This paper considers two resource constrained single-machine group scheduling problems. These problems involve variable job processing times (general position-dependent learning effects and deteriorating jobs); that is, the processing time of a job is defined by the function that involves its starting time and position in the group, and groups' setup time is a positive strictly decreasing continuous function of the amount of consumed resource. Polynomial time algorithms are proposed to optimally solve the makespan minimization problem under the constraint that the total resource consumption does not exceed a given limit and the total resource consumption minimization problem under the constraint that the makespan does not exceed a given lim...
International audienceThe paper deals with a single machine scheduling problem with job processing t...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...
Job deterioration and machine learning co-exist in various real life scheduling settings. This paper...
International audienceThis paper addresses single-machine scheduling problems under the consideratio...
In this article, single-machine group scheduling with learning effects and convex resource allocatio...
Rapport interne.A single machine scheduling problem is studied. The set of n jobs has been partition...
Special issue with papers presented at the 5th International Conference on Optimization: Techniques ...
This paper considers a group scheduling problem with shorten (i.e., a proportional linear shortening...
This paper deals with a single-machine resource allocation scheduling problem with learning effect a...
We consider single-machine scheduling problems in which the processing time of a job is a function o...
The paper deals with single machine scheduling problems with setup time considerations where the act...
In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJo...
Scheduling with general truncated job-dependent learning effect and resource-dependent processing ti...
Abstract—In this paper, we develop a new scheduling model with learning effects where the actual pro...
m unrelated parallel machines scheduling problems with variable job processing times are considered,...
International audienceThe paper deals with a single machine scheduling problem with job processing t...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...
Job deterioration and machine learning co-exist in various real life scheduling settings. This paper...
International audienceThis paper addresses single-machine scheduling problems under the consideratio...
In this article, single-machine group scheduling with learning effects and convex resource allocatio...
Rapport interne.A single machine scheduling problem is studied. The set of n jobs has been partition...
Special issue with papers presented at the 5th International Conference on Optimization: Techniques ...
This paper considers a group scheduling problem with shorten (i.e., a proportional linear shortening...
This paper deals with a single-machine resource allocation scheduling problem with learning effect a...
We consider single-machine scheduling problems in which the processing time of a job is a function o...
The paper deals with single machine scheduling problems with setup time considerations where the act...
In this paper, we introduce a group scheduling model with time-dependent and position-dependent DeJo...
Scheduling with general truncated job-dependent learning effect and resource-dependent processing ti...
Abstract—In this paper, we develop a new scheduling model with learning effects where the actual pro...
m unrelated parallel machines scheduling problems with variable job processing times are considered,...
International audienceThe paper deals with a single machine scheduling problem with job processing t...
AbstractThis paper introduces a new time-dependent learning effect model into a single-machine sched...
Job deterioration and machine learning co-exist in various real life scheduling settings. This paper...