A genetic algorithm for flowshop sequencing
Computers and Operations Research - Special issue on genetic algorithms
A note on scheduling on a single processor with speed dependent on a number of executed jobs
Information Processing Letters
Tabu Search
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
An improved NEH heuristic to minimize makespan in permutation flow shops
Computers and Operations Research
A new approach to the learning effect: Beyond the learning curve restrictions
Computers and Operations Research
Computers and Operations Research
Time-Dependent Scheduling
Some single-machine and m-machine flowshop scheduling problems with learning considerations
Information Sciences: an International Journal
Two-machine flow shop problem with effects of deterioration and learning
Computers and Industrial Engineering
Experience-based approach to scheduling problems with the learning effect
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Computers and Operations Research
Adaptive job routing and scheduling
Engineering Applications of Artificial Intelligence
Scheduling problems with deteriorating jobs and learning effects including proportional setup times
Computers and Industrial Engineering
Computers & Mathematics with Applications
A note on the learning effect in multi-agent optimization
Expert Systems with Applications: An International Journal
Computers and Industrial Engineering
The single-machine total weighted tardiness scheduling problem with position-based learning effects
Computers and Operations Research
Unrelated parallel-machine scheduling with aging effects and multi-maintenance activities
Computers and Operations Research
Computers and Operations Research
A Comprehensive Survey of Multiagent Reinforcement Learning
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Hi-index | 0.01 |
This paper considers flowshop scheduling problems where job processing times are described by position dependent functions, i.e., dependent on the number of processed jobs, that model learning or aging effects. We prove that the two-machine flowshop problem to minimize the maximum completion time (makespan) is NP-hard if job processing times are described by non-decreasing position dependent functions (aging effect) on at least one machine and strongly NP-hard if job processing times are varying on both machines. Furthermore, we construct fast NEH, tabu search with a fast neighborhood search and simulated annealing algorithms that solve the problem with processing times described by arbitrary position dependent functions that model both learning and aging effects. The efficiency of the proposed methods is numerically analyzed.