Single-machine group scheduling with a time-dependent learning effect
Computers and Operations Research
Single machine scheduling with past-sequence-dependent setup times and learning effects
Information Processing Letters
Two-machine flow shop problem with effects of deterioration and learning
Computers and Industrial Engineering
Single-machine scheduling with learning effect and deteriorating jobs
Computers and Industrial Engineering
Scheduling problems with deteriorating jobs and learning effects including proportional setup times
Computers and Industrial Engineering
Single-machine group scheduling problems under the effects of deterioration and learning
Computers and Industrial Engineering
Single machine scheduling with past-sequence-dependent setup times and deteriorating jobs
Computers and Industrial Engineering
Computers and Operations Research
Some single-machine scheduling problems with a truncation learning effect
Computers and Industrial Engineering
Computers and Industrial Engineering
Two-agent scheduling with learning consideration
Computers and Industrial Engineering
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This paper studies the single-machine scheduling problem with time-dependent learning effect and setup times considerations. The time-dependent learning effect means that the processing time of a job is defined by a function of the total normal processing time of the already processed jobs. The setup times are proportional to the length of the already processed jobs, i.e., the setup times are past-sequence-dependent (p-s-d). We consider the following objective functions: the makespan, the total completion time, the sum of the quadratic job completion times, the total weighted completion time and the maximum lateness. We show that the makespan minimization problem, the total completion time minimization problem and the sum of the quadratic job completion times minimization problem can be solved in polynomial time, respectively. We also show that the total weighted completion time minimization problem and the maximum lateness minimization problem can be solved in polynomial time under certain conditions.