We consider scheduling problems in which a job consists of components of different types to be processed on m machines. Each machine is capable of processing components of a single type. Different components of a job are independent and can be processed in parallel on different machines. A job is considered as completed only when all its components have been completed. We study both completion ...

The single-machine scheduling problem with a weight-modifying-activity (WMA) to minimize the total weighted completion time was initially addressed by Mosheiov and Oron in 2020, where activity an option, once performed, weights of subsequent jobs become decreased. This has proven be NP-hard. Following their study, we propose two mixed integer linear programming models (model_1 model_2). Based o...

Abstract : In this paper , we apply the stochastic dynamic programming to approximate the mean project completion time in dynamic Markov PERT networks. It is assumed that the activity durations are independent random variables with exponential distributions, but some social and economical problems influence the mean of activity durations. It is also assumed that the social problems evolve in ac...

in this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). no set-up is necessary between jobs belonging to the same family. a set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i  j, the duration of this set-up being the sequ...

We give a (2 + ǫ)-approximation algorithm for minimizing total weighted completion time on a single machine under release time and precedence constraints. This settles a recent conjecture made in [18]