Flexible job shop scheduling problem in manufacturing

OpenAIRE

Curralo, Ana; Pereira, Ana I.; Barbosa, José; Leitão, Paulo

2013-01-01

This paper addresses a real assembly cell: the AIP-PRIMECA cell at the Université de Valenciennes et du Hainaut-Cambrésis, in France. This system can be viewed as a Flexible Job Shop, leading to the formulation of a Flexible Job Shop Scheduling Problem (FJSSP).

Job schedulers for Big data processing in Hadoop environment: testing real-life schedulers using benchmark programs

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Mohd Usama

2017-11-01

Full Text Available At present, big data is very popular, because it has proved to be much successful in many fields such as social media, E-commerce transactions, etc. Big data describes the tools and technologies needed to capture, manage, store, distribute, and analyze petabyte or larger-sized datasets having different structures with high speed. Big data can be structured, unstructured, or semi structured. Hadoop is an open source framework that is used to process large amounts of data in an inexpensive and efficient way, and job scheduling is a key factor for achieving high performance in big data processing. This paper gives an overview of big data and highlights the problems and challenges in big data. It then highlights Hadoop Distributed File System (HDFS, Hadoop MapReduce, and various parameters that affect the performance of job scheduling algorithms in big data such as Job Tracker, Task Tracker, Name Node, Data Node, etc. The primary purpose of this paper is to present a comparative study of job scheduling algorithms along with their experimental results in Hadoop environment. In addition, this paper describes the advantages, disadvantages, features, and drawbacks of various Hadoop job schedulers such as FIFO, Fair, capacity, Deadline Constraints, Delay, LATE, Resource Aware, etc, and provides a comparative study among these schedulers.

Scheduling Parallel Jobs Using Migration and Consolidation in the Cloud

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Xiaocheng Liu

2012-01-01

Full Text Available An increasing number of high performance computing parallel applications leverages the power of the cloud for parallel processing. How to schedule the parallel applications to improve the quality of service is the key to the successful host of parallel applications in the cloud. The large scale of the cloud makes the parallel job scheduling more complicated as even simple parallel job scheduling problem is NP-complete. In this paper, we propose a parallel job scheduling algorithm named MEASY. MEASY adopts migration and consolidation to enhance the most popular EASY scheduling algorithm. Our extensive experiments on well-known workloads show that our algorithm takes very good care of the quality of service. For two common parallel job scheduling objectives, our algorithm produces an up to 41.1% and an average of 23.1% improvement on the average response time; an up to 82.9% and an average of 69.3% improvement on the average slowdown. Our algorithm is robust even in terms that it allows inaccurate CPU usage estimation and high migration cost. Our approach involves trivial modification on EASY and requires no additional technique; it is practical and effective in the cloud environment.

A genetic algorithm-based job scheduling model for big data analytics.

Science.gov (United States)

Lu, Qinghua; Li, Shanshan; Zhang, Weishan; Zhang, Lei

Big data analytics (BDA) applications are a new category of software applications that process large amounts of data using scalable parallel processing infrastructure to obtain hidden value. Hadoop is the most mature open-source big data analytics framework, which implements the MapReduce programming model to process big data with MapReduce jobs. Big data analytics jobs are often continuous and not mutually separated. The existing work mainly focuses on executing jobs in sequence, which are often inefficient and consume high energy. In this paper, we propose a genetic algorithm-based job scheduling model for big data analytics applications to improve the efficiency of big data analytics. To implement the job scheduling model, we leverage an estimation module to predict the performance of clusters when executing analytics jobs. We have evaluated the proposed job scheduling model in terms of feasibility and accuracy.

Job schedul in Grid batch farms

International Nuclear Information System (INIS)

Gellrich, Andreas

2014-01-01

We present here a study for a scheduler which cooperates with the queueing system TORQUE and is tailored to the needs of a HEP-dominated large Grid site with around 10000 jobs slots. Triggered by severe scaling problems of MAUI, a scheduler, referred to as MYSCHED, was developed and put into operation. We discuss conceptional aspects as well as experiences after almost two years of running.

Simultaneous Scheduling of Jobs, AGVs and Tools Considering Tool Transfer Times in Multi Machine FMS By SOS Algorithm

Science.gov (United States)

Sivarami Reddy, N.; Ramamurthy, D. V., Dr.; Prahlada Rao, K., Dr.

2017-08-01

This article addresses simultaneous scheduling of machines, AGVs and tools where machines are allowed to share the tools considering transfer times of jobs and tools between machines, to generate best optimal sequences that minimize makespan in a multi-machine Flexible Manufacturing System (FMS). Performance of FMS is expected to improve by effective utilization of its resources, by proper integration and synchronization of their scheduling. Symbiotic Organisms Search (SOS) algorithm is a potent tool which is a better alternative for solving optimization problems like scheduling and proven itself. The proposed SOS algorithm is tested on 22 job sets with makespan as objective for scheduling of machines and tools where machines are allowed to share tools without considering transfer times of jobs and tools and the results are compared with the results of existing methods. The results show that the SOS has outperformed. The same SOS algorithm is used for simultaneous scheduling of machines, AGVs and tools where machines are allowed to share tools considering transfer times of jobs and tools to determine the best optimal sequences that minimize makespan.

Scheduling Non-Preemptible Jobs to Minimize Peak Demand

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Sean Yaw

2017-10-01

Full Text Available This paper examines an important problem in smart grid energy scheduling; peaks in power demand are proportionally more expensive to generate and provision for. The issue is exacerbated in local microgrids that do not benefit from the aggregate smoothing experienced by large grids. Demand-side scheduling can reduce these peaks by taking advantage of the fact that there is often flexibility in job start times. We focus attention on the case where the jobs are non-preemptible, meaning once started, they run to completion. The associated optimization problem is called the peak demand minimization problem, and has been previously shown to be NP-hard. Our results include an optimal fixed-parameter tractable algorithm, a polynomial-time approximation algorithm, as well as an effective heuristic that can also be used in an online setting of the problem. Simulation results show that these methods can reduce peak demand by up to 50% versus on-demand scheduling for household power jobs.

Backfilling with Fairness and Slack for Parallel Job Scheduling

International Nuclear Information System (INIS)

Sodan, Angela C; Wei Jin

2010-01-01

Parallel job scheduling typically combines a basic policy like FCFS with backfilling, i.e. moving jobs to an earlier than their regular scheduling position if they do not delay the jobs ahead in the queue according to the rules of the backfilling approach applied. Commonly used are conservative and easy backfilling which either have worse response times but better predictability or better response times and poor predictability. The paper proposes a relaxation of conservative backfilling by permitting to shift jobs within certain constraints to backfill more jobs and reduce fragmentation and subsequently obtain better response times. At the same time, deviation from fairness is kept low and predictability remains high. The results of the experimentation evaluation show that the goals are met, with response-time performance lying as expected between conservative and easy backfilling.

Backfilling with Fairness and Slack for Parallel Job Scheduling

Energy Technology Data Exchange (ETDEWEB)

Sodan, Angela C; Wei Jin, E-mail: acsodan@uwindsor.ca [University of Windsor, Computer Science, Windsor, Ontario (Canada)

2010-11-01

Parallel job scheduling typically combines a basic policy like FCFS with backfilling, i.e. moving jobs to an earlier than their regular scheduling position if they do not delay the jobs ahead in the queue according to the rules of the backfilling approach applied. Commonly used are conservative and easy backfilling which either have worse response times but better predictability or better response times and poor predictability. The paper proposes a relaxation of conservative backfilling by permitting to shift jobs within certain constraints to backfill more jobs and reduce fragmentation and subsequently obtain better response times. At the same time, deviation from fairness is kept low and predictability remains high. The results of the experimentation evaluation show that the goals are met, with response-time performance lying as expected between conservative and easy backfilling.

Job shop scheduling by local search

NARCIS (Netherlands)

Aarts, E.H.L.; Lenstra, J.K.; Laarhoven, van P.J.M.; Ulder, N.L.J.

1992-01-01

We present a computational performance analysis of local search algorithms for job shop scheduling. The algorithms under investigation are iterative improvement, simulated annealing, threshold accepting and genetic local search. Our study shows that simulated annealing performs best in the sense

A multi-criteria model for maintenance job scheduling

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Sunday A. Oke

2007-12-01

Full Text Available This paper presents a multi-criteria maintenance job scheduling model, which is formulated using a weighted multi-criteria integer linear programming maintenance scheduling framework. Three criteria, which have direct relationship with the primary objectives of a typical production setting, were used. These criteria are namely minimization of equipment idle time, manpower idle time and lateness of job with unit parity. The mathematical model constrained by available equipment, manpower and job available time within planning horizon was tested with a 10-job, 8-hour time horizon problem with declared equipment and manpower available as against the required. The results, analysis and illustrations justify multi-criteria consideration. Thus, maintenance managers are equipped with a tool for adequate decision making that guides against error in the accumulated data which may lead to wrong decision making. The idea presented is new since it provides an approach that has not been documented previously in the literature.

Variable Neighborhood Search for Parallel Machines Scheduling Problem with Step Deteriorating Jobs

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Wenming Cheng

2012-01-01

Full Text Available In many real scheduling environments, a job processed later needs longer time than the same job when it starts earlier. This phenomenon is known as scheduling with deteriorating jobs to many industrial applications. In this paper, we study a scheduling problem of minimizing the total completion time on identical parallel machines where the processing time of a job is a step function of its starting time and a deteriorating date that is individual to all jobs. Firstly, a mixed integer programming model is presented for the problem. And then, a modified weight-combination search algorithm and a variable neighborhood search are employed to yield optimal or near-optimal schedule. To evaluate the performance of the proposed algorithms, computational experiments are performed on randomly generated test instances. Finally, computational results show that the proposed approaches obtain near-optimal solutions in a reasonable computational time even for large-sized problems.

Selection and scheduling of jobs with time-dependent duration

OpenAIRE

DM Seegmuller; SE Visagie; HC de Kock; WJ Pienaar

2007-01-01

In this paper two mathematical programming models, both with multiple objective functions, are proposed to solve four related categories of job scheduling problems. All four of these categories have the property that the duration of the jobs is dependent on the time of implementation and in some cases the preceding job. Furthermore, some jobs (restricted to subsets of the total pool of jobs) can, to different extents, run in parallel. In addition, not all the jobs need necessarily be implemen...

Job shop scheduling by local search

NARCIS (Netherlands)

Vaessens, R.J.M.; Aarts, E.H.L.; Lenstra, J.K.

1994-01-01

We survey solution methods for the job shop scheduling problem with an emphasis on local search. We discuss both cleterministic and randomized local search methods as well as the applied neighborhoods. We compare the computational performance of the various methods in terms of their effectiveness

Two-Agent Scheduling to Minimize the Maximum Cost with Position-Dependent Jobs

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Long Wan

2015-01-01

Full Text Available This paper investigates a single-machine two-agent scheduling problem to minimize the maximum costs with position-dependent jobs. There are two agents, each with a set of independent jobs, competing to perform their jobs on a common machine. In our scheduling setting, the actual position-dependent processing time of one job is characterized by variable function dependent on the position of the job in the sequence. Each agent wants to fulfil the objective of minimizing the maximum cost of its own jobs. We develop a feasible method to achieve all the Pareto optimal points in polynomial time.

An improved ant colony optimization algorithm with fault tolerance for job scheduling in grid computing systems.

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Hajara Idris

Full Text Available The Grid scheduler, schedules user jobs on the best available resource in terms of resource characteristics by optimizing job execution time. Resource failure in Grid is no longer an exception but a regular occurring event as resources are increasingly being used by the scientific community to solve computationally intensive problems which typically run for days or even months. It is therefore absolutely essential that these long-running applications are able to tolerate failures and avoid re-computations from scratch after resource failure has occurred, to satisfy the user's Quality of Service (QoS requirement. Job Scheduling with Fault Tolerance in Grid Computing using Ant Colony Optimization is proposed to ensure that jobs are executed successfully even when resource failure has occurred. The technique employed in this paper, is the use of resource failure rate, as well as checkpoint-based roll back recovery strategy. Check-pointing aims at reducing the amount of work that is lost upon failure of the system by immediately saving the state of the system. A comparison of the proposed approach with an existing Ant Colony Optimization (ACO algorithm is discussed. The experimental results of the implemented Fault Tolerance scheduling algorithm show that there is an improvement in the user's QoS requirement over the existing ACO algorithm, which has no fault tolerance integrated in it. The performance evaluation of the two algorithms was measured in terms of the three main scheduling performance metrics: makespan, throughput and average turnaround time.

Selection and scheduling of jobs with time-dependent duration

Directory of Open Access Journals (Sweden)

DM Seegmuller

2007-06-01

Full Text Available In this paper two mathematical programming models, both with multiple objective functions, are proposed to solve four related categories of job scheduling problems. All four of these categories have the property that the duration of the jobs is dependent on the time of implementation and in some cases the preceding job. Furthermore, some jobs (restricted to subsets of the total pool of jobs can, to different extents, run in parallel. In addition, not all the jobs need necessarily be implemented during the given time period.

Overlap Algorithms in Flexible Job-shop Scheduling

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Celia Gutierrez

2014-06-01

Full Text Available The flexible Job-shop Scheduling Problem (fJSP considers the execution of jobs by a set of candidate resources while satisfying time and technological constraints. This work, that follows the hierarchical architecture, is based on an algorithm where each objective (resource allocation, start-time assignment is solved by a genetic algorithm (GA that optimizes a particular fitness function, and enhances the results by the execution of a set of heuristics that evaluate and repair each scheduling constraint on each operation. The aim of this work is to analyze the impact of some algorithmic features of the overlap constraint heuristics, in order to achieve the objectives at a highest degree. To demonstrate the efficiency of this approach, experimentation has been performed and compared with similar cases, tuning the GA parameters correctly.

Preventive maintenance optimization for a multi-component system under changing job shop schedule

International Nuclear Information System (INIS)

Zhou Xiaojun; Lu Zhiqiang; Xi Lifeng

2012-01-01

Variability and small lot size is a common feature for many discrete manufacturing processes designed to meet a wide array of customer needs. Because of this, job shop schedule often has to be continuously updated in reaction to changes in production plan. Generally, the aim of preventive maintenance is to ensure production effectiveness and therefore the preventive maintenance models must have the ability to be adaptive to changes in job shop schedule. In this paper, a dynamic opportunistic preventive maintenance model is developed for a multi-component system with considering changes in job shop schedule. Whenever a job is completed, preventive maintenance opportunities arise for all the components in the system. An optimal maintenance practice is dynamically determined by maximizing the short-term cumulative opportunistic maintenance cost savings for the system. The numerical example shows that the scheme obtained by the proposed model can effectively address the preventive maintenance scheduling problem caused by the changes in job shop schedule and is more efficient than the ones based on two other commonly used preventive maintenance models.

Performance analysis of job scheduling policies in parallel supercomputing environments

Energy Technology Data Exchange (ETDEWEB)

Naik, V.K.; Squillante, M.S. [IBM T.J. Watson Research Center, Yorktown Heights, NY (United States); Setia, S.K. [George Mason Univ., Fairfax, VA (United States). Dept. of Computer Science

1993-12-31

In this paper the authors analyze three general classes of scheduling policies under a workload typical of largescale scientific computing. These policies differ in the manner in which processors are partitioned among the jobs as well as the way in which jobs are prioritized for execution on the partitions. Their results indicate that existing static schemes do not perform well under varying workloads. Adaptive policies tend to make better scheduling decisions, but their ability to adjust to workload changes is limited. Dynamic partitioning policies, on the other hand, yield the best performance and can be tuned to provide desired performance differences among jobs with varying resource demands.

Application of Tabu Search Algorithm in Job Shop Scheduling

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Betrianis Betrianis

2010-10-01

Full Text Available Tabu Search is one of local search methods which is used to solve the combinatorial optimization problem. This method aimed is to make the searching process of the best solution in a complex combinatorial optimization problem(np hard, ex : job shop scheduling problem, became more effective, in a less computational time but with no guarantee to optimum solution.In this paper, tabu search is used to solve the job shop scheduling problem consists of 3 (three cases, which is ordering package of September, October and November with objective of minimizing makespan (Cmax. For each ordering package, there is a combination for initial solution and tabu list length. These result then  compared with 4 (four other methods using basic dispatching rules such as Shortest Processing Time (SPT, Earliest Due Date (EDD, Most Work Remaining (MWKR dan First Come First Served (FCFS. Scheduling used Tabu Search Algorithm is sensitive for variables changes and gives makespan shorter than scheduling used by other four methods.

A priority-based heuristic algorithm (PBHA for optimizing integrated process planning and scheduling problem

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Muhammad Farhan Ausaf

2015-12-01

Full Text Available Process planning and scheduling are two important components of a manufacturing setup. It is important to integrate them to achieve better global optimality and improved system performance. To find optimal solutions for integrated process planning and scheduling (IPPS problem, numerous algorithm-based approaches exist. Most of these approaches try to use existing meta-heuristic algorithms for solving the IPPS problem. Although these approaches have been shown to be effective in optimizing the IPPS problem, there is still room for improvement in terms of quality of solution and algorithm efficiency, especially for more complicated problems. Dispatching rules have been successfully utilized for solving complicated scheduling problems, but haven’t been considered extensively for the IPPS problem. This approach incorporates dispatching rules with the concept of prioritizing jobs, in an algorithm called priority-based heuristic algorithm (PBHA. PBHA tries to establish job and machine priority for selecting operations. Priority assignment and a set of dispatching rules are simultaneously used to generate both the process plans and schedules for all jobs and machines. The algorithm was tested for a series of benchmark problems. The proposed algorithm was able to achieve superior results for most complex problems presented in recent literature while utilizing lesser computational resources.

