نتایج جستجو برای: parallel machine scheduling problem
تعداد نتایج: 1319150 فیلتر نتایج به سال:
The problem of scheduling G groups of jobs on m unrelated parallel machines is considered. Each group consists of several identical jobs. Implicit in a schedule is a partition of a group into batches; all jobs of a batch are processed jointly. It is possible for diierent batches of the same group to be processed concurrently on diierent machines. However, at any time, a batch can be processed o...
The parallel mechine scheduling problem with unrelated machines is studied where the objective is to minimize the maximum makespan. In this paper, new local search algorithms are proposed where the neighborhood search of a solution uses the “efficiency” of the machinea for each job. It is shown that this method yields better solutions and shorter running times than the more general local search...
Two important characteristics encountered in many real-world scheduling problems are heterogeneous processors and a certain degree of uncertainty about the sizes of jobs. In this paper we address both, and study for the first time a scheduling problem that combines the classical unrelated machine scheduling model with stochastic processing times of jobs. By means of a novel time-indexed linear ...
This paper addresses a scheduling problem motivated by scheduling of diffusion operations in the wafer fabrication facility. In the target problem, jobs arrive at the batch machines at different time instants, and only jobs belonging to the same family can be processed together. Parallel batch machine scheduling typically consists of three types of decisions – batch forming, machine assignment,...
A new unrelated parallel machine scheduling problem with deteriorating 26 effect and the objective of makespan minimization is presented in this paper. The 27 deterioration of each machine (and therefore of the job processing times) is a function of the 28 sequence of jobs that have been processed by the machine and not (as considered in the 29 literature) by the time at which each job is assig...
Scheduling is an important subject of production and operations management area. In flow-shop scheduling, the objective is to obtain a sequence of jobs which when processed in a fixed order of machines, will optimize some well defined criteria. The concept of transportation time is very important in scheduling. Transportation can be done by robots. In situations that robots are used to transpor...
This paper deals with a common due date parallel machines scheduling problem in which each job has a different tardiness penalty. The objective is to minimize the total weighted tardiness. The scheduling problem of minimizing the total weighted tardiness with a common due date on a single machine is known to be ordinary NP-hard. This is also the case for problem Pm|di = d| ∑ wiTi. A new dynamic...
In this paper the problem of job shop scheduling with parallel machines in each stages is discussed. The objective is to minimize the maximum completion time (makespan).This problem is a combination of two classic problems of job shop and parallel machines which in this case parallel machines has been used as kind of flexibility in the job shop problem. The review of literature has shown that t...
In this paper, the train scheduling problem is modelled as a Blocking Parallel-Machine JobShop-Scheduling (BPMJSS) problem. In the model, trains, single-track sections and multiple-track sections respectively are synonymous with jobs, single machines and parallel machines; and an operation is regarded as the movement/traversal of a train across a section. Due to the lack of buffer space, the re...
Traditionally, mathematical optimization methods have been applied in manufacturing industries where production scheduling is one of the most important problems and being actively researched. Extant studies assume that processing times are known or follow a simple distribution. However, actual time factory often unknown likely follows complex Therefore, this study, we consider estimating using ...
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