Browsing by Subject "Scheduling"

Now showing 1 - 20 of 120

Open Access
Adaptive compute-phase prediction and thread prioritization to mitigate memory access latency
(ACM, 2014-06) Aktürk, İsmail; Öztürk, Özcan
The full potential of chip multiprocessors remains unex- ploited due to the thread oblivious memory access sched- ulers used in off-chip main memory controllers. This is especially pronounced in embedded systems due to limita- Tions in memory. We propose an adaptive compute-phase prediction and thread prioritization algorithm for memory access scheduling for embedded chip multiprocessors. The proposed algorithm eficiently categorize threads based on execution characteristics and provides fine-grained priori- Tization that allows to differentiate threads and prioritize their memory access requests accordingly. The threads in compute phase are prioritized among the threads in mem- ory phase. Furthermore, the threads in compute phase are prioritized among themselves based on the potential of mak- ing more progress in their execution. Compared to the prior works First-Ready First-Come First-Serve (FR-FCFS) and Compute-phase Prediction with Writeback-Refresh Overlap (CP-WO), the proposed algorithm reduces the execution time of the generated workloads up to 23.6% and 12.9%, respectively. Copyright 2014 ACM.
Open Access
An analysis of cyclic scheduling problems in robot centered cells
(Elsevier, 2012) Yıldız, Serdar; Karasan, Oya Ekin; Aktürk, M. Selim
The focus of this study is a robot centered cell consisting of m computer numerical control (CNC) machines producing identical parts. Two pure cycles are singled out and further investigated as prominent cycles in minimizing the cycle time. It has been shown that these two cycles jointly dominate the rest of the pure cycles for a wide range of processing time values. For the remaining region, the worst case performances of these pure cycles are established. The special case of 3-machines is studied extensively in order to provide further insight for the more general case. The situation where the processing times are controllable is analyzed. The proposed pure cycles also dominate the rest when the cycle time and total manufacturing cost objectives are considered simultaneously from a bicriteria optimization point of view. Moreover, they also dominate all of the pure cycles in in-line robotic cells. Finally, the efficient frontier of the 3-machine case with controllable processing times is depicted as an example.
Open Access
Analysis of maintenance policies for M machines with deteriorating performance
(Taylor & Francis, 2000) Berk, E.; Moinzadeh, K.
In this paper, we consider the maintenance scheduling of a group of M identical machines, the performance of which deteriorates with usage. Examples of such situations are frequently found in the heavy machine tooling, petro-chemical and semi-conductor industries among others. Assuming a limited maintenance resource and that the maintenance times are i.i.d., we propose a dynamic maintenance policy which utilities the information about the number of operating machines and their ages. We analyze the system for the special cases of constant and exponentially distributed maintenance times. We investigate the impact of maintenance time variability on system performance and evaluate the performance of various maintenance policies within the proposed policy class when the expected profit rate is maximized.
Open Access
Analysis of order review/release problems in production systems
(Elsevier Science B.V., Amsterdam, Netherlands, 1999) Sabuncuoglu, İhsan; Karapınar, H.Y.
Order Review/Release (ORR) activities have mostly been ignored in past job shop research. In most previous studies, arriving jobs are immediately released to the shop floor without considering any information about the system or job characteristics. In practice however, these jobs are often first collected in a pool and then released to the system according to a specific criterion. Although practitioners often observe the benefits of ORR, researchers have found limited support for the use of these input regulation policies. One objective of this paper is to examine this research paradox in a capacitated system. We also offer a new classification framework for existing research work. Finally, for the first time in this paper, both periodic and continuous ORR methods are compared simultaneously under various experimental conditions against different performance measures. The results of simulation experiments and statistical tests are also presented in the paper.
Open Access
Analysis of reactive scheduling problems in a job shop environment
(Elsevier, 2000) Sabuncuoğlu, İ.; Bayız, M.
In this paper, we study the reactive scheduling problems in a stochastic manufacturing environment. Specifically, we test the several scheduling policies under machine breakdowns in a classical job shop system. In addition, we measure the effect of system size and type of work allocation (uniform and bottleneck) on the system performance. The performance of the system is measured for the mean tardiness and makespan criteria. We also investigate a partial scheduling scheme under both deterministic and stochastic environments for several system configurations.