Filling the Holes: Work Schedulers as Job Crafters of Employment Practice in Long-Term Health Care

Science.gov (United States)

Kossek, Ellen Ernst; Piszczek, Matthew M.; Mcalpine, Kristie L.; Hammer, Leslie B.; Burke, Lisa

2016-01-01

Although work schedulers serve an organizational role influencing decisions about balancing conflicting stakeholder interests over schedules and staffing, scheduling has primarily been described as an objective activity or individual job characteristic. The authors use the lens of job crafting to examine how schedulers in 26 health care facilities enact their roles as they “fill holes” to schedule workers. Qualitative analysis of interview data suggests that schedulers expand their formal scope and influence to meet their interpretations of how to manage stakeholders (employers, workers, and patients). The authors analyze variations in the extent of job crafting (cognitive, physical, relational) to broaden role repertoires. They find evidence that some schedulers engage in rule-bound interpretation to avoid role expansion. They also identify four types of schedulers: enforcers, patient-focused schedulers, employee-focused schedulers, and balancers. The article adds to the job-crafting literature by showing that job crafting is conducted not only to create meaningful work but also to manage conflicting demands and to mediate among the competing labor interests of workers, clients, and employers. PMID:27721517

Cultural-Based Genetic Tabu Algorithm for Multiobjective Job Shop Scheduling

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Yuzhen Yang

2014-01-01

Full Text Available The job shop scheduling problem, which has been dealt with by various traditional optimization methods over the decades, has proved to be an NP-hard problem and difficult in solving, especially in the multiobjective field. In this paper, we have proposed a novel quadspace cultural genetic tabu algorithm (QSCGTA to solve such problem. This algorithm provides a different structure from the original cultural algorithm in containing double brief spaces and population spaces. These spaces deal with different levels of populations globally and locally by applying genetic and tabu searches separately and exchange information regularly to make the process more effective towards promising areas, along with modified multiobjective domination and transform functions. Moreover, we have presented a bidirectional shifting for the decoding process of job shop scheduling. The computational results we presented significantly prove the effectiveness and efficiency of the cultural-based genetic tabu algorithm for the multiobjective job shop scheduling problem.

Two-Agent Single-Machine Scheduling of Jobs with Time-Dependent Processing Times and Ready Times

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Jan-Yee Kung

2013-01-01

Full Text Available Scheduling involving jobs with time-dependent processing times has recently attracted much research attention. However, multiagent scheduling with simultaneous considerations of jobs with time-dependent processing times and ready times is relatively unexplored. Inspired by this observation, we study a two-agent single-machine scheduling problem in which the jobs have both time-dependent processing times and ready times. We consider the model in which the actual processing time of a job of the first agent is a decreasing function of its scheduled position while the actual processing time of a job of the second agent is an increasing function of its scheduled position. In addition, each job has a different ready time. The objective is to minimize the total completion time of the jobs of the first agent with the restriction that no tardy job is allowed for the second agent. We propose a branch-and-bound and several genetic algorithms to obtain optimal and near-optimal solutions for the problem, respectively. We also conduct extensive computational results to test the proposed algorithms and examine the impacts of different problem parameters on their performance.

Solving Flexible Job-Shop Scheduling Problem Using Gravitational Search Algorithm and Colored Petri Net

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Behnam Barzegar

2012-01-01

Full Text Available Scheduled production system leads to avoiding stock accumulations, losses reduction, decreasing or even eliminating idol machines, and effort to better benefitting from machines for on time responding customer orders and supplying requested materials in suitable time. In flexible job-shop scheduling production systems, we could reduce time and costs by transferring and delivering operations on existing machines, that is, among NP-hard problems. The scheduling objective minimizes the maximal completion time of all the operations, which is denoted by Makespan. Different methods and algorithms have been presented for solving this problem. Having a reasonable scheduled production system has significant influence on improving effectiveness and attaining to organization goals. In this paper, new algorithm were proposed for flexible job-shop scheduling problem systems (FJSSP-GSPN that is based on gravitational search algorithm (GSA. In the proposed method, the flexible job-shop scheduling problem systems was modeled by color Petri net and CPN tool and then a scheduled job was programmed by GSA algorithm. The experimental results showed that the proposed method has reasonable performance in comparison with other algorithms.

Scheduling Agreeable Jobs On A Single Machine To Minimize ...

African Journals Online (AJOL)

Journal of Applied Science and Technology ... (NP) scheduling of number of jobs on a single machine to minimize weighted number of early and tardy jobs where the earliest start times and latest due date are agreeable (i.e. earliest start time must increase in the same sequence as latest due dates) has been considered.

A new genetic algorithm for flexible job-shop scheduling problems

International Nuclear Information System (INIS)

Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia

2015-01-01

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

A new genetic algorithm for flexible job-shop scheduling problems

Energy Technology Data Exchange (ETDEWEB)

Driss, Imen; Mouss, Kinza Nadia; Laggoun, Assia [University of Batna, Batna (Algeria)

2015-03-15

Flexible job-shop scheduling problem (FJSP), which is proved to be NP-hard, is an extension of the classical job-shop scheduling problem. In this paper, we propose a new genetic algorithm (NGA) to solve FJSP to minimize makespan. This new algorithm uses a new chromosome representation and adopts different strategies for crossover and mutation. The proposed algorithm is validated on a series of benchmark data sets and tested on data from a drug manufacturing company. Experimental results prove that the NGA is more efficient and competitive than some other existing algorithms.

Genetic algorithm and neural network hybrid approach for job-shop scheduling

OpenAIRE

Zhao, Kai; Yang, Shengxiang; Wang, Dingwei

1998-01-01

Copyright @ 1998 ACTA Press This paper proposes a genetic algorithm (GA) and constraint satisfaction adaptive neural network (CSANN) hybrid approach for job-shop scheduling problems. In the hybrid approach, GA is used to iterate for searching optimal solutions, CSANN is used to obtain feasible solutions during the iteration of genetic algorithm. Simulations have shown the valid performance of the proposed hybrid approach for job-shop scheduling with respect to the quality of solutions and ...

Work schedule manager gap analysis : assessing the future training needs of work schedule managers using a strategic job analysis approach

Science.gov (United States)

2010-05-01

This report documents the results of a strategic job analysis that examined the job tasks and knowledge, skills, abilities, and other characteristics (KSAOs) needed to perform the job of a work schedule manager. The strategic job analysis compared in...

Multi-objective group scheduling optimization integrated with preventive maintenance

Science.gov (United States)

Liao, Wenzhu; Zhang, Xiufang; Jiang, Min

2017-11-01

This article proposes a single-machine-based integration model to meet the requirements of production scheduling and preventive maintenance in group production. To describe the production for identical/similar and different jobs, this integrated model considers the learning and forgetting effects. Based on machine degradation, the deterioration effect is also considered. Moreover, perfect maintenance and minimal repair are adopted in this integrated model. The multi-objective of minimizing total completion time and maintenance cost is taken to meet the dual requirements of delivery date and cost. Finally, a genetic algorithm is developed to solve this optimization model, and the computation results demonstrate that this integrated model is effective and reliable.

The comparison of predictive scheduling algorithms for different sizes of job shop scheduling problems

Science.gov (United States)

Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.; Krenczyk, D.

2016-08-01

In the paper a survey of predictive and reactive scheduling methods is done in order to evaluate how the ability of prediction of reliability characteristics influences over robustness criteria. The most important reliability characteristics are: Mean Time to Failure, Mean Time of Repair. Survey analysis is done for a job shop scheduling problem. The paper answers the question: what method generates robust schedules in the case of a bottleneck failure occurrence before, at the beginning of planned maintenance actions or after planned maintenance actions? Efficiency of predictive schedules is evaluated using criteria: makespan, total tardiness, flow time, idle time. Efficiency of reactive schedules is evaluated using: solution robustness criterion and quality robustness criterion. This paper is the continuation of the research conducted in the paper [1], where the survey of predictive and reactive scheduling methods is done only for small size scheduling problems.

Manufacturing scheduling systems an integrated view on models, methods and tools

CERN Document Server

Framinan, Jose M; Ruiz García, Rubén

2014-01-01

The book is devoted to the problem of manufacturing scheduling, which is the efficient allocation of jobs (orders) over machines (resources) in a manufacturing facility. It offers a comprehensive and integrated perspective on the different aspects required to design and implement systems to efficiently and effectively support manufacturing scheduling decisions. Obtaining economic and reliable schedules constitutes the core of excellence in customer service and efficiency in manufacturing operations. Therefore, scheduling forms an area of vital importance for competition in manufacturing companies. However, only a fraction of scheduling research has been translated into practice, due to several reasons. First, the inherent complexity of scheduling has led to an excessively fragmented field in which different sub problems and issues are treated in an independent manner as goals themselves, therefore lacking a unifying view of the scheduling problem. Furthermore, mathematical brilliance and elegance has sometime...

Integrated test schedule for buried waste integrated demonstration

International Nuclear Information System (INIS)

Brown, J.T.; McDonald, J.K.

1992-05-01

The Integrated Test Schedule incorporates the various schedules the Buried Waste Integrated Demonstration (BWID) supports into one document. This document contains the Federal Facilities Agreement and Consent Order schedules for the Idaho National Engineering Laboratory, Hanford Reservation, Oak Ridge Reservation, and Fernald Environmental Materials Center. Included in the Integrated Test Schedule is the Buried Waste Integrated Demonstration ''windows of opportunity'' schedule. The ''windows of opportunity'' schedule shows periods of time in which Buried Waste Integrated Demonstration Program-sponsored technology demonstrations could support key decisions in the Federal Facilities Agreement and Consent Order. Schedules for the Buried Waste Integrated Demonstration-sponsored technology task plans are categorized by technology area and divided by current fiscal year and out-year. Total estimated costs for Buried Waste Integrated Demonstration-sponsored Technology Task Plans for FY-92 through FY-97 are $74.756M

Scheduling preemptable jobs on identical processors under varying availability of an additional continuous resource

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Różycki Rafał

2016-09-01

Full Text Available In this work we consider a problem of scheduling preemptable, independent jobs, characterized by the fact that their processing speeds depend on the amounts of a continuous, renewable resource allocated to jobs at a time. Jobs are scheduled on parallel, identical machines, with the criterion of minimization of the schedule length. Since two categories of resources occur in the problem: discrete (set of machines and continuous, it is generally called a discrete-continuous scheduling problem. The model studied in this paper allows the total available amount of the continuous resource to vary over time, which is a practically important generalization that has not been considered yet for discrete-continuous scheduling problems. For this model we give some properties of optimal schedules on a basis of which we propose a general methodology for solving the considered class of problems. The methodology uses a two-phase approach in which, firstly, an assignment of machines to jobs is defined and, secondly, for this assignment an optimal continuous resource allocation is found by solving an appropriate mathematical programming problem. In the approach various cases are considered, following from assumptions made on the form of the processing speed functions of jobs. For each case an iterative algorithm is designed, leading to an optimal solution in a finite number of steps.

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, S.

1999-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

A tabu search algorithm for scheduling a single robot in a job-shop environment

NARCIS (Netherlands)

Hurink, Johann L.; Knust, Sigrid

2002-01-01

We consider a single-machine scheduling problem which arises as a subproblem in a job-shop environment where the jobs have to be transported between the machines by a single transport robot. The robot scheduling problem may be regarded as a generalization of the travelling-salesman problem with time

A Pareto archive floating search procedure for solving multi-objective flexible job shop scheduling problem

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J. S. Sadaghiani

2014-04-01

Full Text Available Flexible job shop scheduling problem is a key factor of using efficiently in production systems. This paper attempts to simultaneously optimize three objectives including minimization of the make span, total workload and maximum workload of jobs. Since the multi objective flexible job shop scheduling problem is strongly NP-Hard, an integrated heuristic approach has been used to solve it. The proposed approach was based on a floating search procedure that has used some heuristic algorithms. Within floating search procedure utilize local heuristic algorithms; it makes the considered problem into two sections including assigning and sequencing sub problem. First of all search is done upon assignment space achieving an acceptable solution and then search would continue on sequencing space based on a heuristic algorithm. This paper has used a multi-objective approach for producing Pareto solution. Thus proposed approach was adapted on NSGA II algorithm and evaluated Pareto-archives. The elements and parameters of the proposed algorithms were adjusted upon preliminary experiments. Finally, computational results were used to analyze efficiency of the proposed algorithm and this results showed that the proposed algorithm capable to produce efficient solutions.

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

OpenAIRE

Amjad, Muhammad Kamal; Butt, Shahid Ikramullah; Kousar, Rubeena; Ahmad, Riaz; Agha, Mujtaba Hassan; Faping, Zhang; Anjum, Naveed; Asgher, Umer

2018-01-01

Flexible Job Shop Scheduling Problem (FJSSP) is an extension of the classical Job Shop Scheduling Problem (JSSP). The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA) have gained the most popularity. Keeping in...

Scheduling Network Traffic for Grid Purposes

DEFF Research Database (Denmark)

Gamst, Mette

This thesis concerns scheduling of network traffic in grid context. Grid computing consists of a number of geographically distributed computers, which work together for solving large problems. The computers are connected through a network. When scheduling job execution in grid computing, data...... transmission has so far not been taken into account. This causes stability problems, because data transmission takes time and thus causes delays to the execution plan. This thesis proposes the integration of job scheduling and network routing. The scientific contribution is based on methods from operations...... research and consists of six papers. The first four considers data transmission in grid context. The last two solves the data transmission problem, where the number of paths per data connection is bounded from above. The thesis shows that it is possible to solve the integrated job scheduling and network...

Job Scheduling with Efficient Resource Monitoring in Cloud Datacenter

Directory of Open Access Journals (Sweden)

Shyamala Loganathan

2015-01-01

Full Text Available Cloud computing is an on-demand computing model, which uses virtualization technology to provide cloud resources to users in the form of virtual machines through internet. Being an adaptable technology, cloud computing is an excellent alternative for organizations for forming their own private cloud. Since the resources are limited in these private clouds maximizing the utilization of resources and giving the guaranteed service for the user are the ultimate goal. For that, efficient scheduling is needed. This research reports on an efficient data structure for resource management and resource scheduling technique in a private cloud environment and discusses a cloud model. The proposed scheduling algorithm considers the types of jobs and the resource availability in its scheduling decision. Finally, we conducted simulations using CloudSim and compared our algorithm with other existing methods, like V-MCT and priority scheduling algorithms.

Skipping Strategy (SS) for Initial Population of Job-Shop Scheduling Problem

Science.gov (United States)

Abdolrazzagh-Nezhad, M.; Nababan, E. B.; Sarim, H. M.

2018-03-01

Initial population in job-shop scheduling problem (JSSP) is an essential step to obtain near optimal solution. Techniques used to solve JSSP are computationally demanding. Skipping strategy (SS) is employed to acquire initial population after sequence of job on machine and sequence of operations (expressed in Plates-jobs and mPlates-jobs) are determined. The proposed technique is applied to benchmark datasets and the results are compared to that of other initialization techniques. It is shown that the initial population obtained from the SS approach could generate optimal solution.

Parallelization and scheduling of data intensive particle physics analysis jobs on clusters of PCs

CERN Document Server

Ponce, S

2004-01-01

Summary form only given. Scheduling policies are proposed for parallelizing data intensive particle physics analysis applications on computer clusters. Particle physics analysis jobs require the analysis of tens of thousands of particle collision events, each event requiring typically 200ms processing time and 600KB of data. Many jobs are launched concurrently by a large number of physicists. At a first view, particle physics jobs seem to be easy to parallelize, since particle collision events can be processed independently one from another. However, since large amounts of data need to be accessed, the real challenge resides in making an efficient use of the underlying computing resources. We propose several job parallelization and scheduling policies aiming at reducing job processing times and at increasing the sustainable load of a cluster server. Since particle collision events are usually reused by several jobs, cache based job splitting strategies considerably increase cluster utilization and reduce job ...

Decentralized Job Scheduling in the Cloud Based on a Spatially Generalized Prisoner’s Dilemma Game

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Gąsior Jakub

2015-12-01

Full Text Available We present in this paper a novel distributed solution to a security-aware job scheduling problem in cloud computing infrastructures. We assume that the assignment of the available resources is governed exclusively by the specialized brokers assigned to individual users submitting their jobs to the system. The goal of this scheme is allocating a limited quantity of resources to a specific number of jobs minimizing their execution failure probability and total completion time. Our approach is based on the Pareto dominance relationship and implemented at an individual user level. To select the best scheduling strategies from the resulting Pareto frontiers and construct a global scheduling solution, we developed a decision-making mechanism based on the game-theoretic model of Spatial Prisoner’s Dilemma, realized by selfish agents operating in the two-dimensional cellular automata space. Their behavior is conditioned by the objectives of the various entities involved in the scheduling process and driven towards a Nash equilibrium solution by the employed social welfare criteria. The performance of the scheduler applied is verified by a number of numerical experiments. The related results show the effectiveness and scalability of the scheme in the presence of a large number of jobs and resources involved in the scheduling process.

