نتایج جستجو برای: scheduling and optimization
تعداد نتایج: 16892955 فیلتر نتایج به سال:
This paper assumes each user has more than one queue, derives a new packet-dependant proportional fairness power allocation pattern based on the sum of weight capacity and the packet’s priority in users’ queues, and proposes 4 new cross-layer packet-dependant OFDM scheduling schemes based on proportional fairness for heterogeneous classes of traffic. Scenario 1, scenario 2 and scenario 3 lead r...
In this paper, we first introduce a generalized version of open shop scheduling (OSS), called generalized cyclic open shop scheduling (GCOSS) and then develop a hybrid method of metaheuristic to solve this problem. Open shop scheduling is concerned with processing n jobs on m machines, where each job has exactly m operations and operation i of each job has to be processed on machine i . However...
this paper considers identical parallel machines scheduling problem with past-sequence-dependent setup times, deteriorating jobs and learning effects, in which the actual processing time of a job on each machine is given as a function of the processing times of the jobs already processed and its scheduled position on the corresponding machine. in addition, the setup time of a job on each machin...
although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. this paper deals with scheduling jobs in lot streaming flexible flow line problems. the paper mathematically formulates the problem by a mixed integer linear programming model. this model solves small instances to optimality. moreo...
Grid computing is a process of aggregate the functionality of different geographically resources and provide services to the user. Scheduling is most popular research area in grid computing for achieving high performance. In scheduling, tasks are assigning to resources and maintain the execution. Dependencies constraints are need to preserve for workflow scheduling in grid computing. In this pa...
Many scientific applications running in Cloud Computing system are workflow applications that contains large number of tasks and in which tasks are connected by precedence relations. Efficient scheduling the workflow tasks become a challenging issue in Cloud Computing environments because the scheduling decides performance of the applications. Unfortunately, finding the optimal scheduling is kn...
This paper explores the task scheduling algorithm for cloud computing on the basis of Particle Swarm Optimization (PSO). Based on task scheduling problems of the cloud computing, first of all, this paper detailed introduction to cloud computing, task scheduling of cloud computing, particle swarm optimization algorithm and ant colony optimization algorithm. On this basis of the above, task sched...
This paper introduces a new approach for scheduling security constraint unit commitment (SCUC) including wind farms. Because of uncertainty in wind power production, we tried to develop a new method for incorporating wind power generation in power plant scheduling. For this, wind power generation modeled with unit commitment in a non-linear optimization problem and simulated by submitting diffe...
Bio-Inspired computing is the subset of Nature-Inspired computing. Job Shop Scheduling Problem is categorized under popular scheduling problems. In this research work, Bacterial Foraging Optimization was hybridized with Ant Colony Optimization and a new technique Hybrid Bacterial Foraging Optimization for solving Job Shop Scheduling Problem was proposed. The optimal solutions obtained by propos...
in this paper, we considered solving approaches to flexible job shop problems. makespan is not a good evaluation criterion with overlapping in operations assumption. accordingly, in addition to makespan, we used total machine work loading time and critical machine work loading time as evaluation criteria. as overlapping in operations is a practical assumption in chemical, petrochemical, and gla...
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