Open Access
Analytical modeling of multi-channel optical burst switching with multiple traffic classes
(2011) Dinç, Volkan
In this thesis, we study an Optical Burst Switching (OBS) node with links carrying multiple wavelength channels (called hereafter channels) with multiple traffic classes. We assume that offset-based service differentiation is used to differentiate among these traffic classes in terms of packet loss probabilities. We first propose a basic scheme, called bLAUC (Basic Latest Available Unused Channel) for channel scheduling. Although practicality of the bLAUC scheme is relatively limited when compared to other conventional schedulers such as LAUC, we study bLAUC in this thesis due to its tractability to analysis and moreover bLAUC possesses certain crucial properties of conventional schedulers. We then propose an iterative procedure to approximate per-class loss probabilities for the OBS link of interest when packet arrivals to the link are Poisson and packet lengths are exponentially distributed. In our iterative procedure, we model a multi-channel OBS link with Poisson arrivals by a single channel Markov fluid queue with occupancy-dependent packet arrival intensities. The proposed procedure provides acceptable approximations for a wide range of scenarios with relatively low complexity. Consequently, the proposed procedure can be used in optimization problems concerning multiclass OBS and in finding guidelines to effectively utilize OBS resources under loss probability constraints.
Open Access
Auction based scheduling for distributed systems
(2005) Zarifoğlu, Emrah
Businesses deal with huge databases over a geographically distributed supply network. When this is combined with scheduling and planning needs, it becomes too difficult to handle. Recently, Fast Consumer Goods sector tends to consolidate their manufacturing facilities on a single supplier serving to a distributed customer network. This decentralized structure causes imperfect information sharing between customers and the supplier. We model this problem as a single machine distributed scheduling problem with job agents representing the customers and the machine agent representing the supplier. For benchmarking purpose, we analyzed the problem under three different scenarios: decentralized utility case (realistic case), centralized utility case, centralized cost case (classical single machine early/tardy problem). We developed Auction Based Algorithm by exploiting the opportunity to use game theoretic approach to solve the problem in the decentralized utility case. We used optimization techniques (Lagrangean Relaxation and Branch-and-Bound) for the centralized cases. Results of our extensive computational experiments indicate that Auction Based Algorithm converges to the upper bound found for the total utility measure.
Open Access
Batch scheduling to minimize maximum lateness
(Elsevier, 1997) Ghosh, J. B.; Gupta, J. N. D.
We address the single-machine batch scheduling problem which arises when there are job families and setup requirements exist between these families; our objective is to minimize the maximum lateness. As our main result, we give an improved dynamic program for the solution of the problem.
Open Access
Batch scheduling to minimize the weighted number of tardy jobs
(Pergamon Press, 2007) Erel, E.; Ghosh, J. B.
In this paper, we address a single-machine scheduling problem with due dates and batch setup times to minimize the weighted number of tardy jobs. We give a pseudo-polynomial dynamic program and a fully-polynomial approximation scheme for the case where the due dates are uniform within a family.
Open Access
Beam search based algorithm for scheduling machines and AGVs in an FMS
(Institute for Industrial Engineers, 1993) Karabük, S.; Sabuncuoğlu, İhsan
This paper presents a beam search based scheduling algorithm for a random FMS. The proposed algorithm considers finite buffer capacity, routing and sequence flexibilities and generates machine and AGV schedules in varying time windows. The performance of the algorithm is measured using makespan, flow time, and tardiness criteria under various experimental conditions.
Open Access
A beam search-based algorithm and evaluation of scheduling approaches for fexible manufacturing systems
(Taylor & Francis, 1998) Sabuncuoglu İ.; Karabuk, S.
This paper presents a new algorithm for the flexible manufacturing system (FMS) scheduling problem. The proposed algorithm is a heuristic based on filtered beam search. It considers finite buffer capacity, routing and sequence flexibilities and generates machine and automated guided vehicle (AGV) schedules for a given scheduling period. A new deadlock resolution mechanism is also developed as an integral part of the proposed algorithm. The performance of the algorithm is compared with several machine and AGV dispatching rules using mean flow time, mean tardiness and makespan criteria. It is also used to examine the effects of scheduling factors (i.e., machine and AGV load levels, routing and sequence flexibilities, etc.) on the system performance. The results indicate thai the proposed scheduling algorithm yields considerable improvements in system performance over dispatching rules under a wide variety of experimental conditions. © 1998 "IIE".