On-line scheduling of two-machine open shops where jobs arrive over time

NARCIS (Netherlands)

Chen, B.; Vestjens, A.P.A.; Woeginger, G.J.

1998-01-01

We investigate the problem of on-line scheduling two-machine open shops with the objective of minimizing the makespan.Jobs arrive independently over time, and the existence of a job is not known until its arrival. In the clairvoyant on-line model, the processing requirement of every job becomes

Data location-aware job scheduling in the grid. Application to the GridWay metascheduler

International Nuclear Information System (INIS)

Delgado Peris, Antonio; Hernandez, Jose; Huedo, Eduardo; Llorente, Ignacio M

2010-01-01

Grid infrastructures constitute nowadays the core of the computing facilities of the biggest LHC experiments. These experiments produce and manage petabytes of data per year and run thousands of computing jobs every day to process that data. It is the duty of metaschedulers to allocate the tasks to the most appropriate resources at the proper time. Our work reviews the policies that have been proposed for the scheduling of grid jobs in the context of very data-intensive applications. We indicate some of the practical problems that such models will face and describe what we consider essential characteristics of an optimum scheduling system: aim to minimise not only job turnaround time but also data replication, flexibility to support different virtual organisation requirements and capability to coordinate the tasks of data placement and job allocation while keeping their execution decoupled. These ideas have guided the development of an enhanced prototype for GridWay, a general purpose metascheduler, part of the Globus Toolkit and member of the EGEE's RESPECT program. Current GridWay's scheduling algorithm is unaware of data location. Our prototype makes it possible for job requests to set data needs not only as absolute requirements but also as functions for resource ranking. As our tests show, this makes it more flexible than currently used resource brokers to implement different data-aware scheduling algorithms.

On-line scheduling on a single machine : maximizing the number of early jobs

NARCIS (Netherlands)

Hoogeveen, J.A.; Potts, C.N.; Woeginger, G.J.

2000-01-01

This note deals with the scheduling problem of maximizing the number of early jobs on a single machine. We investigate the on-line version of this problem in the Preemption-Restart model. This means that jobs may be preempted, but preempting results in all the work done on this job so far being

Proposed algorithm to improve job shop production scheduling using ant colony optimization method

Science.gov (United States)

Pakpahan, Eka KA; Kristina, Sonna; Setiawan, Ari

2017-12-01

This paper deals with the determination of job shop production schedule on an automatic environment. On this particular environment, machines and material handling system are integrated and controlled by a computer center where schedule were created and then used to dictate the movement of parts and the operations at each machine. This setting is usually designed to have an unmanned production process for a specified interval time. We consider here parts with various operations requirement. Each operation requires specific cutting tools. These parts are to be scheduled on machines each having identical capability, meaning that each machine is equipped with a similar set of cutting tools therefore is capable of processing any operation. The availability of a particular machine to process a particular operation is determined by the remaining life time of its cutting tools. We proposed an algorithm based on the ant colony optimization method and embedded them on matlab software to generate production schedule which minimize the total processing time of the parts (makespan). We test the algorithm on data provided by real industry and the process shows a very short computation time. This contributes a lot to the flexibility and timelines targeted on an automatic environment.

One-machine job-scheduling with non-constant capacity - Minimizing weighted completion times

NARCIS (Netherlands)

Amaddeo, H.F.; Amaddeo, H.F.; Nawijn, W.M.; van Harten, Aart

1997-01-01

In this paper an n-job one-machine scheduling problem is considered, in which the machine capacity is time-dependent and jobs are characterized by their work content. The objective is to minimize the sum of weighted completion times. A necessary optimality condition is presented and we discuss some

A novel discrete PSO algorithm for solving job shop scheduling problem to minimize makespan

Science.gov (United States)

Rameshkumar, K.; Rajendran, C.

2018-02-01

In this work, a discrete version of PSO algorithm is proposed to minimize the makespan of a job-shop. A novel schedule builder has been utilized to generate active schedules. The discrete PSO is tested using well known benchmark problems available in the literature. The solution produced by the proposed algorithms is compared with best known solution published in the literature and also compared with hybrid particle swarm algorithm and variable neighborhood search PSO algorithm. The solution construction methodology adopted in this study is found to be effective in producing good quality solutions for the various benchmark job-shop scheduling problems.

EFFICIENT MULTI-OBJECTIVE EVOLUTIONARY ALGORITHM FOR JOB SHOP SCHEDULING

Institute of Scientific and Technical Information of China (English)

Lei Deming; Wu Zhiming

2005-01-01

A new representation method is first presented based on priority rules. According to this method, each entry in the chromosome indicates that in the procedure of the Giffler and Thompson (GT) algorithm, the conflict occurring in the corresponding machine is resolved by the corresponding priority rule. Then crowding-measure multi-objective evolutionary algorithm (CMOEA) is designed,in which both archive maintenance and fitness assignment use crowding measure. Finally the comparisons between CMOEA and SPEA in solving 15 scheduling problems demonstrate that CMOEA is suitable to job shop scheduling.

Online Algorithms for Parallel Job Scheduling and Strip Packing

NARCIS (Netherlands)

Hurink, Johann L.; Paulus, J.J.

We consider the online scheduling problem of parallel jobs on parallel machines, $P|online{−}list,m_j |C_{max}$. For this problem we present a 6.6623-competitive algorithm. This improves the best known 7-competitive algorithm for this problem. The presented algorithm also applies to the problem

Review of job shop scheduling research and its new perspectives under Industry 4.0

OpenAIRE

Zhang, Jian; Ding, Guofu; Zou, Yisheng; Qin, Sheng-feng; Fu, Jianlin

2017-01-01

Traditional job shop scheduling is concentrated on centralized scheduling or semi-distributed scheduling. Under the Industry 4.0, the scheduling should deal with a smart and distributed manufacturing system supported by novel and emerging manufacturing technologies such as mass customization, Cyber-Physics Systems, Digital Twin, and SMAC (Social, Mobile, Analytics, Cloud). The scheduling research needs to shift its focus to smart distributed scheduling modeling and optimization. In order to t...

A hybrid algorithm for flexible job-shop scheduling problem with setup times

Directory of Open Access Journals (Sweden)

Ameni Azzouz

2017-01-01

Full Text Available Job-shop scheduling problem is one of the most important fields in manufacturing optimization where a set of n jobs must be processed on a set of m specified machines. Each job consists of a specific set of operations, which have to be processed according to a given order. The Flexible Job Shop problem (FJSP is a generalization of the above-mentioned problem, where each operation can be processed by a set of resources and has a processing time depending on the resource used. The FJSP problems cover two difficulties, namely, machine assignment problem and operation sequencing problem. This paper addresses the flexible job-shop scheduling problem with sequence-dependent setup times to minimize two kinds of objectives function: makespan and bi-criteria objective function. For that, we propose a hybrid algorithm based on genetic algorithm (GA and variable neighbourhood search (VNS to solve this problem. To evaluate the performance of our algorithm, we compare our results with other methods existing in literature. All the results show the superiority of our algorithm against the available ones in terms of solution quality.

Job Burnout and its Association With Work Schedules and Job Satisfaction Among Iranian Nurses in a Public Hospital: A Questionnaire Survey

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Asghari

2016-08-01

Full Text Available Background Job burnout, defined as a syndrome derived from prolonged exposure to stressors at work, is often observed in health care workers. Shift work and job satisfaction are considered two of the occupational risks for burnout in nurses. Nurses have stress and health complaints. In addition, nurses are likely to job burnout. Objectives The current study aimed to determine the prevalence of job burnout and its association with work schedules and job satisfaction among Iranian nurses in a public hospital. Methods This cross-sectional study was conducted in one of the largest Iranian public hospitals among 362 nurses (response rate: 80.44% in Tehran, Iran. The Maslach burnout inventory (MBI-22 and demographic factors questionnaire were used in the present study. The relationship between job burnout with work schedules and job satisfaction was investigated with multiple logistic regression analysis. Results The mean age and work experience of the participants were 36.14 ± 8.59 and 15.23 ±9.30 years, respectively. The result indicated a relatively high prevalence of burnout (particularly, personal accomplishment among the study population. In general, 64.4% of participants reported low personal accomplishment level. The nurses engaged in shift work reported higher levels of emotional exhaustion (odds ratio (OR = 1.02, 95% confidence interval (CI = 1.006 - 1.041, P-value = 0.008; there was no relationship between work schedules with depersonalization and personal accomplishment. The result showed significant relationship between job satisfaction and emotional exhaustion (OR = 0.945, 95% CI = 0.928 - 0.963, P-value < 0.001 and personal accomplishment (OR = 1.003, 95% CI = 1.014 - 1.058, P-value = 0.001. Conclusions The current study revealed that the Iranian nurses are exposed to a considerable risk of personal accomplishment. Also, job burnout is in association with shift working and low job satisfaction level. In this regard, working pressure

Solving multi-objective job shop scheduling problems using a non-dominated sorting genetic algorithm

Science.gov (United States)

Piroozfard, Hamed; Wong, Kuan Yew

2015-05-01

The efforts of finding optimal schedules for the job shop scheduling problems are highly important for many real-world industrial applications. In this paper, a multi-objective based job shop scheduling problem by simultaneously minimizing makespan and tardiness is taken into account. The problem is considered to be more complex due to the multiple business criteria that must be satisfied. To solve the problem more efficiently and to obtain a set of non-dominated solutions, a meta-heuristic based non-dominated sorting genetic algorithm is presented. In addition, task based representation is used for solution encoding, and tournament selection that is based on rank and crowding distance is applied for offspring selection. Swapping and insertion mutations are employed to increase diversity of population and to perform intensive search. To evaluate the modified non-dominated sorting genetic algorithm, a set of modified benchmarking job shop problems obtained from the OR-Library is used, and the results are considered based on the number of non-dominated solutions and quality of schedules obtained by the algorithm.

A neural network approach to job-shop scheduling.

Science.gov (United States)

Zhou, D N; Cherkassky, V; Baldwin, T R; Olson, D E

1991-01-01

A novel analog computational network is presented for solving NP-complete constraint satisfaction problems, i.e. job-shop scheduling. In contrast to most neural approaches to combinatorial optimization based on quadratic energy cost function, the authors propose to use linear cost functions. As a result, the network complexity (number of neurons and the number of resistive interconnections) grows only linearly with problem size, and large-scale implementations become possible. The proposed approach is related to the linear programming network described by D.W. Tank and J.J. Hopfield (1985), which also uses a linear cost function for a simple optimization problem. It is shown how to map a difficult constraint-satisfaction problem onto a simple neural net in which the number of neural processors equals the number of subjobs (operations) and the number of interconnections grows linearly with the total number of operations. Simulations show that the authors' approach produces better solutions than existing neural approaches to job-shop scheduling, i.e. the traveling salesman problem-type Hopfield approach and integer linear programming approach of J.P.S. Foo and Y. Takefuji (1988), in terms of the quality of the solution and the network complexity.

An Evaluation of Parallel Job Scheduling for ASCI Blue-Pacific

International Nuclear Information System (INIS)

Franke, H.; Jann, J.; Moreira, J.; Pattnaik, P.; Jette, M.

1999-01-01

In this paper we analyze the behavior of a gang-scheduling strategy that we are developing for the ASCI Blue-Pacific machines. Using actual job logs for one of the ASCI machines we generate a statistical model of the current workload with hyper Erlang distributions. We then vary the parameters of those distributions to generate various workloads, representative of different operating points of the machine. Through simulation we obtain performance parameters for three different scheduling strategies: (i) first-come first-serve, (ii) gang-scheduling, and (iii) backfilling. Our results show that backfilling, can be very effective for the common operating points in the 60-70% utilization range. However, for higher utilization rates, time-sharing techniques such as gang-scheduling offer much better performance

A Distributed Particle Swarm Optimization Zlgorithmfor Flexible Job-hop Scheduling Problem

Directory of Open Access Journals (Sweden)

LIU Sheng--hui

2017-06-01

Full Text Available According to the characteristics of the Flexible job shop scheduling problem the minimum makespan as measures we proposed a distributed particle swarm optimization algorithm aiming to solve flexible job shop scheduling problem. The algorithm adopts the method of distributed ideas to solve problems and we are established for two multi agent particle swarm optimization model in this algorithm it can solve the traditional particle swarm optimization algorithm when making decisions in real time according to the emergencies. Finally some benthmark problems were experimented and the results are compared with the traditional algorithm. Experimental results proved that the developed distributed PSO is enough effective and efficient to solve the FJSP and it also verified the reasonableness of the multi}gent particle swarm optimization model.

Multiobjective Variable Neighborhood Search algorithm for scheduling independent jobs on computational grid

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S. Selvi

2015-07-01

Full Text Available Grid computing solves high performance and high-throughput computing problems through sharing resources ranging from personal computers to super computers distributed around the world. As the grid environments facilitate distributed computation, the scheduling of grid jobs has become an important issue. In this paper, an investigation on implementing Multiobjective Variable Neighborhood Search (MVNS algorithm for scheduling independent jobs on computational grid is carried out. The performance of the proposed algorithm has been evaluated with Min–Min algorithm, Simulated Annealing (SA and Greedy Randomized Adaptive Search Procedure (GRASP algorithm. Simulation results show that MVNS algorithm generally performs better than other metaheuristics methods.

No-Wait Job Shop Scheduling, a Constraint Propagation Approach

NARCIS (Netherlands)

Lennartz, P.M.

2006-01-01

Multi-machine scheduling problems have earned themselves a reputation of intractability. In this thesis we try to solve a special kind of these problems, the so-called no-wait job shop problems. In an instance of this problem-class we are given a number of operations that are to be executed on a

Single machine total completion time minimization scheduling with a time-dependent learning effect and deteriorating jobs

Science.gov (United States)

Wang, Ji-Bo; Wang, Ming-Zheng; Ji, Ping

2012-05-01

In this article, we consider a single machine scheduling problem with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the job processing time is defined by a function of its starting time and total normal processing time of jobs in front of it in the sequence. The objective is to determine an optimal schedule so as to minimize the total completion time. This problem remains open for the case of -1 < a < 0, where a denotes the learning index; we show that an optimal schedule of the problem is V-shaped with respect to job normal processing times. Three heuristic algorithms utilising the V-shaped property are proposed, and computational experiments show that the last heuristic algorithm performs effectively and efficiently in obtaining near-optimal solutions.

A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems

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Yingni Zhai

2014-10-01

Full Text Available Purpose: A decomposition heuristics based on multi-bottleneck machines for large-scale job shop scheduling problems (JSP is proposed.Design/methodology/approach: In the algorithm, a number of sub-problems are constructed by iteratively decomposing the large-scale JSP according to the process route of each job. And then the solution of the large-scale JSP can be obtained by iteratively solving the sub-problems. In order to improve the sub-problems' solving efficiency and the solution quality, a detection method for multi-bottleneck machines based on critical path is proposed. Therewith the unscheduled operations can be decomposed into bottleneck operations and non-bottleneck operations. According to the principle of “Bottleneck leads the performance of the whole manufacturing system” in TOC (Theory Of Constraints, the bottleneck operations are scheduled by genetic algorithm for high solution quality, and the non-bottleneck operations are scheduled by dispatching rules for the improvement of the solving efficiency.Findings: In the process of the sub-problems' construction, partial operations in the previous scheduled sub-problem are divided into the successive sub-problem for re-optimization. This strategy can improve the solution quality of the algorithm. In the process of solving the sub-problems, the strategy that evaluating the chromosome's fitness by predicting the global scheduling objective value can improve the solution quality.Research limitations/implications: In this research, there are some assumptions which reduce the complexity of the large-scale scheduling problem. They are as follows: The processing route of each job is predetermined, and the processing time of each operation is fixed. There is no machine breakdown, and no preemption of the operations is allowed. The assumptions should be considered if the algorithm is used in the actual job shop.Originality/value: The research provides an efficient scheduling method for the

Fog computing job scheduling optimization based on bees swarm

Science.gov (United States)

Bitam, Salim; Zeadally, Sherali; Mellouk, Abdelhamid

2018-04-01

Fog computing is a new computing architecture, composed of a set of near-user edge devices called fog nodes, which collaborate together in order to perform computational services such as running applications, storing an important amount of data, and transmitting messages. Fog computing extends cloud computing by deploying digital resources at the premise of mobile users. In this new paradigm, management and operating functions, such as job scheduling aim at providing high-performance, cost-effective services requested by mobile users and executed by fog nodes. We propose a new bio-inspired optimization approach called Bees Life Algorithm (BLA) aimed at addressing the job scheduling problem in the fog computing environment. Our proposed approach is based on the optimized distribution of a set of tasks among all the fog computing nodes. The objective is to find an optimal tradeoff between CPU execution time and allocated memory required by fog computing services established by mobile users. Our empirical performance evaluation results demonstrate that the proposal outperforms the traditional particle swarm optimization and genetic algorithm in terms of CPU execution time and allocated memory.

