Scheduling two chains of unit jobs on one machine: A polyhedral study

Networks ◽  
2011 ◽  
Vol 58 (2) ◽  
pp. 103-113 ◽  
Author(s):  
Claudio Arbib ◽  
Martine Labbé ◽  
Mara Servilio
Keyword(s):  
Author(s):  
Lijuan Li ◽  
Yongdong Chen ◽  
Bin Zhou ◽  
Hongliang Liu ◽  
Yongfei Liu

AbstractWith the increase in the proportion of multiple renewable energy sources, power electronics equipment and new loads, power systems are gradually evolving towards the integration of multi-energy, multi-network and multi-subject affected by more stochastic excitation with greater intensity. There is a problem of establishing an effective stochastic dynamic model and algorithm under different stochastic excitation intensities. A Milstein-Euler predictor-corrector method for a nonlinear and linearized stochastic dynamic model of a power system is constructed to numerically discretize the models. The optimal threshold model of stochastic excitation intensity for linearizing the nonlinear stochastic dynamic model is proposed to obtain the corresponding linearization threshold condition. The simulation results of one-machine infinite-bus (OMIB) systems show the correctness and rationality of the predictor-corrector method and the linearization threshold condition for the power system stochastic dynamic model. This study provides a reference for stochastic modelling and efficient simulation of power systems with multiple stochastic excitations and has important application value for stability judgment and security evaluation.


Author(s):  
Chin-Chia Wu ◽  
Ameni Azzouz ◽  
Jia-Yang Chen ◽  
Jianyou Xu ◽  
Wei-Lun Shen ◽  
...  

AbstractThis paper studies a single-machine multitasking scheduling problem together with two-agent consideration. The objective is to look for an optimal schedule to minimize the total tardiness of one agent subject to the total completion time of another agent has an upper bound. For this problem, a branch-and-bound method equipped with several dominant properties and a lower bound is exploited to search optimal solutions for small size jobs. Three metaheuristics, cloud simulated annealing algorithm, genetic algorithm, and simulated annealing algorithm, each with three improvement ways, are proposed to find the near-optimal solutions for large size jobs. The computational studies, experiments, are provided to evaluate the capabilities for the proposed algorithms. Finally, statistical analysis methods are applied to compare the performances of these algorithms.


Author(s):  
Klaus Jansen ◽  
Kim-Manuel Klein ◽  
Marten Maack ◽  
Malin Rau

AbstractInteger linear programs of configurations, or configuration IPs, are a classical tool in the design of algorithms for scheduling and packing problems where a set of items has to be placed in multiple target locations. Herein, a configuration describes a possible placement on one of the target locations, and the IP is used to choose suitable configurations covering the items. We give an augmented IP formulation, which we call the module configuration IP. It can be described within the framework of n-fold integer programming and, therefore, be solved efficiently. As an application, we consider scheduling problems with setup times in which a set of jobs has to be scheduled on a set of identical machines with the objective of minimizing the makespan. For instance, we investigate the case that jobs can be split and scheduled on multiple machines. However, before a part of a job can be processed, an uninterrupted setup depending on the job has to be paid. For both of the variants that jobs can be executed in parallel or not, we obtain an efficient polynomial time approximation scheme (EPTAS) of running time $$f(1/\varepsilon )\cdot \mathrm {poly}(|I|)$$ f ( 1 / ε ) · poly ( | I | ) . Previously, only constant factor approximations of 5/3 and $$4/3 + \varepsilon $$ 4 / 3 + ε , respectively, were known. Furthermore, we present an EPTAS for a problem where classes of (non-splittable) jobs are given, and a setup has to be paid for each class of jobs being executed on one machine.


2016 ◽  
Vol 210 ◽  
pp. 223-234
Author(s):  
Manoel Campêlo ◽  
Victor A. Campos ◽  
Ricardo C. Corrêa ◽  
Diego Delle Donne ◽  
Javier Marenco ◽  
...  

Author(s):  
Xi Gu ◽  
Xiaoning Jin ◽  
Jun Ni

Real-time maintenance decision making in large manufacturing system is complex because it requires the integration of different information, including the degradation states of machines, as well as inventories in the intermediate buffers. In this paper, by using a discrete time Markov chain (DTMC) model, we consider the real-time maintenance policies in manufacturing systems consisting of multiple machines and intermediate buffers. The optimal policy is investigated by using a Markov Decision Process (MDP) approach. This policy is compared with a baseline policy, where the maintenance decision on one machine only depends on its degradation state. The result shows how the structures of the policies are affected by the buffer capacities and real-time buffer levels.


Jurnal METRIS ◽  
2019 ◽  
Vol 20 (2) ◽  
pp. 77-82
Author(s):  
Yanto Yanto ◽  
Marsellinus Bachtiar Wahju

This study aims to determine the utilization of the worker’s time in the filling process, packaging department, a cup and bottled water company. Considering the aim of the study and the task characteristics, work sampling technique was used. Two production lines and two work stations were selected for time studyanalysis. In each work station, two workers with different tasks were involved for the time analysis. A number 586 and 1710 observations from Worker 1 in Line 1 and Line 2, and 586 and 1440 observations from Worker 2 in Line 1 and Line 2 were taken and observed. Results showed that the utilization of worker’s time are 31.7% and 33.6 % of Worker 1 in Line 1 and Line 2, and 25.6% and 21.0% of Worker 2 in Line 1 and Line 2. Results of significant testing showed that no significant differences were found for workers’ time utilization between Worker 1 in Line 1 and Worker 1 in Line 2 (Z=-0.82, p=0.41) and between Worker 2 in Line 1 and Worker 2 in Line 2 (Z=2.17, p=0.03) for α=0.01. Regarding findings in this study, it is reasonable for the management to consider work station which one worker per machine instead of two workers per one machine.


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