Open Access
Benefits of forecasting and energy storage in isolated grids with large wind penetration – The case of Sao Vicente
(Elsevier, 2017) Yuan, S.; Kocaman, A.S.; Modi, V.
For electric grids that rely primarily on liquid fuel based power generation for energy provision, e.g. one or more diesel gensets, measures to allow a larger fraction of intermittent sources can pay-off since the displaced is high cost diesel powered generation. This paper presents a case study of Sao Vicente, located in Cape Verde where a particularly high fraction of wind capacity of 5.950ï¿½MW (75% of the average demand) is installed, with diesel gensets forming the dispatchable source of power. This high penetration of intermittent power is managed through conservative forecasting and curtailments. Two potential approaches to reduce curtailments are examined in this paper: 1) an improved wind speed forecasting using a rolling horizon ARIMA model; and 2) energy storage. This case study shows that combining renewable energy forecasting and energy storage is a promising solution which enhances diesel fuel savings as well as enables the isolated grid to further increase the annual renewable energy penetration from the current 30.4% up to 38% while reducing grid unreliability. In general, since renewable energy forecasting ensures more accurate scheduling and energy storage absorbs scheduling error, this solution is applicable to any small size isolated power grid with large renewable energy penetration.
Open Access
Bicriteria robotic cell scheduling with controllable processing times
(Taylor & Francis, 2011) Yildiz, S.; Akturk, M. S.; Karasan, O. E.
The current study deals with a bicriteria scheduling problem arising in an m-machine robotic cell consisting of CNC machines producing identical parts. Such machines by nature possess the process flexibility of altering processing times by modifying the machining conditions at differing manufacturing costs. Furthermore, they possess the operational flexibility of being capable of processing all the operations of these identical parts. This latter flexibility in turn introduced a new class of robot move cycles, called pure cycles, to the literature. Within the restricted class of pure cycles, our task is to find the processing times on machines so as to minimise the cycle time and the manufacturing cost simultaneously. We characterise the set of all non-dominated solutions for two specific pure cycles that have emerged as prominent ones in the literature. We prove that either of these pure cycles is non-dominated for the majority of attainable cycle time values. For the remaining regions, we provide the worst case performance of one of these two cycles.
Open Access
Big-data streaming applications scheduling based on staged multi-armed bandits
(Institute of Electrical and Electronics Engineers, 2016) Kanoun, K.; Tekin, C.; Atienza, D.; Van Der Schaar, M.
Several techniques have been recently proposed to adapt Big-Data streaming applications to existing many core platforms. Among these techniques, online reinforcement learning methods have been proposed that learn how to adapt at run-time the throughput and resources allocated to the various streaming tasks depending on dynamically changing data stream characteristics and the desired applications performance (e.g., accuracy). However, most of state-of-the-art techniques consider only one single stream input in its application model input and assume that the system knows the amount of resources to allocate to each task to achieve a desired performance. To address these limitations, in this paper we propose a new systematic and efficient methodology and associated algorithms for online learning and energy-efficient scheduling of Big-Data streaming applications with multiple streams on many core systems with resource constraints. We formalize the problem of multi-stream scheduling as a staged decision problem in which the performance obtained for various resource allocations is unknown. The proposed scheduling methodology uses a novel class of online adaptive learning techniques which we refer to as staged multi-armed bandits (S-MAB). Our scheduler is able to learn online which processing method to assign to each stream and how to allocate its resources over time in order to maximize the performance on the fly, at run-time, without having access to any offline information. The proposed scheduler, applied on a face detection streaming application and without using any offline information, is able to achieve similar performance compared to an optimal semi-online solution that has full knowledge of the input stream where the differences in throughput, observed quality, resource usage and energy efficiency are less than 1, 0.3, 0.2 and 4 percent respectively.
Open Access
Climbing depth-bounded discrepancy search for solving hybrid flow shop problems
(Inderscience Publishers, 2007) Hmida, A. B.; Huguet, M.-J.; Lopez, P.; Haouari, M.