An improved sheep flock heredity algorithm for job shop scheduling and flow shop scheduling problems

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Chandramouli Anandaraman

2011-10-01

Full Text Available Job Shop Scheduling Problem (JSSP and Flow Shop Scheduling Problem (FSSP are strong NP-complete combinatorial optimization problems among class of typical production scheduling problems. An improved Sheep Flock Heredity Algorithm (ISFHA is proposed in this paper to find a schedule of operations that can minimize makespan. In ISFHA, the pairwise mutation operation is replaced by a single point mutation process with a probabilistic property which guarantees the feasibility of the solutions in the local search domain. A Robust-Replace (R-R heuristic is introduced in place of chromosomal crossover to enhance the global search and to improve the convergence. The R-R heuristic is found to enhance the exploring potential of the algorithm and enrich the diversity of neighborhoods. Experimental results reveal the effectiveness of the proposed algorithm, whose optimization performance is markedly superior to that of genetic algorithms and is comparable to the best results reported in the literature.

Flexible job-shop scheduling based on genetic algorithm and simulation validation

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Zhou Erming

2017-01-01

Full Text Available This paper selects flexible job-shop scheduling problem as the research object, and Constructs mathematical model aimed at minimizing the maximum makespan. Taking the transmission reverse gear production line of a transmission corporation as an example, genetic algorithm is applied for flexible jobshop scheduling problem to get the specific optimal scheduling results with MATLAB. DELMIA/QUEST based on 3D discrete event simulation is applied to construct the physical model of the production workshop. On the basis of the optimal scheduling results, the logical link of the physical model for the production workshop is established, besides, importing the appropriate process parameters to make virtual simulation on the production workshop. Finally, through analyzing the simulated results, it shows that the scheduling results are effective and reasonable.

JOB SHOP SCHEDULING BIOBJETIVO MEDIANTE ENFRIAMIENTO SIMULADO Y ENFOQUE DE PARETO JOB-SHOP SCHEDULING: BIO-OBJECTIVE THROUGH SIMULATED COOLING AND PARETO PRINCIPLE

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Juan Carlos Osorio

2012-12-01

Full Text Available El problema del scheduling es uno de los problemas más ampliamente tratados en la literatura; sin embargo, es un problema complejo NP hard. Cuando, además, se involucra más de un objetivo, este problema se convierte en uno de los más complejos en el campo de la investigación de operaciones. Se presenta entonces un modelo biobjetivo para el job shop scheduling que incluye el makespan y el tiempo de flujo medio. Para resolver el modelo se ha utilizado una propuesta que incluye el uso del meta-heurístico Recocido Simulado (SA y el enfoque de Pareto. Este modelo es evaluado en tres problemas presentados en la literatura de tamaños 6x6, 10x5 y 10x10. Los resultados del modelo se comparan con otros meta-heurísticos y se encuentra que este modelo presenta buenos resultados en los tres problemas evaluados.The scheduling problem is one of the most widely treated problems in literature; however, it is an NP hard complex problem. Also, when more than one objective is involved, this problem becomes one of the most complex ones in the field of operations research. A bio-objective model is then emerged for the Job-Shop Scheduling, including makespan and mean flow time. For solving the model a proposal which includes the use of Simulated Annealing (SA metaheuristic and Pareto Principle. This model is evaluated in three problems described in literature with the following sizes: 6x6, 10x5 and 10x10. Results of the model are compared to other metaheuristics and it has been found that this model shows good results in the three problems evaluated.

Proposta de classificação hierarquizada dos modelos de solução para o problema de job shop scheduling A proposition of hierarchical classification for solution models in the job shop scheduling problem

Directory of Open Access Journals (Sweden)

Ricardo Ferrari Pacheco

1999-04-01

Full Text Available Este artigo propõe uma classificação hierarquizada dos modelos utilizados na solução do problema de programação da produção intermitente do tipo job shop, incluindo tanto os que fornecem solução ótima, quanto os modelos heurísticos mais recentes baseados em métodos de busca estendida. Por meio dessa classificação obteve-se um painel amplo dos modelos existentes, evidenciando as diferentes abordagens do problema e suas soluções, com o objetivo de proporcionar uma orientação preliminar na escolha do modelo de job shop scheduling mais adequado.This paper proposes a hierarchical model classification used in the job shop scheduling problem, including those that provide an optimal solution and the more recent ones based on heuristics, called extended search methods. A panel with the existing models is obtained by this classification, and solutions and approach differences are highlighted with the aim of a preliminary orientation on the choice of a more adequate job shop scheduling model.

Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

Science.gov (United States)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

Parallel Branch-and-Bound Methods for the Job Shop Scheduling

DEFF Research Database (Denmark)

Clausen, Jens; Perregaard, Michael

1998-01-01

Job-shop scheduling (JSS) problems are among the more difficult to solve in the class of NP-complete problems. The only successful approach has been branch-and-bound based algorithms, but such algorithms depend heavily on good bound functions. Much work has been done to identify such functions...... for the JSS problem, but with limited success. Even with recent methods, it is still not possible to solve problems substantially larger than 10 machines and 10 jobs. In the current study, we focus on parallel methods for solving JSS problems. We implement two different parallel branch-and-bound algorithms...

Limited access: gender, occupational composition, and flexible work scheduling.

Science.gov (United States)

Glauber, Rebecca

2011-01-01

The current study draws on national data to explore differences in access to flexible work scheduling by the gender composition of women's and men's occupations. Results show that those who work in integrated occupations are more likely to have access to flexible scheduling. Women and men do not take jobs with lower pay in return for greater access to flexibility. Instead, jobs with higher pay offer greater flexibility. Integrated occupations tend to offer the greatest access to flexible scheduling because of their structural locations. Part-time work is negatively associated with men's access to flexible scheduling but positively associated with women's access. Women have greater flexibility when they work for large establishments, whereas men have greater flexibility when they work for small establishments.

Energy-efficient approach to minimizing the energy consumption in an extended job-shop scheduling problem

Science.gov (United States)

Tang, Dunbing; Dai, Min

2015-09-01

The traditional production planning and scheduling problems consider performance indicators like time, cost and quality as optimization objectives in manufacturing processes. However, environmentally-friendly factors like energy consumption of production have not been completely taken into consideration. Against this background, this paper addresses an approach to modify a given schedule generated by a production planning and scheduling system in a job shop floor, where machine tools can work at different cutting speeds. It can adjust the cutting speeds of the operations while keeping the original assignment and processing sequence of operations of each job fixed in order to obtain energy savings. First, the proposed approach, based on a mixed integer programming mathematical model, changes the total idle time of the given schedule to minimize energy consumption in the job shop floor while accepting the optimal solution of the scheduling objective, makespan. Then, a genetic-simulated annealing algorithm is used to explore the optimal solution due to the fact that the problem is strongly NP-hard. Finally, the effectiveness of the approach is performed smalland large-size instances, respectively. The experimental results show that the approach can save 5%-10% of the average energy consumption while accepting the optimal solution of the makespan in small-size instances. In addition, the average maximum energy saving ratio can reach to 13%. And it can save approximately 1%-4% of the average energy consumption and approximately 2.4% of the average maximum energy while accepting the near-optimal solution of the makespan in large-size instances. The proposed research provides an interesting point to explore an energy-aware schedule optimization for a traditional production planning and scheduling problem.

Hybrid Genetic Algorithm with Multiparents Crossover for Job Shop Scheduling Problems

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Noor Hasnah Moin

2015-01-01

Full Text Available The job shop scheduling problem (JSSP is one of the well-known hard combinatorial scheduling problems. This paper proposes a hybrid genetic algorithm with multiparents crossover for JSSP. The multiparents crossover operator known as extended precedence preservative crossover (EPPX is able to recombine more than two parents to generate a single new offspring distinguished from common crossover operators that recombine only two parents. This algorithm also embeds a schedule generation procedure to generate full-active schedule that satisfies precedence constraints in order to reduce the search space. Once a schedule is obtained, a neighborhood search is applied to exploit the search space for better solutions and to enhance the GA. This hybrid genetic algorithm is simulated on a set of benchmarks from the literatures and the results are compared with other approaches to ensure the sustainability of this algorithm in solving JSSP. The results suggest that the implementation of multiparents crossover produces competitive results.

Spent nuclear fuel project integrated schedule plan

International Nuclear Information System (INIS)

Squires, K.G.

1995-01-01

The Spent Nuclear Fuel Integrated Schedule Plan establishes the organizational responsibilities, rules for developing, maintain and status of the SNF integrated schedule, and an implementation plan for the integrated schedule. The mission of the SNFP on the Hanford site is to provide safe, economic, environmentally sound management of Hanford SNF in a manner which stages it to final disposition. This particularly involves K Basin fuel

Spent nuclear fuel project integrated schedule plan

Energy Technology Data Exchange (ETDEWEB)

Squires, K.G.

1995-03-06

The Spent Nuclear Fuel Integrated Schedule Plan establishes the organizational responsibilities, rules for developing, maintain and status of the SNF integrated schedule, and an implementation plan for the integrated schedule. The mission of the SNFP on the Hanford site is to provide safe, economic, environmentally sound management of Hanford SNF in a manner which stages it to final disposition. This particularly involves K Basin fuel.

A Simulated Annealing-Based Heuristic Algorithm for Job Shop Scheduling to Minimize Lateness

Directory of Open Access Journals (Sweden)

Rui Zhang

2013-04-01

Full Text Available A decomposition-based optimization algorithm is proposed for solving large job shop scheduling problems with the objective of minimizing the maximum lateness. First, we use the constraint propagation theory to derive the orientation of a portion of disjunctive arcs. Then we use a simulated annealing algorithm to find a decomposition policy which satisfies the maximum number of oriented disjunctive arcs. Subsequently, each subproblem (corresponding to a subset of operations as determined by the decomposition policy is successively solved with a simulated annealing algorithm, which leads to a feasible solution to the original job shop scheduling problem. Computational experiments are carried out for adapted benchmark problems, and the results show the proposed algorithm is effective and efficient in terms of solution quality and time performance.

ADAPTATION OF JOHNSON SEQUENCING ALGORITHM FOR JOB SCHEDULING TO MINIMISE THE AVERAGE WAITING TIME IN CLOUD COMPUTING ENVIRONMENT

Directory of Open Access Journals (Sweden)

SOUVIK PAL

2016-09-01

Full Text Available Cloud computing is an emerging paradigm of Internet-centric business computing where Cloud Service Providers (CSPs are providing services to the customer according to their needs. The key perception behind cloud computing is on-demand sharing of resources available in the resource pool provided by CSP, which implies new emerging business model. The resources are provisioned when jobs arrive. The job scheduling and minimization of waiting time are the challenging issue in cloud computing. When a large number of jobs are requested, they have to wait for getting allocated to the servers which in turn may increase the queue length and also waiting time. This paper includes system design for implementation which is concerned with Johnson Scheduling Algorithm that provides the optimal sequence. With that sequence, service times can be obtained. The waiting time and queue length can be reduced using queuing model with multi-server and finite capacity which improves the job scheduling model.

Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Muhammad Kamal Amjad

2018-01-01

Full Text Available Flexible Job Shop Scheduling Problem (FJSSP is an extension of the classical Job Shop Scheduling Problem (JSSP. The FJSSP is known to be NP-hard problem with regard to optimization and it is very difficult to find reasonably accurate solutions of the problem instances in a rational time. Extensive research has been carried out in this area especially over the span of the last 20 years in which the hybrid approaches involving Genetic Algorithm (GA have gained the most popularity. Keeping in view this aspect, this article presents a comprehensive literature review of the FJSSPs solved using the GA. The survey is further extended by the inclusion of the hybrid GA (hGA techniques used in the solution of the problem. This review will give readers an insight into use of certain parameters in their future research along with future research directions.

Iterated greedy algorithms to minimize the total family flow time for job-shop scheduling with job families and sequence-dependent set-ups

Science.gov (United States)

Kim, Ji-Su; Park, Jung-Hyeon; Lee, Dong-Ho

2017-10-01

This study addresses a variant of job-shop scheduling in which jobs are grouped into job families, but they are processed individually. The problem can be found in various industrial systems, especially in reprocessing shops of remanufacturing systems. If the reprocessing shop is a job-shop type and has the component-matching requirements, it can be regarded as a job shop with job families since the components of a product constitute a job family. In particular, sequence-dependent set-ups in which set-up time depends on the job just completed and the next job to be processed are also considered. The objective is to minimize the total family flow time, i.e. the maximum among the completion times of the jobs within a job family. A mixed-integer programming model is developed and two iterated greedy algorithms with different local search methods are proposed. Computational experiments were conducted on modified benchmark instances and the results are reported.

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, H.; Skutella, M.; Woeginger, Gerhard

2003-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Preemptive scheduling with rejection

NARCIS (Netherlands)

Hoogeveen, J.A.; Skutella, M.; Woeginger, G.J.; Paterson, M.

2000-01-01

We consider the problem of preemptively scheduling a set of n jobs on m (identical, uniformly related, or unrelated) parallel machines. The scheduler may reject a subset of the jobs and thereby incur job-dependent penalties for each rejected job, and he must construct a schedule for the remaining

Comparison of job stress and obesity in nurses with favorable and unfavorable work schedules.

Science.gov (United States)

Han, Kihye; Trinkoff, Alison M; Storr, Carla L; Geiger-Brown, Jeanne; Johnson, Karen L; Park, Sungae

2012-08-01

To compare obesity-related factors between female nurses with favorable work schedules (WSs) and unfavorable WSs. In a cross-sectional study, 1724 female nurses were stratified by WS (favorable vs unfavorable). For each schedule type, the odds of obesity were related to health behaviors, home demands, and job stress using logistic regression models. Among nurses with unfavorable WSs, healthy behaviors (exercise, sleep) were inversely associated with obesity, whereas for those with favorable WSs, obese nurses reported significantly more unhealthy behaviors (smoking, alcohol use; odds ratio [OR], 1.19; 95% confidence interval [CI], 1.02-1.38), more physical lifting of children/dependents (OR, 1.43; 95% CI, 1.06-1.93), having more nurse input into their jobs (OR, 1.21; 95% CI, 1.02-1.44), yet less boss support at work (OR, 0.83; 95% CI, 0.68-0.99). Considering impacts of WSs on obesity and potential obesity-related health outcomes, healthful scheduling should be provided to nurses.

Study on multi-objective flexible job-shop scheduling problem considering energy consumption

Directory of Open Access Journals (Sweden)

Zengqiang Jiang

2014-06-01

Full Text Available Purpose: Build a multi-objective Flexible Job-shop Scheduling Problem(FJSP optimization model, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered, then Design a Modified Non-dominated Sorting Genetic Algorithm (NSGA-II based on blood variation for above scheduling model.Design/methodology/approach: A multi-objective optimization theory based on Pareto optimal method is used in carrying out the optimization model. NSGA-II is used to solve the model.Findings: By analyzing the research status and insufficiency of multi-objective FJSP, Find that the difference in scheduling will also have an effect on energy consumption in machining process and environmental emissions. Therefore, job-shop scheduling requires not only guaranteeing the processing quality, time and cost, but also optimizing operation plan of machines and minimizing energy consumption.Originality/value: A multi-objective FJSP optimization model is put forward, in which the makespan, processing cost, energy consumption and cost-weighted processing quality are considered. According to above model, Blood-Variation-based NSGA-II (BVNSGA-II is designed. In which, the chromosome mutation rate is determined after calculating the blood relationship between two cross chromosomes, crossover and mutation strategy of NSGA-II is optimized and the prematurity of population is overcome. Finally, the performance of the proposed model and algorithm is evaluated through a case study, and the results proved the efficiency and feasibility of the proposed model and algorithm.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads...

Sequencing, lot sizing and scheduling in job shops: the common cycle approach

NARCIS (Netherlands)

Ouenniche, J.; Boctor, F.F.

1998-01-01

This paper deals with the multi-product, finite horizon, static demand, sequencing, lot sizing and scheduling problem in a job shop environment where the objective is to minimize the sum of setup and inventory holding costs while satisfying the demand with no backlogging. To solve this problem, we

A PMBGA to Optimize the Selection of Rules for Job Shop Scheduling Based on the Giffler-Thompson Algorithm

Directory of Open Access Journals (Sweden)

Rui Zhang

2012-01-01

Full Text Available Most existing research on the job shop scheduling problem has been focused on the minimization of makespan (i.e., the completion time of the last job. However, in the fiercely competitive market nowadays, delivery punctuality is more important for maintaining a high service reputation. So in this paper, we aim at solving job shop scheduling problems with the total weighted tardiness objective. Several dispatching rules are adopted in the Giffler-Thompson algorithm for constructing active schedules. It is noticeable that the rule selections for scheduling consecutive operations are not mutually independent but actually interrelated. Under such circumstances, a probabilistic model-building genetic algorithm (PMBGA is proposed to optimize the sequence of selected rules. First, we use Bayesian networks to model the distribution characteristics of high-quality solutions in the population. Then, the new generation of individuals is produced by sampling the established Bayesian network. Finally, some elitist individuals are further improved by a special local search module based on parameter perturbation. The superiority of the proposed approach is verified by extensive computational experiments and comparisons.

Scheduling Maintenance Jobs in Networks

OpenAIRE

Abed, Fidaa; Chen, Lin; Disser, Yann; Groß, Martin; Megow, Nicole; Meißner, Julie; Richter, Alexander T.; Rischke, Roman

2017-01-01

We investigate the problem of scheduling the maintenance of edges in a network, motivated by the goal of minimizing outages in transportation or telecommunication networks. We focus on maintaining connectivity between two nodes over time; for the special case of path networks, this is related to the problem of minimizing the busy time of machines. We show that the problem can be solved in polynomial time in arbitrary networks if preemption is allowed. If preemption is restricted to integral t...

