Job-dependent Learning Effects Research Articles

Minimizing the maximum lateness in a single-machine scheduling problem with the normal time-dependent and job-dependent learning effect

We prove that the problem of single machine lateness minimization with a normal time-dependent and job-dependent learning effect in decision version is NP-complete.

A note on due-date assignment and single-machine scheduling with deteriorating jobs and learning effects

The concepts of deteriorating jobs and learning effects have been individually studied in many scheduling problems. This note considers a single-machine scheduling problem with deteriorating jobs and learning effects. All of the jobs have a common (but unknown) due date. The objective is to minimize the sum of the weighted earliness, tardiness and due-date penalties. An O(n3) algorithm is proposed to optimally solve the problem with deteriorating jobs and job-dependent learning effect. Besides, an O(n log n) algorithm is provided to solve the problem with deteriorating jobs and job-independent learning effect.

A note on single-machine scheduling with job-dependent learning effects

Mosheiov and Sidney (2003) showed that the makespan minimization problem with job-dependent learning effects can be formulated as an assignment problem and solved in O( n 3) time. We show that this problem can be solved in O( nlog n) time by sequencing the jobs according to the shortest processing time (SPT) order if we utilize the observation that the job-dependent learning rates are correlated with the level of sophistication of the jobs and assume that these rates are bounded from below. The optimality of the SPT sequence is also preserved when the job-dependent learning rates are inversely correlated with the level of sophistication of the jobs and bounded from above.

Scheduling with job-dependent learning effects and multiple rate-modifying activities

We consider a scheduling problem with job-dependent learning effects and multiple rate-modifying activities. The learning effects manifest such that the processing time of a job is a decreasing function of its position in a sequence. By job-dependent learning effects, we mean that the learning of the jobs is different. A rate-modifying activity is an activity that changes the production rate of a machine. So the actual processing time of a job in our problem is a variable, which depends not only on its position in a sequence but also on whether it is scheduled before or after a rate-modifying activity. We assume that each machine may have multiple rate-modifying activities. The objective is to minimize the total completion time. We show that all the cases of the problem are polynomially solvable.