In recent times many research has been focused on assumption that processing times of a job is unfixed. In practice, thus the processing time ofa job processing time of a job may changes due to some factors. We investigated factors that affect the varying processing time of a job under different machine environments. We were able to identify four factors that may influence processing time of a job, these include learning effect, deteriorating effect,maintenance activity and non-monotonic time-dependent processing time. In this paper, we discussed machine environments and their assumption and some features of jobs processing times. We also gave a concise overview on the literature on scheduling with learning effect, deteriorating effect, mai...
Lee and Wu [3] introduce a scheduling model in which the job processing times are affected by both p...
WOS: 000314494700019In traditional scheduling problems, most literature assumes that the processing ...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...
International audienceIn traditional scheduling problems, job processing times are considered consta...
In scheduling theory, the models that have attracted considerable attention during the last two deca...
This paper deals with the machine scheduling problems with the effects of deterioration and learning...
Job deterioration and machine learning co-exist in various real life scheduling settings. This paper...
Although scheduling with deteriorating jobs and learning effect has been widely investigated, schedu...
In classical scheduling models, it is normally assumed that the processing times of jobs are fixed. ...
This paper studies scheduling problems which include a combination of nonlinear job deterioration an...
Although scheduling with deteriorating jobs and learning effect has been widely investigated, schedu...
In this paper, we present both nonlinear job deterioration and nonlinear learning which exist simult...
This paper considers earliness/tardiness (ET) scheduling problem on a parallel machine environment w...
WOS: 000273012500023In traditional scheduling problems, most literature assumes that the processing ...
The main results in a recent paper [1] (J.-B. Wang, D. Wang, G.-D. Zhang, Single-machine scheduling ...
Lee and Wu [3] introduce a scheduling model in which the job processing times are affected by both p...
WOS: 000314494700019In traditional scheduling problems, most literature assumes that the processing ...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...
International audienceIn traditional scheduling problems, job processing times are considered consta...
In scheduling theory, the models that have attracted considerable attention during the last two deca...
This paper deals with the machine scheduling problems with the effects of deterioration and learning...
Job deterioration and machine learning co-exist in various real life scheduling settings. This paper...
Although scheduling with deteriorating jobs and learning effect has been widely investigated, schedu...
In classical scheduling models, it is normally assumed that the processing times of jobs are fixed. ...
This paper studies scheduling problems which include a combination of nonlinear job deterioration an...
Although scheduling with deteriorating jobs and learning effect has been widely investigated, schedu...
In this paper, we present both nonlinear job deterioration and nonlinear learning which exist simult...
This paper considers earliness/tardiness (ET) scheduling problem on a parallel machine environment w...
WOS: 000273012500023In traditional scheduling problems, most literature assumes that the processing ...
The main results in a recent paper [1] (J.-B. Wang, D. Wang, G.-D. Zhang, Single-machine scheduling ...
Lee and Wu [3] introduce a scheduling model in which the job processing times are affected by both p...
WOS: 000314494700019In traditional scheduling problems, most literature assumes that the processing ...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...