A controlled genetic algorithm by fuzzy logic and belief functions for job-shop scheduling.

Science.gov (United States)

Hajri, S; Liouane, N; Hammadi, S; Borne, P

2000-01-01

Most scheduling problems are highly complex combinatorial problems. However, stochastic methods such as genetic algorithm yield good solutions. In this paper, we present a controlled genetic algorithm (CGA) based on fuzzy logic and belief functions to solve job-shop scheduling problems. For better performance, we propose an efficient representational scheme, heuristic rules for creating the initial population, and a new methodology for mixing and computing genetic operator probabilities.

A Comparison of the DISASTER (Trademark) Scheduling Software with a Simultaneous Scheduling Algorithm for Minimizing Maximum Tardiness in Job Shops

Science.gov (United States)

1993-09-01

goal ( Heizer , Render , and Stair, 1993:94). Integer Prgronmming. Integer programming is a general purpose approach used to optimally solve job shop...Scheduling," Operations Research Journal. 29, No 4: 646-667 (July-August 1981). Heizer , Jay, Barry Render and Ralph M. Stair, Jr. Production and Operations

Peer-to-peer Cooperative Scheduling Architecture for National Grid Infrastructure

Science.gov (United States)

Matyska, Ludek; Ruda, Miroslav; Toth, Simon

For some ten years, the Czech National Grid Infrastructure MetaCentrum uses a single central PBSPro installation to schedule jobs across the country. This centralized approach keeps a full track about all the clusters, providing support for jobs spanning several sites, implementation for the fair-share policy and better overall control of the grid environment. Despite a steady progress in the increased stability and resilience to intermittent very short network failures, growing number of sites and processors makes this architecture, with a single point of failure and scalability limits, obsolete. As a result, a new scheduling architecture is proposed, which relies on higher autonomy of clusters. It is based on a peer to peer network of semi-independent schedulers for each site or even cluster. Each scheduler accepts jobs for the whole infrastructure, cooperating with other schedulers on implementation of global policies like central job accounting, fair-share, or submission of jobs across several sites. The scheduling system is integrated with the Magrathea system to support scheduling of virtual clusters, including the setup of their internal network, again eventually spanning several sites. On the other hand, each scheduler is local to one of several clusters and is able to directly control and submit jobs to them even if the connection of other scheduling peers is lost. In parallel to the change of the overall architecture, the scheduling system itself is being replaced. Instead of PBSPro, chosen originally for its declared support of large scale distributed environment, the new scheduling architecture is based on the open-source Torque system. The implementation and support for the most desired properties in PBSPro and Torque are discussed and the necessary modifications to Torque to support the MetaCentrum scheduling architecture are presented, too.

Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling.

Science.gov (United States)

Yang, S; Wang, D

2000-01-01

This paper presents a constraint satisfaction adaptive neural network, together with several heuristics, to solve the generalized job-shop scheduling problem, one of NP-complete constraint satisfaction problems. The proposed neural network can be easily constructed and can adaptively adjust its weights of connections and biases of units based on the sequence and resource constraints of the job-shop scheduling problem during its processing. Several heuristics that can be combined with the neural network are also presented. In the combined approaches, the neural network is used to obtain feasible solutions, the heuristic algorithms are used to improve the performance of the neural network and the quality of the obtained solutions. Simulations have shown that the proposed neural network and its combined approaches are efficient with respect to the quality of solutions and the solving speed.

A Hybrid Differential Evolution and Tree Search Algorithm for the Job Shop Scheduling Problem

Directory of Open Access Journals (Sweden)

Rui Zhang

2011-01-01

Full Text Available The job shop scheduling problem (JSSP is a notoriously difficult problem in combinatorial optimization. In terms of the objective function, most existing research has been focused on the makespan criterion. However, in contemporary manufacturing systems, due-date-related performances are more important because they are essential for maintaining a high service reputation. Therefore, in this study we aim at minimizing the total weighted tardiness in JSSP. Considering the high complexity, a hybrid differential evolution (DE algorithm is proposed for the problem. To enhance the overall search efficiency, a neighborhood property of the problem is discovered, and then a tree search procedure is designed and embedded into the DE framework. According to the extensive computational experiments, the proposed approach is efficient in solving the job shop scheduling problem with total weighted tardiness objective.

Flexible Job Shop Scheduling Problem Using an Improved Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available As an extension of the classical job shop scheduling problem, the flexible job shop scheduling problem (FJSP plays an important role in real production systems. In FJSP, an operation is allowed to be processed on more than one alternative machine. It has been proven to be a strongly NP-hard problem. Ant colony optimization (ACO has been proven to be an efficient approach for dealing with FJSP. However, the basic ACO has two main disadvantages including low computational efficiency and local optimum. In order to overcome these two disadvantages, an improved ant colony optimization (IACO is proposed to optimize the makespan for FJSP. The following aspects are done on our improved ant colony optimization algorithm: select machine rule problems, initialize uniform distributed mechanism for ants, change pheromone’s guiding mechanism, select node method, and update pheromone’s mechanism. An actual production instance and two sets of well-known benchmark instances are tested and comparisons with some other approaches verify the effectiveness of the proposed IACO. The results reveal that our proposed IACO can provide better solution in a reasonable computational time.

Emergency Radiology Practice Patterns: Shifts, Schedules, and Job Satisfaction.

Science.gov (United States)

Hanna, Tarek N; Shekhani, Haris; Lamoureux, Christine; Mar, Hanna; Nicola, Refky; Sliker, Clint; Johnson, Jamlik-Omari

2017-03-01

To assess the practice environment of emergency radiologists with a focus on schedule, job satisfaction, and self-perception of health, wellness, and diagnostic accuracy. A survey drawing from prior radiology and health care shift-work literature was distributed via e-mail to national societies, teleradiology groups, and private practices. The survey remained open for 4 weeks in 2016, with one reminder. Data were analyzed using hypothesis testing and logistic regression modeling. Response rate was 29.6% (327/1106); 69.1% of respondents (n = 226) were greater than 40 years old, 73% (n = 240) were male, and 87% (n = 284) practiced full time. With regard to annual overnight shifts (NS): 36% (n = 118) did none, 24.9% (n = 81) did 182 or more, and 15.6% (n = 51) did 119. There was a significant association between average NS worked per year and both perceived negative health effects (P impact on memory (P job enjoyment and number of annual NS (P job" for radiologists who work no NS is 2.21 times greater than for radiologists who work at least 119 NS, when shift length is held constant. Radiologists with 11+ years of experience who work no NS or 1 to 100 NS annually have lower odds of feeling overwhelmed when compared with those working the same number of NS with job satisfaction and negative health self-perception. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available In real-world manufacturing systems, production scheduling systems are often implemented under random or dynamic events like machine failure, unexpected processing times, stochastic arrival of the urgent orders, cancellation of the orders, and so on. These dynamic events will lead the initial scheduling scheme to be nonoptimal and/or infeasible. Hence, appropriate dynamic rescheduling approaches are needed to overcome the dynamic events. In this paper, we propose a dynamic rescheduling method based on variable interval rescheduling strategy (VIRS to deal with the dynamic flexible job shop scheduling problem considering machine failure, urgent job arrival, and job damage as disruptions. On the other hand, an improved genetic algorithm (GA is proposed for minimizing makespan. In our improved GA, a mix of random initialization population by combining initialization machine and initialization operation with random initialization is designed for generating high-quality initial population. In addition, the elitist strategy (ES and improved population diversity strategy (IPDS are used to avoid falling into the local optimal solution. Experimental results for static and several dynamic events in the FJSP show that our method is feasible and effective.

Extended precedence preservative crossover for job shop scheduling problems

Science.gov (United States)

Ong, Chung Sin; Moin, Noor Hasnah; Omar, Mohd

2013-04-01

Job shop scheduling problems (JSSP) is one of difficult combinatorial scheduling problems. A wide range of genetic algorithms based on the two parents crossover have been applied to solve the problem but multi parents (more than two parents) crossover in solving the JSSP is still lacking. This paper proposes the extended precedence preservative crossover (EPPX) which uses multi parents for recombination in the genetic algorithms. EPPX is a variation of the precedence preservative crossover (PPX) which is one of the crossovers that perform well to find the solutions for the JSSP. EPPX is based on a vector to determine the gene selected in recombination for the next generation. Legalization of children (offspring) can be eliminated due to the JSSP representation encoded by using permutation with repetition that guarantees the feasibility of chromosomes. The simulations are performed on a set of benchmarks from the literatures and the results are compared to ensure the sustainability of multi parents recombination in solving the JSSP.

Integrated multi-resource planning and scheduling in engineering project

Directory of Open Access Journals (Sweden)

Samer Ben Issa

2017-01-01

Full Text Available Planning and scheduling processes in project management are carried out sequentially in prac-tice, i.e. planning project activities first without visibility of resource limitation, and then schedul-ing the project according to these pre-planned activities. This is a need to integrate these two pro-cesses. In this paper, we use Branch and Bound approach for generating all the feasible and non-feasible project schedules with/without activity splitting, and with a new criterion called “the Minimum Moments of Resources Required around X-Y axes (MMORR”, we select the best feasible project schedule to integrate plan processing and schedule processing for engineering projects. The results illustrate that this integrated approach can effectively select the best feasible project schedule among alternatives, improves the resource utilization, and shortens the project lead time.

Solving a large-scale precedence constrained scheduling problem with elastic jobs using tabu search

DEFF Research Database (Denmark)

Pedersen, C.R.; Rasmussen, R.V.; Andersen, Kim Allan

2007-01-01

exploitation of the elastic jobs and solve the problem using a tabu search procedure. Finding an initial feasible solution is in general -complete, but the tabu search procedure includes a specialized heuristic for solving this problem. The solution method has proven to be very efficient and leads......This paper presents a solution method for minimizing makespan of a practical large-scale scheduling problem with elastic jobs. The jobs are processed on three servers and restricted by precedence constraints, time windows and capacity limitations. We derive a new method for approximating the server...... to a significant decrease in makespan compared to the strategy currently implemented....

Evaluation and Selection of Best Priority Sequencing Rule in Job Shop Scheduling using Hybrid MCDM Technique

Science.gov (United States)

Kiran Kumar, Kalla; Nagaraju, Dega; Gayathri, S.; Narayanan, S.

2017-05-01

Priority Sequencing Rules provide the guidance for the order in which the jobs are to be processed at a workstation. The application of different priority rules in job shop scheduling gives different order of scheduling. More experimentation needs to be conducted before a final choice is made to know the best priority sequencing rule. Hence, a comprehensive method of selecting the right choice is essential in managerial decision making perspective. This paper considers seven different priority sequencing rules in job shop scheduling. For evaluation and selection of the best priority sequencing rule, a set of eight criteria are considered. The aim of this work is to demonstrate the methodology of evaluating and selecting the best priority sequencing rule by using hybrid multi criteria decision making technique (MCDM), i.e., analytical hierarchy process (AHP) with technique for order preference by similarity to ideal solution (TOPSIS). The criteria weights are calculated by using AHP whereas the relative closeness values of all priority sequencing rules are computed based on TOPSIS with the help of data acquired from the shop floor of a manufacturing firm. Finally, from the findings of this work, the priority sequencing rules are ranked from most important to least important. The comprehensive methodology presented in this paper is very much essential for the management of a workstation to choose the best priority sequencing rule among the available alternatives for processing the jobs with maximum benefit.

A Mathematical Model for Scheduling a Batch Processing Machine with Multiple Incompatible Job Families, Non-identical Job dimensions, Non-identical Job sizes, Non-agreeable release times and due dates

International Nuclear Information System (INIS)

Ramasubramaniam, M; Mathirajan, M

2013-01-01

The paper addresses the problem scheduling a batch processing machine with multiple incompatible job families, non-identical job dimensions, non-identical job sizes and non-agreeable release dates to minimize makespan. The research problem is solved by proposing a mixed integer programming model that appropriately takes into account the parameters considered in the problem. The proposed is validated using a numerical example. The experiment conducted show that the model can pose significant difficulties in solving the large scale instances. The paper concludes by giving the scope for future work and some alternative approaches one can use for solving these class of problems.

The Effects of Machine Load Sitnations on Performance of Job Shop and Group Scheduling

OpenAIRE

Torkul, O.

2018-01-01

Perfonnance of job shop and group scheduling ndermulti­natch work input environment was exarnined against two nachine load (light and high load) situations. n order to conduct the analysis, a deterministic computer ;im ulation program was written and used. A job shop {JS) model is applied to the shop floor area and :ompared with a simulation of a similar proposal except hat group technology (GT) model was used in the shop loor area instead. )etailed analysis of the results from applying diffe...

The Effects of Machine Load Sitnations on Performance of Job Shop and Group Scheduling

OpenAIRE

O.TORKUL TORKUL

1998-01-01

Perfonnance of job shop and group scheduling ndermulti­natch work input environment was exarnined against two nachine load (light and high load) situations. n order to conduct the analysis, a deterministic computer ;im ulation program was written and used. A job shop {JS) model is applied to the shop floor area and :ompared with a simulation of a similar proposal except hat group technology (GT) model was used in the shop loor area instead. )etailed analysis of the results from applying diffe...

Planning construction of integrative schedule management for nuclear power project

International Nuclear Information System (INIS)

Zeng Zhenglin; Wang Wenying; Peng Fei

2012-01-01

This paper introduces the planning construction of integrative schedule management for Nuclear Power Project. It details schedule management system and the requirement of schedulers and the mode of three schedule management flats. And analysis it combing with the implementation of construction water and all special schedules before FCD to further propose the improving and researching direction for the integrative schedule management. (authors)

Preemptive scheduling of independent jobs on identical parallel machines subject to migration delays

NARCIS (Netherlands)

Fishkin, A.V.; Jansen, K.; Sevastyanov, S.V.; Sitters, R.A.; Leonardi, S.

2005-01-01

We present hardness and approximation results for the problem of scheduling n independent jobs on m identical parallel machines subject to a migration delay d so as to minimize the makespan. We give a sharp threshold on the value of d for which the complexity of the problem changes from polynomial

Preemptive scheduling of independent jobs on identical parallel machines subject to migration delays

NARCIS (Netherlands)

Sevastyanov, S. V.; Sitters, R. A.; Fishkin, A.V.

2010-01-01

We present hardness and approximation results for the problem of preemptive scheduling of n independent jobs on m identical parallel machines subject to a migration delay d with the objective to minimize the makespan. We give a sharp threshold on the value of d for which the complexity of the

A modified genetic algorithm with fuzzy roulette wheel selection for job-shop scheduling problems

Science.gov (United States)

Thammano, Arit; Teekeng, Wannaporn

2015-05-01

The job-shop scheduling problem is one of the most difficult production planning problems. Since it is in the NP-hard class, a recent trend in solving the job-shop scheduling problem is shifting towards the use of heuristic and metaheuristic algorithms. This paper proposes a novel metaheuristic algorithm, which is a modification of the genetic algorithm. This proposed algorithm introduces two new concepts to the standard genetic algorithm: (1) fuzzy roulette wheel selection and (2) the mutation operation with tabu list. The proposed algorithm has been evaluated and compared with several state-of-the-art algorithms in the literature. The experimental results on 53 JSSPs show that the proposed algorithm is very effective in solving the combinatorial optimization problems. It outperforms all state-of-the-art algorithms on all benchmark problems in terms of the ability to achieve the optimal solution and the computational time.

Comparative study of heuristics algorithms in solving flexible job shop scheduling problem with condition based maintenance

Directory of Open Access Journals (Sweden)

Yahong Zheng

2014-05-01

Full Text Available Purpose: This paper focuses on a classic optimization problem in operations research, the flexible job shop scheduling problem (FJSP, to discuss the method to deal with uncertainty in a manufacturing system.Design/methodology/approach: In this paper, condition based maintenance (CBM, a kind of preventive maintenance, is suggested to reduce unavailability of machines. Different to the simultaneous scheduling algorithm (SSA used in the previous article (Neale & Cameron,1979, an inserting algorithm (IA is applied, in which firstly a pre-schedule is obtained through heuristic algorithm and then maintenance tasks are inserted into the pre-schedule scheme.Findings: It is encouraging that a new better solution for an instance in benchmark of FJSP is obtained in this research. Moreover, factually SSA used in literature for solving normal FJSPPM (FJSP with PM is not suitable for the dynamic FJSPPM. Through application in the benchmark of normal FJSPPM, it is found that although IA obtains inferior results compared to SSA used in literature, it performs much better in executing speed.Originality/value: Different to traditional scheduling of FJSP, uncertainty of machines is taken into account, which increases the complexity of the problem. An inserting algorithm (IA is proposed to solve the dynamic scheduling problem. It is stated that the quality of the final result depends much on the quality of the pre-schedule obtained during the procedure of solving a normal FJSP. In order to find the best solution of FJSP, a comparative study of three heuristics is carried out, the integrated GA, ACO and ABC. In the comparative study, we find that GA performs best in the three heuristic algorithms. Meanwhile, a new better solution for an instance in benchmark of FJSP is obtained in this research.

