Priority rules for job shops with weighted tardiness costs
Management Science
The single machine early/tardy problem
Management Science
Heuristics for scheduling unrelated parallel machines
Computers and Operations Research
Scheduling unrelated parallel machines to minimize total weighted tardiness
Computers and Operations Research
A tabu search algorithm for parallel machine total tardiness problem
Computers and Operations Research
Design and Analysis of Experiments
Design and Analysis of Experiments
Unrelated parallel machine scheduling using local search
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Planning production using mathematical programming: The case of a woodturning company
Computers and Operations Research
Robotics and Computer-Integrated Manufacturing
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
Journal of Intelligent Manufacturing
Integrating parts design characteristics and scheduling on parallel machines
Expert Systems with Applications: An International Journal
Sequence-dependent group scheduling problem on unrelated-parallel machines
Expert Systems with Applications: An International Journal
Scheduling jobs in flowshops with the introduction of additional machines in the future
Expert Systems with Applications: An International Journal
Journal of Intelligent Manufacturing
Journal of Intelligent Manufacturing
Electronic Notes in Theoretical Computer Science (ENTCS)
Hi-index | 0.02 |
A methodology for minimizing the weighted tardiness of jobs in unrelated parallel machining scheduling with sequence-dependent setups is presented in this paper. To comply with industrial situations, the dynamic release of jobs and dynamic availability of machines are assumed. Recognizing the inherent difficulty in solving industrial-size problems efficiently, six different search algorithms based on tabu search are developed to identify the best schedule that gives the minimum weighted tardiness. To enhance both the efficiency and efficacy of the search algorithms, four different initial solution finding mechanisms, based on dispatching rules, are developed. While there is no evidence of identifying solutions of better quality by employing a specific initial solution finding mechanism, the use of a specific search algorithm led to identifying solutions of better quality or that required lower computation time, but not both. Based on the extensive statistical analysis performed, the search algorithm with short-term memory and fixed tabu list size is recommended for solving small size problems, while that with long-term memory and minimum frequency for solving medium and large size problems, combined with fixed tabu list size for the former and variable tabu list size for the latter.