We consider a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that jobs arrive online, and there is no knowledge about the jobs that will arrive in the future. The mod...

This paper addresses the problem of optimizing the scheduling of a production system, using a decentralized heuristic in a parallel machine environment. The proposed algorithm extends the use of the traveling salesman problem for scheduling in single machine models to a multiple machine problem. Here, the algorithm is applied to a complex production environment with time constrains, and its per...

This paper introduces a new scheduling algorithm for parallel single-agent search, transposition table driven work scheduling, that places the transposition table at the heart of the parallel work scheduling. The scheme results in less synchronization overhead, less processor idle time, and less redundant search effort. Measurements on a 128-processor parallel machine show that the scheme achie...

In this research, Lagrangian relaxation algorithms are proposed for Hybrid Flow-Shop (HFS) scheduling problems. Conventional HFS consists of a series of production stages, each of which has several identical parallel machines and no buffer spaces are considered. Jobs are processed through all stages in the same direction. In the previous researches, they are assumed that the capacity of buffer ...

This paper represents linkage network of queues consisting of biserial and parallel servers linked to a common server in series with a flowshop scheduling system consisting of two machines. The significant transportation time of the jobs from one machine to another is also considered. Further, the completion time of jobs/customers (waiting time + service time) in the queue network is the set...

The parallel machine scheduling problem has been a popular topic for many years due to its theoretical and practical importance. This paper addresses the robust makespan optimization on unrelated with sequence-dependent setup times, where processing times are uncertain, only knowledge is time intervals they take values from. We propose model min-max regret criterion formulate this problem. To s...

This study deals with an unrelated parallel machine scheduling problem additional resources (UPMR). That is one of the important sub-problems in scheduling. UPMR consists a set jobs on machines. In addition to that, number or more are needed. very and its importance comes from wealth applications; they applicable engineering scientific situations manufacturing systems such as industrial robots,...