Parallel-aware, dedicated job co-scheduling within/across symmetric multiprocessing nodes

Science.gov (United States)

Jones, Terry R.; Watson, Pythagoras C.; Tuel, William; Brenner, Larry; ,Caffrey, Patrick; Fier, Jeffrey

2010-10-05

In a parallel computing environment comprising a network of SMP nodes each having at least one processor, a parallel-aware co-scheduling method and system for improving the performance and scalability of a dedicated parallel job having synchronizing collective operations. The method and system uses a global co-scheduler and an operating system kernel dispatcher adapted to coordinate interfering system and daemon activities on a node and across nodes to promote intra-node and inter-node overlap of said interfering system and daemon activities as well as intra-node and inter-node overlap of said synchronizing collective operations. In this manner, the impact of random short-lived interruptions, such as timer-decrement processing and periodic daemon activity, on synchronizing collective operations is minimized on large processor-count SPMD bulk-synchronous programming styles.

Production Scheduling in Complex Job Shops from an Industrie 4.0 Perspective: A Review and Challenges in the Semiconductor Industry

OpenAIRE

Waschneck, Bernd; Bauernhansl, Thomas; Altenmüller, Thomas; Kyek, Andreas

2017-01-01

On the one hand, Industrie 4.0 has recently emerged as the keyword for increasing productivity in the 21st century. On the other hand, production scheduling in a Complex Job Shop (CJS) environment, such as wafer fabrication facilities, has drawn interest of researchers dating back to the 1950s [65, 18]. Although both research areas overlap, there seems to be very little interchange of ideas. This review presents and assesses production scheduling techniques in complex job shops from an Indust...

A Review On Job Shop Scheduling Using Non-Conventional Optimization Algorithm

OpenAIRE

K.Mallikarjuna; Venkatesh.G

2014-01-01

A great deal of research has been focused on solving job shop scheduling problem (∫J), over the last four decades, resulting in a wide variety of approaches. Recently much effort has been concentrated on hybrid methods to solve ∫J, as a single technique cannot solve this stubborn problem. As a result much effort has recently been concentrated on techniques that lead to combinatorial optimization methods and a meta-strategy which guides the search out of local optima. In this p...

A job analysis of community health workers in the context of integrated nutrition and early child development.

Science.gov (United States)

Phuka, John; Maleta, Kenneth; Thomas, Mavuto; Gladstone, Melisa

2014-01-01

Stunting and poor child development are major public health concerns in Malawi. Integrated nutrition and early child development (ECD) interventions have shown potential to reduce stunting, but it is not known how these integrated approaches can be implemented in Malawi. In this paper, we aimed to evaluate the current jobs status of community health workers and their potential to implement integrated approaches. This was accomplished by a desk review of nutrition and ECD policy documents, as well as interviews with key informants, community health workers, and community members. We found that Malawi has comprehensive policies and well-outlined coordination structures for nutrition and ECD that advocate for integrated approaches. Strong multidisciplinary interaction exists at central levels but not at the community level. Integration of community health workers from different sectors is limited by workload, logistics, and a lack of synchronized work schedules. Favorable, sound policies and well-outlined coordination structures alone are not enough for the establishment of integrated nutrition and ECD activities. Balanced bureaucratic structures, improved task allocation, and synchronization of work schedules across all relevant sectors are needed for integrated intervention in Malawi. © 2014 New York Academy of Sciences.

A Hybrid Genetic Algorithm with a Knowledge-Based Operator for Solving the Job Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Hamed Piroozfard

2016-01-01

Full Text Available Scheduling is considered as an important topic in production management and combinatorial optimization in which it ubiquitously exists in most of the real-world applications. The attempts of finding optimal or near optimal solutions for the job shop scheduling problems are deemed important, because they are characterized as highly complex and NP-hard problems. This paper describes the development of a hybrid genetic algorithm for solving the nonpreemptive job shop scheduling problems with the objective of minimizing makespan. In order to solve the presented problem more effectively, an operation-based representation was used to enable the construction of feasible schedules. In addition, a new knowledge-based operator was designed based on the problem’s characteristics in order to use machines’ idle times to improve the solution quality, and it was developed in the context of function evaluation. A machine based precedence preserving order-based crossover was proposed to generate the offspring. Furthermore, a simulated annealing based neighborhood search technique was used to improve the local exploitation ability of the algorithm and to increase its population diversity. In order to prove the efficiency and effectiveness of the proposed algorithm, numerous benchmarked instances were collected from the Operations Research Library. Computational results of the proposed hybrid genetic algorithm demonstrate its effectiveness.

The Impact of the Implementation Cost of Replication in Data Grid Job Scheduling

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Babar Nazir

2018-05-01

Full Text Available Data Grids deal with geographically-distributed large-scale data-intensive applications. Schemes scheduled for data grids attempt to not only improve data access time, but also aim to improve the ratio of data availability to a node, where the data requests are generated. Data replication techniques manage large data by storing a number of data files efficiently. In this paper, we propose centralized dynamic scheduling strategy-replica placement strategies (CDSS-RPS. CDSS-RPS schedule the data and task so that it minimizes the implementation cost and data transfer time. CDSS-RPS consists of two algorithms, namely (a centralized dynamic scheduling (CDS and (b replica placement strategy (RPS. CDS considers the computing capacity of a node and finds an appropriate location for the job. RPS attempts to improve file access time by using replication on the basis of number of accesses, storage capacity of a computing node, and response time of a requested file. Extensive simulations are carried out to demonstrate the effectiveness of the proposed strategy. Simulation results demonstrate that the replication and scheduling strategies improve the implementation cost and average access time significantly.

Integrating Preventive Maintenance Scheduling As Probability Machine Failure And Batch Production Scheduling

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Zahedi Zahedi

2016-06-01

Full Text Available This paper discusses integrated model of batch production scheduling and machine maintenance scheduling. Batch production scheduling uses minimize total actual flow time criteria and machine maintenance scheduling uses the probability of machine failure based on Weibull distribution. The model assumed no nonconforming parts in a planning horizon. The model shows an increase in the number of the batch (length of production run up to a certain limit will minimize the total actual flow time. Meanwhile, an increase in the length of production run will implicate an increase in the number of PM. An example was given to show how the model and algorithm work.

Job Satisfaction: A Possible Integration of Two Theories

Science.gov (United States)

Hazer, John T.

1976-01-01

The author proposes an integration of Herzberg's two-factor theory of job satisfaction (job satisfaction/dissatisfaction as two separate, parallel continua) and traditional theory (job satisfaction/dissatisfaction sharing the same continuum) and a rationale for deciding which motivation methods to use for employees with differeing levels of…

Variable Neighbourhood Search and Mathematical Programming for Just-in-Time Job-Shop Scheduling Problem

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Sunxin Wang

2014-01-01

Full Text Available This paper presents a combination of variable neighbourhood search and mathematical programming to minimize the sum of earliness and tardiness penalty costs of all operations for just-in-time job-shop scheduling problem (JITJSSP. Unlike classical E/T scheduling problem with each job having its earliness or tardiness penalty cost, each operation in this paper has its earliness and tardiness penalties, which are paid if the operation is completed before or after its due date. Our hybrid algorithm combines (i a variable neighbourhood search procedure to explore the huge feasible solution spaces efficiently by alternating the swap and insertion neighbourhood structures and (ii a mathematical programming model to optimize the completion times of the operations for a given solution in each iteration procedure. Additionally, a threshold accepting mechanism is proposed to diversify the local search of variable neighbourhood search. Computational results on the 72 benchmark instances show that our algorithm can obtain the best known solution for 40 problems, and the best known solutions for 33 problems are updated.

Economic Benefit from Progressive Integration of Scheduling and Control for Continuous Chemical Processes

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Logan D. R. Beal

2017-12-01

Full Text Available Performance of integrated production scheduling and advanced process control with disturbances is summarized and reviewed with four progressive stages of scheduling and control integration and responsiveness to disturbances: open-loop segregated scheduling and control, closed-loop segregated scheduling and control, open-loop scheduling with consideration of process dynamics, and closed-loop integrated scheduling and control responsive to process disturbances and market fluctuations. Progressive economic benefit from dynamic rescheduling and integrating scheduling and control is shown on a continuously stirred tank reactor (CSTR benchmark application in closed-loop simulations over 24 h. A fixed horizon integrated scheduling and control formulation for multi-product, continuous chemical processes is utilized, in which nonlinear model predictive control (NMPC and continuous-time scheduling are combined.

The moderating effect of control over work scheduling and overtime on the relationship between workload demands and perceived job risk.

Science.gov (United States)

Näswall, Katharina; Burt, Christopher D B; Pearce, Megan

2015-01-01

This study investigated the impact of workload demands on perceived job risk using the Job Demand-Control model as a research framework. The primary objective was to test the hypothesis that employee control over work scheduling and overtime would moderate the relationship between workload demands and perceived job risk. Ninety-six participants working in a variety of industries completed measures of workload demands, and of control over work scheduling and overtime, and a measure of perceived job risk. Workload demands predicted higher perceptions of job risk. However, the results also suggest that control over overtime moderated this relationship, where those with the combination of high workload demands and low control over overtime reported higher levels of perceived risk. The results indicate that the JDC model is applicable to safety research. The results suggest that employee control over workload demands is an important variable to consider in terms of managing workplace safety. The present study also points to important areas for future research to explore in order to further understand the connection between demands and safety.

Performance evaluation of different types of particle representation procedures of Particle Swarm Optimization in Job-shop Scheduling Problems

Science.gov (United States)

Izah Anuar, Nurul; Saptari, Adi

2016-02-01

This paper addresses the types of particle representation (encoding) procedures in a population-based stochastic optimization technique in solving scheduling problems known in the job-shop manufacturing environment. It intends to evaluate and compare the performance of different particle representation procedures in Particle Swarm Optimization (PSO) in the case of solving Job-shop Scheduling Problems (JSP). Particle representation procedures refer to the mapping between the particle position in PSO and the scheduling solution in JSP. It is an important step to be carried out so that each particle in PSO can represent a schedule in JSP. Three procedures such as Operation and Particle Position Sequence (OPPS), random keys representation and random-key encoding scheme are used in this study. These procedures have been tested on FT06 and FT10 benchmark problems available in the OR-Library, where the objective function is to minimize the makespan by the use of MATLAB software. Based on the experimental results, it is discovered that OPPS gives the best performance in solving both benchmark problems. The contribution of this paper is the fact that it demonstrates to the practitioners involved in complex scheduling problems that different particle representation procedures can have significant effects on the performance of PSO in solving JSP.

MIP Models and Hybrid Algorithms for Simultaneous Job Splitting and Scheduling on Unrelated Parallel Machines

Science.gov (United States)

Ozmutlu, H. Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms. PMID:24977204

MIP models and hybrid algorithms for simultaneous job splitting and scheduling on unrelated parallel machines.

Science.gov (United States)

Eroglu, Duygu Yilmaz; Ozmutlu, H Cenk

2014-01-01

We developed mixed integer programming (MIP) models and hybrid genetic-local search algorithms for the scheduling problem of unrelated parallel machines with job sequence and machine-dependent setup times and with job splitting property. The first contribution of this paper is to introduce novel algorithms which make splitting and scheduling simultaneously with variable number of subjobs. We proposed simple chromosome structure which is constituted by random key numbers in hybrid genetic-local search algorithm (GAspLA). Random key numbers are used frequently in genetic algorithms, but it creates additional difficulty when hybrid factors in local search are implemented. We developed algorithms that satisfy the adaptation of results of local search into the genetic algorithms with minimum relocation operation of genes' random key numbers. This is the second contribution of the paper. The third contribution of this paper is three developed new MIP models which are making splitting and scheduling simultaneously. The fourth contribution of this paper is implementation of the GAspLAMIP. This implementation let us verify the optimality of GAspLA for the studied combinations. The proposed methods are tested on a set of problems taken from the literature and the results validate the effectiveness of the proposed algorithms.

Near-Optimal Heuristics for Just-In-Time Jobs Maximization in Flow Shop Scheduling

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Helio Yochihiro Fuchigami

2018-04-01

Full Text Available The number of just-in-time jobs maximization in a permutation flow shop scheduling problem is considered. A mixed integer linear programming model to represent the problem as well as solution approaches based on enumeration and constructive heuristics were proposed and computationally implemented. Instances with up to 10 jobs and five machines are solved by the mathematical model in an acceptable running time (3.3 min on average while the enumeration method consumes, on average, 1.5 s. The 10 constructive heuristics proposed show they are practical especially for large-scale instances (up to 100 jobs and 20 machines, with very good-quality results and efficient running times. The best two heuristics obtain near-optimal solutions, with only 0.6% and 0.8% average relative deviations. They prove to be better than adaptations of the NEH heuristic (well-known for providing very good solutions for makespan minimization in flow shop for the considered problem.

Hybrid Discrete Differential Evolution Algorithm for Lot Splitting with Capacity Constraints in Flexible Job Scheduling

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Xinli Xu

2013-01-01

Full Text Available A two-level batch chromosome coding scheme is proposed to solve the lot splitting problem with equipment capacity constraints in flexible job shop scheduling, which includes a lot splitting chromosome and a lot scheduling chromosome. To balance global search and local exploration of the differential evolution algorithm, a hybrid discrete differential evolution algorithm (HDDE is presented, in which the local strategy with dynamic random searching based on the critical path and a random mutation operator is developed. The performance of HDDE was experimented with 14 benchmark problems and the practical dye vat scheduling problem. The simulation results showed that the proposed algorithm has the strong global search capability and can effectively solve the practical lot splitting problems with equipment capacity constraints.

Management information system for cost-schedule integration control for nuclear power projects

International Nuclear Information System (INIS)

Liu Wei; Wang Yongqing; Tian Li

2001-01-01

Based on the project management experience abroad and at home, a cost-schedule integration control model was developed to improve nuclear power project management. The model integrates cost data with the scheduling data by unity coding to efficiently implement cost-schedule integration control on line. The software system architecture and database is designed and implemented. The system functions include estimating and forecasting dynamically cash flow, scheduling and evaluating deviation from the cost-schedule plan, etc. The research and development of the system should improve the architecture of computer integrated management information systems for nuclear power projects in China

Multi-objective flexible job-shop scheduling problem using modified discrete particle swarm optimization.

Science.gov (United States)

Huang, Song; Tian, Na; Wang, Yan; Ji, Zhicheng

2016-01-01

Taking resource allocation into account, flexible job shop problem (FJSP) is a class of complex scheduling problem in manufacturing system. In order to utilize the machine resources rationally, multi-objective particle swarm optimization (MOPSO) integrating with variable neighborhood search is introduced to address FJSP efficiently. Firstly, the assignment rules (AL) and dispatching rules (DR) are provided to initialize the population. And then special discrete operators are designed to produce new individuals and earliest completion machine (ECM) is adopted in the disturbance operator to escape the optima. Secondly, personal-best archives (cognitive memories) and global-best archive (social memory), which are updated by the predefined non-dominated archive update strategy, are simultaneously designed to preserve non-dominated individuals and select personal-best positions and the global-best position. Finally, three neighborhoods are provided to search the neighborhoods of global-best archive for enhancing local search ability. The proposed algorithm is evaluated by using Kacem instances and Brdata instances, and a comparison with other approaches shows the effectiveness of the proposed algorithm for FJSP.

Job shop scheduling model for non-identic machine with fixed delivery time to minimize tardiness

Science.gov (United States)

Kusuma, K. K.; Maruf, A.

2016-02-01

Scheduling non-identic machines problem with low utilization characteristic and fixed delivery time are frequent in manufacture industry. This paper propose a mathematical model to minimize total tardiness for non-identic machines in job shop environment. This model will be categorized as an integer linier programming model and using branch and bound algorithm as the solver method. We will use fixed delivery time as main constraint and different processing time to process a job. The result of this proposed model shows that the utilization of production machines can be increase with minimal tardiness using fixed delivery time as constraint.

Ant colony optimisation for scheduling of flexible job shop with multi-resources requirements

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Kalinowski Krzysztof

2017-01-01

Full Text Available The paper presents application of ant colony optimisation algorithm for scheduling multi-resources operations in flexible job shop type of production systems. Operations that require the participation of two or more resources are common in industrial practice, when planning are subject not only machines, but also other additional resources (personnel, tools, etc.. Resource requirements of operation are indicated indirectly by resource groups. The most important parameters of the resource model and resource groups are also described. A basic assumptions for ant colony algorithm used for scheduling in the considered model with multiresources requirements of operations is discussed. The main result of the research is the schema of metaheuristic that enables searching best-score solutions in manufacturing systems satisfying presented constraints.

Heuristic and Exact Algorithms for the Two-Machine Just in Time Job Shop Scheduling Problem

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Mohammed Al-Salem

2016-01-01

Full Text Available The problem addressed in this paper is the two-machine job shop scheduling problem when the objective is to minimize the total earliness and tardiness from a common due date (CDD for a set of jobs when their weights equal 1 (unweighted problem. This objective became very significant after the introduction of the Just in Time manufacturing approach. A procedure to determine whether the CDD is restricted or unrestricted is developed and a semirestricted CDD is defined. Algorithms are introduced to find the optimal solution when the CDD is unrestricted and semirestricted. When the CDD is restricted, which is a much harder problem, a heuristic algorithm is proposed to find approximate solutions. Through computational experiments, the heuristic algorithms’ performance is evaluated with problems up to 500 jobs.