This paper investigates how to adapt some discrepancy-based search methods to solve Hybrid Flow Shop (HFS) problems in which each stage consists of several identical machines operating in parallel. The objective is to determine a schedule that minimises the makespan. We present here an adaptation of the Depth-bounded Discrepancy Search (DDS) method to obtain near-optimal solutions with makespan of high quality. This adaptation for the HFS contains no redundancy for the search tree expansion. To improve the solutions of our HFS problem, we propose a local search method, called Climbing Depth-bounded Discrepancy Search (CDDS), which is a hybridisation of two existing discrepancy-based methods: DDS and Climbing Discrepancy Search (CDS). CDDS introduces an intensification process around promising solutions. These methods are tested on benchmark problems. Results show that discrepancy methods give promising results and CDDS method gives the best solutions.
Open Access
Common due date early
(2013) Şirvan, Fatma
This study considers a scheduling problem with position-dependent deteriorating jobs and a maintenance activity in a single machine. Even in the absence of maintenance activity and deterioration problem is NP-hard. A solution comprises the following: (i) positions of jobs, (ii) the position of the maintenance activity, (iii) starting time of the first job in the schedule. After the maintenance activity, machine will revert to its initial condition and deterioration will start anew. The objective is to minimize the total weighted earliness and tardiness costs. Jobs scheduled before (after) the due-date are penalized according to their earliness (tardiness) value. Polynomial (O(n log n)) time solutions are provided for some special cases. No polynomial solution exists for instances with tight due-dates. We propose a mixed integer programming model and efficient algorithms for the cases where mathematical formulation is not efficient in terms of computational time requirements. Computational results show that the proposed algorithms perform well in terms of both solution quality and computation time.
Open Access
A comparative study of computational procedures for resource constrained project scheduling problem
(1991) Bala, Hasan
Customarily, the project sclheduling problem is thought in the context of PERT and CPM. Although widely used and powerful, these techniques do not take into account a basic feature of the problem, that is resource limitations. The problem addressed in this study is to schedule the activities of a single project in order that all resource and precedence relationships constraints are satisfied with an objective of minimizing total of activity completion times. Our purpose is to make a computational comparison of some solution procedures for the problem. Firstly, the 0 - 1 formulation of the problem is introduced together with the underlying assumptions. Then, we describe the solution procedures tested in this study. In order to evaluate them, the random activity networks are generated. Finally, we provide the results and conclusions.
Open Access
A comparative study of computational procedures for the resource constrained project scheduling problem
(Elsevier, 1994) Oğuz, O.; Bala, H.
Performance of two new integer programming based heuristics together with some special purpose algorithms for project scheduling are tested from a computational point of view. The objective of the study is to compare the quality of solutions obtained by using these algorithms and reach conclusions about their relative merits on this specific problem. © 1994.
Open Access
Considering manufacturing cost and scheduling performance on a CNC turning machine
(Elsevier, 2007) Gurel, S.; Akturk, M. S.
A well known industry application that allows controllable processing times is the manufacturing operations on CNC machines. For each turning operation as an example, there is a nonlinear relationship between the manufacturing cost and its required processing time on a CNC turning machine. If we consider total manufacturing cost (F1) and total weighted completion time (F2) objectives simultaneously on a single CNC machine, making appropriate processing time decisions is as critical as making job sequencing decisions. We first give an effective model for the problem of minimizing F1 subject to a given F2 level. We deduce some optimality properties for this problem. Based on these properties, we propose a heuristic algorithm to generate an approximate set of efficient solutions. Our computational results indicate that the proposed algorithm performs better than the GAMS/MINOS commercial solver both in terms of solution quality and computational requirements such that the average CPU time is only 8% of the time required by the GAMS/MINOS.
Open Access
Cost and emission impacts of virtual power plant formation in plug-in hybrid electric vehicle penetrated networks
(2013) Arslan, O.; Karasan, O. E.
With increasing interest in alternative energy resources and technologies, mass penetration of PHEVs (plug-in hybrid vehicles) into the electricity grid and widespread utilization of DERs (distributed energy resources) are anticipated in the near future. As an aggregation unit, the VPP (virtual power plant) is introduced for load management and resource scheduling. In this article, we develop an energy management model for VPPs and analyze the cost and emission impacts of VPP formation and PHEV penetration. We conduct a case study for the state of California using real-world data from official resources. An average of 29.5% cost reduction and 79% CO2 and 83% NOx emission reductions are attained as shared benefits of consumers in the case study. Results are illustrative of opportunities that VPP formation can provide for the community. Sensitivity of the results to the DER costs and capacities, battery and gasoline prices are also analyzed. In addition, we prove that charging and discharging do not simultaneously occur in the solutions, which leads to a simplification in traditional energy management models.