The shifting bottleneck procedure for job shop scheduling
Management Science
A genetic algorithm for the job shop problem
Computers and Operations Research - Special issue on genetic algorithms
A systematic procedure for setting parameters in simulated annealing algorithms
Computers and Operations Research
Problem difficulty for tabu search in job-shop scheduling
Artificial Intelligence
An Advanced Tabu Search Algorithm for the Job Shop Problem
Journal of Scheduling
A bee colony optimization algorithm to job shop scheduling
Proceedings of the 38th conference on Winter simulation
A hybrid particle swarm optimization for job shop scheduling problem
Computers and Industrial Engineering
Robotics and Computer-Integrated Manufacturing
A very fast TS/SA algorithm for the job shop scheduling problem
Computers and Operations Research
Ant colony optimization combined with taboo search for the job shop scheduling problem
Computers and Operations Research
A genetic algorithm for the Flexible Job-shop Scheduling Problem
Computers and Operations Research
Research of Production Scheduling Algorithm Based on Bottleneck Analysis
CCCM '08 Proceedings of the 2008 ISECS International Colloquium on Computing, Communication, Control, and Management - Volume 03
A multi-modal immune algorithm for the job-shop scheduling problem
Information Sciences: an International Journal
A robust scheduling method based on a multi-objective immune algorithm
Information Sciences: an International Journal
An efficient hybrid algorithm for resource-constrained project scheduling
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem
Information Sciences: an International Journal
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Parallel-machine scheduling to minimize makespan with fuzzy processing times and learning effects
Information Sciences: an International Journal
Planning of business process execution in Business Process Management environments
Information Sciences: an International Journal
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Practical production scheduling problems usually involve some ''bottleneck'' machines, the scheduling policies for which could significantly affect the final solution quality. Therefore, it is beneficial to identify the bottleneck machines beforehand, so that we can intensify the optimization for these machines in the subsequent solving stage. To this end, a bottleneck machine identification algorithm is proposed in this paper for the job shop scheduling problem with the objective of minimizing total tardiness. In order to obtain the instance-specific information about bottleneck machine distribution, we first propose a new optimization model which relaxes some conventional constraints of the standard job shop problem. Then, a simulated annealing algorithm is applied to solve this newly defined problem. Based on the optimization result, the bottleneck characteristic value (which is a measure of bottleneck level) is calculated for each machine. To utilize the obtained bottleneck information for job shop scheduling, we design a genetic algorithm which allocates more computational resources to the identified bottleneck machines by using a hybrid encoding scheme. Computational results verify the effectiveness and the robustness of the proposed bottleneck identification procedure. It is shown that intensifying the local search effort for the bottleneck machines will generally result in higher solution quality within reasonably short computational time.