Automatic programming via iterated local search for dynamic job shop scheduling.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2015-01-01

Dispatching rules have been commonly used in practice for making sequencing and scheduling decisions. Due to specific characteristics of each manufacturing system, there is no universal dispatching rule that can dominate in all situations. Therefore, it is important to design specialized dispatching rules to enhance the scheduling performance for each manufacturing environment. Evolutionary computation approaches such as tree-based genetic programming (TGP) and gene expression programming (GEP) have been proposed to facilitate the design task through automatic design of dispatching rules. However, these methods are still limited by their high computational cost and low exploitation ability. To overcome this problem, we develop a new approach to automatic programming via iterated local search (APRILS) for dynamic job shop scheduling. The key idea of APRILS is to perform multiple local searches started with programs modified from the best obtained programs so far. The experiments show that APRILS outperforms TGP and GEP in most simulation scenarios in terms of effectiveness and efficiency. The analysis also shows that programs generated by APRILS are more compact than those obtained by genetic programming. An investigation of the behavior of APRILS suggests that the good performance of APRILS comes from the balance between exploration and exploitation in its search mechanism.

Integration of Formal Job Hazard Analysis and ALARA Work Practice

International Nuclear Information System (INIS)

NELSEN, D.P.

2002-01-01

ALARA work practices have traditionally centered on reducing radiological exposure and controlling contamination. As such, ALARA policies and procedures are not well suited to a wide range of chemical and human health issues. Assessing relative risk, identifying appropriate engineering/administrative controls and selecting proper Personal Protective Equipment (PPE) for non nuclear work activities extends beyond the limitations of traditional ALARA programs. Forging a comprehensive safety management program in today's (2002) work environment requires a disciplined dialog between health and safety professionals (e.g. safety, engineering, environmental, quality assurance, industrial hygiene, ALARA, etc.) and personnel working in the field. Integrating organizational priorities, maintaining effective pre-planning of work and supporting a team-based approach to safety management represents today's hallmark of safety excellence. Relying on the mandates of any single safety program does not provide industrial hygiene with the tools necessary to implement an integrated safety program. The establishment of tools and processes capable of sustaining a comprehensive safety program represents a key responsibility of industrial hygiene. Fluor Hanford has built integrated safety management around three programmatic attributes: (1) Integration of radiological, chemical and ergonomic issues under a single program. (2) Continuous improvement in routine communications among work planning/scheduling, job execution and management. (3) Rapid response to changing work conditions, formalized work planning and integrated worker involvement

The triangle scheduling problem

NARCIS (Netherlands)

Dürr, Christoph; Hanzálek, Zdeněk; Konrad, Christian; Seddik, Yasmina; Sitters, R.A.; Vásquez, Óscar C.; Woeginger, Gerhard

2017-01-01

This paper introduces a novel scheduling problem, where jobs occupy a triangular shape on the time line. This problem is motivated by scheduling jobs with different criticality levels. A measure is introduced, namely the binary tree ratio. It is shown that the Greedy algorithm solves the problem to

Project control integrating cost and schedule in construction

CERN Document Server

Del Pico, Wayne J

2013-01-01

The key to successful project control is the fusing of cost to schedule whereby the management of one helps to manage the other. Project Control: Integrating Cost and Schedule in Construction explores the reasons behind and the methodologies for proper planning, monitoring, and controlling both project costs and schedule. Filling a current void the topic of project control applied to the construction industry, it is essential reading for students and professionals alike.

A Novel Memetic Algorithm Based on Decomposition for Multiobjective Flexible Job Shop Scheduling Problem

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Chun Wang

2017-01-01

Full Text Available A novel multiobjective memetic algorithm based on decomposition (MOMAD is proposed to solve multiobjective flexible job shop scheduling problem (MOFJSP, which simultaneously minimizes makespan, total workload, and critical workload. Firstly, a population is initialized by employing an integration of different machine assignment and operation sequencing strategies. Secondly, multiobjective memetic algorithm based on decomposition is presented by introducing a local search to MOEA/D. The Tchebycheff approach of MOEA/D converts the three-objective optimization problem to several single-objective optimization subproblems, and the weight vectors are grouped by K-means clustering. Some good individuals corresponding to different weight vectors are selected by the tournament mechanism of a local search. In the experiments, the influence of three different aggregation functions is first studied. Moreover, the effect of the proposed local search is investigated. Finally, MOMAD is compared with eight state-of-the-art algorithms on a series of well-known benchmark instances and the experimental results show that the proposed algorithm outperforms or at least has comparative performance to the other algorithms.

COMPARISON BETWEEN MIXED INTEGER PROGRAMMING WITH HEURISTIC METHOD FOR JOB SHOP SCHEDULING WITH SEPARABLE SEQUENCE-DEPENDENT SETUPS

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I Gede Agus Widyadana

2001-01-01

Full Text Available The decisions to choose appropriate tools for solving industrial problems are not just tools that achieve optimal solution only but it should consider computation time too. One of industrial problems that still difficult to achieve both criteria is scheduling problem. This paper discuss comparison between mixed integer programming which result optimal solution and heuristic method to solve job shop scheduling problem with separable sequence-dependent setup. The problems are generated and the result shows that the heuristic methods still cannot satisfy optimal solution.

An Improved Version of Discrete Particle Swarm Optimization for Flexible Job Shop Scheduling Problem with Fuzzy Processing Time

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Song Huang

2016-01-01

Full Text Available The fuzzy processing time occasionally exists in job shop scheduling problem of flexible manufacturing system. To deal with fuzzy processing time, fuzzy flexible job shop model was established in several papers and has attracted numerous researchers’ attention recently. In our research, an improved version of discrete particle swarm optimization (IDPSO is designed to solve flexible job shop scheduling problem with fuzzy processing time (FJSPF. In IDPSO, heuristic initial methods based on triangular fuzzy number are developed, and a combination of six initial methods is applied to initialize machine assignment and random method is used to initialize operation sequence. Then, some simple and effective discrete operators are employed to update particle’s position and generate new particles. In order to guide the particles effectively, we extend global best position to a set with several global best positions. Finally, experiments are designed to investigate the impact of four parameters in IDPSO by Taguchi method, and IDPSO is tested on five instances and compared with some state-of-the-art algorithms. The experimental results show that the proposed algorithm can obtain better solutions for FJSPF and is more competitive than the compared algorithms.

Mechanisms for scheduling games with selfish players

NARCIS (Netherlands)

Hoeksma, R.P.

2015-01-01

Many challenges in operations research involve optimization. In particular, scheduling treats the optimal planning of tasks. This thesis focuses on machine scheduling models, where a number of tasks, called jobs, need to be scheduled on one or more machines. The outcome is determined by which job is

Work Scheduling by Use of Worker Model in Consideration of Learning by On-The-Job Training

Science.gov (United States)

Tateno, Toshitake; Shimizu, Keiko

This paper deals with a method of scheduling manual work in consideration of learning by on-the-job training (OJT). In skilled work such as maintenance of trains and airplanes, workers must learn many tasks by OJT. While the work processing time of novice workers is longer than that of experts, the time will be reduced with repeated OJT. Therefore, OJT is important for maintaining the skill level and the long-term work efficiency of an organization. In order to devise a schedule considering OJT, the scheduler must incorporate a management function of workers to trace dynamically changing work experience. In this paper, after the relationship between scheduling problems and worker management problems is defined, a simulation method, in which a worker model and an agent-based mechanism are utilized, is proposed to derive the optimal OJT strategy toward high long-term performance. Finally, we present some case studies showing the effectiveness of OJT planning based on the simulation.

A RELATIONAL DATABASE APPROACH TO THE JOB SHOP SCHEDULING PROBLEM

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P. Lindeque

2012-01-01

Full Text Available

ENGLISH ABSTRACT: This paper will attempt to illuminate the advantages of an approach to the job shop scheduling problem using priority based search algorithms and database technology. It will use as basis a system developed for and implemented at a large manufacturing plant. The paper will also attempt to make some predictions as to future developments in these techniques and look at the possibility of including new technologies such as expert systems.

AFRIKAANSE OPSOMMING: Die voordele en toepaslikheid van prioriteits-gebaseerde soek-algoritmes en databasisstelsels op die taakwerkswinkelprobleem sal in hierdie artikel uitgelig word. 'n Stelsel wat by 'n groot vervaardigingsonderneming geimplementeer is, sal as uitgangspunt gebruik word. Toekomstige ontwikkelings in bogenoemde tegnieke en die moontlike insluiting van ekspertstelsels sal ook ondersoek word.

Underground storage tank - Integrated Demonstration Technical Task Plan master schedule

International Nuclear Information System (INIS)

Johnson, C.M.

1994-08-01

This document provides an integrated programmatic schedule (i.e., Master Schedule) for the U.S. Department of Energy (DOE) Underground Storage Tank-Integrated Demonstration (UST-ID) Program. It includes top-level schedule and related information for the DOE Office of Technology Development (EM-50) UST-ID activities. The information is based upon the fiscal year (FY) 1994 technical task plans (TTPS) and has been prepared as a baseline information resource for program participants. The Master Schedule contains Level 0 and Level 1 program schedules for the UST-ID Program. This document is one of a number of programmatic documents developed to support and manage the UST-ID activities. It is composed of the following sections: Program Overview - provides a summary background of the UST-ID Program. This summary addresses the mission, scope, and organizational structure of the program; Activity Description - provides a programmatic description of UST-ID technology development activities and lists the key milestones for the UST-ID systems. Master Schedules - contains the Level 0 and Level 1 programmatic schedules for the UST-ID systems. References - lists the UST-ID programmatic documents used as a basis for preparing the Master Schedule. The appendixes contain additional details related to site-specific technology applications

Decay-usage scheduling in multiprocessors

NARCIS (Netherlands)

Epema, D.H.J.

1998-01-01

Decay-usage scheduling is a priority-aging time-sharing scheduling policy capable of dealing with a workload of both interactive and batch jobs by decreasing the priority of a job when it acquires CPU time, and by increasing its priority when it does not use the (a) CPU. In this article we deal with

Solving project scheduling problems by minimum cut computations

NARCIS (Netherlands)

Möhring, R.H.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen

In project scheduling, a set of precedence-constrained jobs has to be scheduled so as to minimize a given objective. In resource-constrained project scheduling, the jobs additionally compete for scarce resources. Due to its universality, the latter problem has a variety of applications in

A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling

Directory of Open Access Journals (Sweden)

Qianwang Deng

2017-01-01

Full Text Available Flexible job-shop scheduling problem (FJSP is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II for multiobjective FJSP (MO-FJSP with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N, in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed.

A Bee Evolutionary Guiding Nondominated Sorting Genetic Algorithm II for Multiobjective Flexible Job-Shop Scheduling.

Science.gov (United States)

Deng, Qianwang; Gong, Guiliang; Gong, Xuran; Zhang, Like; Liu, Wei; Ren, Qinghua

2017-01-01

Flexible job-shop scheduling problem (FJSP) is an NP-hard puzzle which inherits the job-shop scheduling problem (JSP) characteristics. This paper presents a bee evolutionary guiding nondominated sorting genetic algorithm II (BEG-NSGA-II) for multiobjective FJSP (MO-FJSP) with the objectives to minimize the maximal completion time, the workload of the most loaded machine, and the total workload of all machines. It adopts a two-stage optimization mechanism during the optimizing process. In the first stage, the NSGA-II algorithm with T iteration times is first used to obtain the initial population N , in which a bee evolutionary guiding scheme is presented to exploit the solution space extensively. In the second stage, the NSGA-II algorithm with GEN iteration times is used again to obtain the Pareto-optimal solutions. In order to enhance the searching ability and avoid the premature convergence, an updating mechanism is employed in this stage. More specifically, its population consists of three parts, and each of them changes with the iteration times. What is more, numerical simulations are carried out which are based on some published benchmark instances. Finally, the effectiveness of the proposed BEG-NSGA-II algorithm is shown by comparing the experimental results and the results of some well-known algorithms already existed.

Evolution of CMS Workload Management Towards Multicore Job Support

Energy Technology Data Exchange (ETDEWEB)

Perez-Calero Yzquierdo, A. [Madrid, CIEMAT; Hernández, J. M. [Madrid, CIEMAT; Khan, F. A. [Quaid-i-Azam U.; Letts, J. [UC, San Diego; Majewski, K. [Fermilab; Rodrigues, A. M. [Fermilab; McCrea, A. [UC, San Diego; Vaandering, E. [Fermilab

2015-12-23

The successful exploitation of multicore processor architectures is a key element of the LHC distributed computing system in the coming era of the LHC Run 2. High-pileup complex-collision events represent a challenge for the traditional sequential programming in terms of memory and processing time budget. The CMS data production and processing framework is introducing the parallel execution of the reconstruction and simulation algorithms to overcome these limitations. CMS plans to execute multicore jobs while still supporting singlecore processing for other tasks difficult to parallelize, such as user analysis. The CMS strategy for job management thus aims at integrating single and multicore job scheduling across the Grid. This is accomplished by employing multicore pilots with internal dynamic partitioning of the allocated resources, capable of running payloads of various core counts simultaneously. An extensive test programme has been conducted to enable multicore scheduling with the various local batch systems available at CMS sites, with the focus on the Tier-0 and Tier-1s, responsible during 2015 of the prompt data reconstruction. Scale tests have been run to analyse the performance of this scheduling strategy and ensure an efficient use of the distributed resources. This paper presents the evolution of the CMS job management and resource provisioning systems in order to support this hybrid scheduling model, as well as its deployment and performance tests, which will enable CMS to transition to a multicore production model for the second LHC run.

The power of reordering for online minimum makespan scheduling

OpenAIRE

Englert, Matthias; Özmen, Deniz; Westermann, Matthias

2014-01-01

In the classic minimum makespan scheduling problem, we are given an input sequence of jobs with processing times. A scheduling algorithm has to assign the jobs to m parallel machines. The objective is to minimize the makespan, which is the time it takes until all jobs are processed. In this paper, we consider online scheduling algorithms without preemption. However, we do not require that each arriving job has to be assigned immediately to one of the machines. A reordering buffer with limited...

Job Characteristics and Pressures and the Organizational Integration of Professionals

Science.gov (United States)

Hall, Douglas T.; Lawler, Edward E.

1970-01-01

Focuses on the relationship between job design and the integration of the professional with his organization; the concept of job pressures is used as an intervening variable in the study of his relationship. (Author)

CMS multicore scheduling strategy

International Nuclear Information System (INIS)

Yzquierdo, Antonio Pérez-Calero; Hernández, Jose; Holzman, Burt; Majewski, Krista; McCrea, Alison

2014-01-01

In the next years, processor architectures based on much larger numbers of cores will be most likely the model to continue 'Moore's Law' style throughput gains. This not only results in many more jobs in parallel running the LHC Run 1 era monolithic applications, but also the memory requirements of these processes push the workernode architectures to the limit. One solution is parallelizing the application itself, through forking and memory sharing or through threaded frameworks. CMS is following all of these approaches and has a comprehensive strategy to schedule multicore jobs on the GRID based on the glideinWMS submission infrastructure. The main component of the scheduling strategy, a pilot-based model with dynamic partitioning of resources that allows the transition to multicore or whole-node scheduling without disallowing the use of single-core jobs, is described. This contribution also presents the experiences made with the proposed multicore scheduling schema and gives an outlook of further developments working towards the restart of the LHC in 2015.

Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms

Directory of Open Access Journals (Sweden)

Kuo-Yang Wu

2013-01-01

Full Text Available We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS in the Flexible Manufacturing System (FMS used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA, the Immune Genetic Algorithm (IGA, and the Particle Swarm Optimization (PSO algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.

An Artificial Bee Colony Algorithm for the Job Shop Scheduling Problem with Random Processing Times

Directory of Open Access Journals (Sweden)

Rui Zhang

2011-09-01

Full Text Available Due to the influence of unpredictable random events, the processing time of each operation should be treated as random variables if we aim at a robust production schedule. However, compared with the extensive research on the deterministic model, the stochastic job shop scheduling problem (SJSSP has not received sufficient attention. In this paper, we propose an artificial bee colony (ABC algorithm for SJSSP with the objective of minimizing the maximum lateness (which is an index of service quality. First, we propose a performance estimate for preliminary screening of the candidate solutions. Then, the K-armed bandit model is utilized for reducing the computational burden in the exact evaluation (through Monte Carlo simulation process. Finally, the computational results on different-scale test problems validate the effectiveness and efficiency of the proposed approach.

Flexible Job-Shop Scheduling with Dual-Resource Constraints to Minimize Tardiness Using Genetic Algorithm

Science.gov (United States)

Paksi, A. B. N.; Ma'ruf, A.

2016-02-01

In general, both machines and human resources are needed for processing a job on production floor. However, most classical scheduling problems have ignored the possible constraint caused by availability of workers and have considered only machines as a limited resource. In addition, along with production technology development, routing flexibility appears as a consequence of high product variety and medium demand for each product. Routing flexibility is caused by capability of machines that offers more than one machining process. This paper presents a method to address scheduling problem constrained by both machines and workers, considering routing flexibility. Scheduling in a Dual-Resource Constrained shop is categorized as NP-hard problem that needs long computational time. Meta-heuristic approach, based on Genetic Algorithm, is used due to its practical implementation in industry. Developed Genetic Algorithm uses indirect chromosome representative and procedure to transform chromosome into Gantt chart. Genetic operators, namely selection, elitism, crossover, and mutation are developed to search the best fitness value until steady state condition is achieved. A case study in a manufacturing SME is used to minimize tardiness as objective function. The algorithm has shown 25.6% reduction of tardiness, equal to 43.5 hours.

