th International Workshop on Hybrid Metaheuristics
A hybrid approach to large-scale job shop scheduling
Applied Intelligence
An optimization approach for the job shop scheduling problem
MATH'09 Proceedings of the 14th WSEAS International Conference on Applied mathematics
Complex scheduling problems using an optimization methodology
WSEAS Transactions on Information Science and Applications
Computers and Operations Research
A hybrid shifting bottleneck-tabu search heuristic for the job shop total weighted tardiness problem
Computers and Operations Research
Computers and Operations Research
A genetic algorithm for the job shop scheduling with a new local search using Monte Carlo method
AIKED'11 Proceedings of the 10th WSEAS international conference on Artificial intelligence, knowledge engineering and data bases
Weighted tardiness minimization in job shops with setup times by hybrid genetic algorithm
CAEPIA'11 Proceedings of the 14th international conference on Advances in artificial intelligence: spanish association for artificial intelligence
Computers and Industrial Engineering
Engineering Applications of Artificial Intelligence
A study of the single-machine two-agent scheduling problem with release times
Applied Soft Computing
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This paper considers the job-shop problem with release dates and due dates, with the objective of minimizing the total weighted tardiness. A genetic algorithm is combined with an iterated local search that uses a longest path approach on a disjunctive graph model. A design of experiments approach is employed to calibrate the parameters and operators of the algorithm. Previous studies on genetic algorithms for the job-shop problem point out that these algorithms are highly depended on the way the chromosomes are decoded. In this paper, we show that the efficiency of genetic algorithms does no longer depend on the schedule builder when an iterated local search is used. Computational experiments carried out on instances of the literature show the efficiency of the proposed algorithm.