Tramp ship routing and scheduling with integrated bunker optimization

DEFF Research Database (Denmark)

Vilhelmsen, Charlotte; Lusby, Richard Martin; Larsen, Jesper

2014-01-01

is referred to as bunker and bunker costs constitute a significant part of the daily operating costs. There can be great variations in bunker prices across bunker ports so it is important to carefully plan bunkering for each ship. As ships operate 24 hours a day, they must refuel during operations. Therefore...... and scheduling phase and present a mixed integer programming formulation for the integrated problem of optimally routing, scheduling and bunkering a tramp fleet. Aside from the integration of bunker, this model also extends standard tramp formulations by using load dependent costs, speed and bunker consumption...

A microeconomic scheduler for parallel computers

Science.gov (United States)

Stoica, Ion; Abdel-Wahab, Hussein; Pothen, Alex

1995-01-01

We describe a scheduler based on the microeconomic paradigm for scheduling on-line a set of parallel jobs in a multiprocessor system. In addition to the classical objectives of increasing the system throughput and reducing the response time, we consider fairness in allocating system resources among the users, and providing the user with control over the relative performances of his jobs. We associate with every user a savings account in which he receives money at a constant rate. When a user wants to run a job, he creates an expense account for that job to which he transfers money from his savings account. The job uses the funds in its expense account to obtain the system resources it needs for execution. The share of the system resources allocated to the user is directly related to the rate at which the user receives money; the rate at which the user transfers money into a job expense account controls the job's performance. We prove that starvation is not possible in our model. Simulation results show that our scheduler improves both system and user performances in comparison with two different variable partitioning policies. It is also shown to be effective in guaranteeing fairness and providing control over the performance of jobs.

Car painting process scheduling with harmony search algorithm

Science.gov (United States)

Syahputra, M. F.; Maiyasya, A.; Purnamawati, S.; Abdullah, D.; Albra, W.; Heikal, M.; Abdurrahman, A.; Khaddafi, M.

2018-02-01

Automotive painting program in the process of painting the car body by using robot power, making efficiency in the production system. Production system will be more efficient if pay attention to scheduling of car order which will be done by considering painting body shape of car. Flow shop scheduling is a scheduling model in which the job-job to be processed entirely flows in the same product direction / path. Scheduling problems often arise if there are n jobs to be processed on the machine, which must be specified which must be done first and how to allocate jobs on the machine to obtain a scheduled production process. Harmony Search Algorithm is a metaheuristic optimization algorithm based on music. The algorithm is inspired by observations that lead to music in search of perfect harmony. This musical harmony is in line to find optimal in the optimization process. Based on the tests that have been done, obtained the optimal car sequence with minimum makespan value.

Evaluation of a twelve-hour/day shift schedule

International Nuclear Information System (INIS)

Lewis, P.M.; Swaim, D.J.

1986-01-01

In April 1985, the operating crews at the Fast Flux Test Facility near Richland, Washington, changed their rotating shift schedule from an 8-hour to a 12-hour a day work schedule. The primary purpose of the change was to reduce the attrition of operators by increasing their job satisfaction. Eighty-four percent of the operators favored the change. A program was established to evaluate the effects on plant performance, operator alertness, attrition, sleep, health, job satisfaction, and off-the-job satisfaction. Preliminary results from that evaluation program indicate that the 12-hour shift schedule is a reasonable alternative to an 8-hour schedule at this facility

Integration of Learning and Practice for Job Sharing Partnerships

Science.gov (United States)

Dixon-Krausse, Pamela Marie

2007-01-01

This paper explores the forces that support the proliferation of the flexible work arrangement called job sharing. Moreover, the paper will illuminate the need for integrating learning and practice as a way to develop and support job sharing partners, or "Partners in Practice" (PiPs). The author puts forth a model derived from learning in…

A Flexible Job Shop Scheduling Problem with Controllable Processing Times to Optimize Total Cost of Delay and Processing

Directory of Open Access Journals (Sweden)

Hadi Mokhtari

2015-11-01

Full Text Available In this paper, the flexible job shop scheduling problem with machine flexibility and controllable process times is studied. The main idea is that the processing times of operations may be controlled by consumptions of additional resources. The purpose of this paper to find the best trade-off between processing cost and delay cost in order to minimize the total costs. The proposed model, flexible job shop scheduling with controllable processing times (FJCPT, is formulated as an integer non-linear programming (INLP model and then it is converted into an integer linear programming (ILP model. Due to NP-hardness of FJCPT, conventional analytic optimization methods are not efficient. Hence, in order to solve the problem, a Scatter Search (SS, as an efficient metaheuristic method, is developed. To show the effectiveness of the proposed method, numerical experiments are conducted. The efficiency of the proposed algorithm is compared with that of a genetic algorithm (GA available in the literature for solving FJSP problem. The results showed that the proposed SS provide better solutions than the existing GA.

Designing an advanced available-to-promise mechanism compatible with the make-to-forecast production systems through integrating inventory allocation and job shop scheduling with due dates and weighted earliness/tardiness cost

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2016-06-01

Full Text Available In the competitive business world, applying a reliable and powerful mechanism to support decision makers in manufacturing companies and helping them save time by considering varieties of effective factors is an inevitable issue. Advanced Available-to-Promise is a perfect tool to design and perform such a mechanism. In this study, this mechanism which is compatible with the Make-to-Forecast production systems is presented. The ability to distinguish between batch mode and real-time mode advanced available-to-promise is one of the unique superiorities of the proposed model. We also try to strengthen this mechanism by integrating the inventory allocation and job shop scheduling by considering due dates and weighted earliness/tardiness cost that leads to more precise decisions. A mixed integer programming (MIP model and a heuristic algorithm according to its disability to solve large size problems are presented. The designed experiments and the obtained results have proved the efficiency of the proposed heuristic method.

Integrated network design and scheduling problems :

Energy Technology Data Exchange (ETDEWEB)

Nurre, Sarah G.; Carlson, Jeffrey J.

2014-01-01

We consider the class of integrated network design and scheduling problems. These problems focus on selecting and scheduling operations that will change the characteristics of a network, while being speci cally concerned with the performance of the network over time. Motivating applications of INDS problems include infrastructure restoration after extreme events and building humanitarian distribution supply chains. While similar models have been proposed, no one has performed an extensive review of INDS problems from their complexity, network and scheduling characteristics, information, and solution methods. We examine INDS problems under a parallel identical machine scheduling environment where the performance of the network is evaluated by solving classic network optimization problems. We classify that all considered INDS problems as NP-Hard and propose a novel heuristic dispatching rule algorithm that selects and schedules sets of arcs based on their interactions in the network. We present computational analysis based on realistic data sets representing the infrastructures of coastal New Hanover County, North Carolina, lower Manhattan, New York, and a realistic arti cial community CLARC County. These tests demonstrate the importance of a dispatching rule to arrive at near-optimal solutions during real-time decision making activities. We extend INDS problems to incorporate release dates which represent the earliest an operation can be performed and exible release dates through the introduction of specialized machine(s) that can perform work to move the release date earlier in time. An online optimization setting is explored where the release date of a component is not known.

Integrated Production-Distribution Scheduling Problem with Multiple Independent Manufacturers

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Jianhong Hao

2015-01-01

Full Text Available We consider the nonstandard parts supply chain with a public service platform for machinery integration in China. The platform assigns orders placed by a machinery enterprise to multiple independent manufacturers who produce nonstandard parts and makes production schedule and batch delivery schedule for each manufacturer in a coordinate manner. Each manufacturer has only one plant with parallel machines and is located at a location far away from other manufacturers. Orders are first processed at the plants and then directly shipped from the plants to the enterprise in order to be finished before a given deadline. We study the above integrated production-distribution scheduling problem with multiple manufacturers to maximize a weight sum of the profit of each manufacturer under the constraints that all orders are finished before the deadline and the profit of each manufacturer is not negative. According to the optimal condition analysis, we formulate the problem as a mixed integer programming model and use CPLEX to solve it.

A Hyper-Heuristic Ensemble Method for Static Job-Shop Scheduling.

Science.gov (United States)

Hart, Emma; Sim, Kevin

2016-01-01

We describe a new hyper-heuristic method NELLI-GP for solving job-shop scheduling problems (JSSP) that evolves an ensemble of heuristics. The ensemble adopts a divide-and-conquer approach in which each heuristic solves a unique subset of the instance set considered. NELLI-GP extends an existing ensemble method called NELLI by introducing a novel heuristic generator that evolves heuristics composed of linear sequences of dispatching rules: each rule is represented using a tree structure and is itself evolved. Following a training period, the ensemble is shown to outperform both existing dispatching rules and a standard genetic programming algorithm on a large set of new test instances. In addition, it obtains superior results on a set of 210 benchmark problems from the literature when compared to two state-of-the-art hyper-heuristic approaches. Further analysis of the relationship between heuristics in the evolved ensemble and the instances each solves provides new insights into features that might describe similar instances.

Multi-objective flexible job shop scheduling problem using variable neighborhood evolutionary algorithm

Science.gov (United States)

Wang, Chun; Ji, Zhicheng; Wang, Yan

2017-07-01

In this paper, multi-objective flexible job shop scheduling problem (MOFJSP) was studied with the objects to minimize makespan, total workload and critical workload. A variable neighborhood evolutionary algorithm (VNEA) was proposed to obtain a set of Pareto optimal solutions. First, two novel crowded operators in terms of the decision space and object space were proposed, and they were respectively used in mating selection and environmental selection. Then, two well-designed neighborhood structures were used in local search, which consider the problem characteristics and can hold fast convergence. Finally, extensive comparison was carried out with the state-of-the-art methods specially presented for solving MOFJSP on well-known benchmark instances. The results show that the proposed VNEA is more effective than other algorithms in solving MOFJSP.

A Hybrid Multiobjective Evolutionary Approach for Flexible Job-Shop Scheduling Problems

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Jian Xiong

2012-01-01

Full Text Available This paper addresses multiobjective flexible job-shop scheduling problem (FJSP with three simultaneously considered objectives: minimizing makespan, minimizing total workload, and minimizing maximal workload. A hybrid multiobjective evolutionary approach (H-MOEA is developed to solve the problem. According to the characteristic of FJSP, a modified crowding distance measure is introduced to maintain the diversity of individuals. In the proposed H-MOEA, well-designed chromosome representation and genetic operators are developed for FJSP. Moreover, a local search procedure based on critical path theory is incorporated in H-MOEA to improve the convergence ability of the algorithm. Experiment results on several well-known benchmark instances demonstrate the efficiency and stability of the proposed algorithm. The comparison with other recently published approaches validates that H-MOEA can obtain Pareto-optimal solutions with better quality and/or diversity.

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

Science.gov (United States)

Zelinski, Shannon; Windhorst, Robert

2016-01-01

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

Minimizing tardiness for job shop scheduling under uncertainties

OpenAIRE

Yahouni , Zakaria; Mebarki , Nasser; Sari , Zaki

2016-01-01

International audience; —Many disturbances can occur during the execution of a manufacturing scheduling process. To cope with this drawback , flexible solutions are proposed based on the offline and the online phase of the schedule. Groups of permutable operations is one of the most studied flexible scheduling methods bringing flexibility as well as quality to a schedule. The online phase of this method is based on a human-machine system allowing to choose in real-time one schedule from a set...

FLOWSHOP SCHEDULING USING A NETWORK APPROACH ...

African Journals Online (AJOL)

eobe

time when the last job completes on the last machine. The objective ... more jobs in a permutation flow shop scheduling problem ... processing time of a job on a machine is zero, it ..... hybrid flow shops with sequence dependent setup times ...

Finding Worst-Case Flexible Schedules using Coevolution

DEFF Research Database (Denmark)

Jensen, Mikkel Thomas

2001-01-01

Finding flexible schedules is important to industry, since in many environments changes such as machine breakdowns or the appearance of new jobs can happen at short notice.......Finding flexible schedules is important to industry, since in many environments changes such as machine breakdowns or the appearance of new jobs can happen at short notice....

Fatigue Risk Management: The Impact of Anesthesiology Residents' Work Schedules on Job Performance and a Review of Potential Countermeasures.

Science.gov (United States)

Wong, Lily R; Flynn-Evans, Erin; Ruskin, Keith J

2018-04-01

Long duty periods and overnight call shifts impair physicians' performance on measures of vigilance, psychomotor functioning, alertness, and mood. Anesthesiology residents typically work between 64 and 70 hours per week and are often required to work 24 hours or overnight shifts, sometimes taking call every third night. Mitigating the effects of sleep loss, circadian misalignment, and sleep inertia requires an understanding of the relationship among work schedules, fatigue, and job performance. This article reviews the current Accreditation Council for Graduate Medical Education guidelines for resident duty hours, examines how anesthesiologists' work schedules can affect job performance, and discusses the ramifications of overnight and prolonged duty hours on patient safety and resident well-being. We then propose countermeasures that have been implemented to mitigate the effects of fatigue and describe how training programs or practice groups who must work overnight can adapt these strategies for use in a hospital setting. Countermeasures include the use of scheduling interventions, strategic naps, microbreaks, caffeine use during overnight and extended shifts, and the use of bright lights in the clinical setting when possible or personal blue light devices when the room lights must be turned off. Although this review focuses primarily on anesthesiology residents in training, many of the mitigation strategies described here can be used effectively by physicians in practice.

Split scheduling with uniform setup times.

NARCIS (Netherlands)

F. Schalekamp; R.A. Sitters (René); S.L. van der Ster; L. Stougie (Leen); V. Verdugo; A. van Zuylen

2015-01-01

htmlabstractWe study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a

REPAIR SHOP JOB SCHEDULING WITH PARALLEL OPERATORS AND MULTIPLE CONSTRAINTS USING SIMULATED ANNEALING

Directory of Open Access Journals (Sweden)

N. Shivasankaran

2013-04-01

Full Text Available Scheduling problems are generally treated as NP andash; complete combinatorial optimization problems which is a multi-objective and multi constraint one. Repair shop Job sequencing and operator allocation is one such NP andash; complete problem. For such problems, an efficient technique is required that explores a wide range of solution space. This paper deals with Simulated Annealing Technique, a Meta - heuristic to solve the complex Car Sequencing and Operator Allocation problem in a car repair shop. The algorithm is tested with several constraint settings and the solution quality exceeds the results reported in the literature with high convergence speed and accuracy. This algorithm could be considered as quite effective while other heuristic routine fails.

Split Scheduling with Uniform Setup Times

NARCIS (Netherlands)

Schalekamp, F.; Sitters, R.A.; van der Ster, S.L.; Stougie, L.; Verdugo, V.; van Zuylen, A.

2015-01-01

We study a scheduling problem in which jobs may be split into parts, where the parts of a split job may be processed simultaneously on more than one machine. Each part of a job requires a setup time, however, on the machine where the job part is processed. During setup, a machine cannot process or

Collectives for Multiple Resource Job Scheduling Across Heterogeneous Servers

Science.gov (United States)

Tumer, K.; Lawson, J.

2003-01-01

Efficient management of large-scale, distributed data storage and processing systems is a major challenge for many computational applications. Many of these systems are characterized by multi-resource tasks processed across a heterogeneous network. Conventional approaches, such as load balancing, work well for centralized, single resource problems, but breakdown in the more general case. In addition, most approaches are often based on heuristics which do not directly attempt to optimize the world utility. In this paper, we propose an agent based control system using the theory of collectives. We configure the servers of our network with agents who make local job scheduling decisions. These decisions are based on local goals which are constructed to be aligned with the objective of optimizing the overall efficiency of the system. We demonstrate that multi-agent systems in which all the agents attempt to optimize the same global utility function (team game) only marginally outperform conventional load balancing. On the other hand, agents configured using collectives outperform both team games and load balancing (by up to four times for the latter), despite their distributed nature and their limited access to information.

The local–global conjecture for scheduling with non-linear cost

NARCIS (Netherlands)

Bansal, N.; Dürr, C.; Thang, N.K.K.; Vásquez, Ó.C.

2017-01-01

We consider the classical scheduling problem on a single machine, on which we need to schedule sequentially n given jobs. Every job j has a processing time pj and a priority weight wj, and for a given schedule a completion time Cj. In this paper, we consider the problem of minimizing the objective

Multiobjective Joint Optimization of Production Scheduling and Maintenance Planning in the Flexible Job-Shop Problem

Directory of Open Access Journals (Sweden)

Jianfei Ye

2015-01-01

Full Text Available In order to solve the joint optimization of production scheduling and maintenance planning problem in the flexible job-shop, a multiobjective joint optimization model considering the maximum completion time and maintenance costs per unit time is established based on the concept of flexible job-shop and preventive maintenance. A weighted sum method is adopted to eliminate the index dimension. In addition, a double-coded genetic algorithm is designed according to the problem characteristics. The best result under the circumstances of joint decision-making is obtained through multiple simulation experiments, which proves the validity of the algorithm. We can prove the superiority of joint optimization model by comparing the result of joint decision-making project with the result of independent decision-making project under fixed preventive maintenance period. This study will enrich and expand the theoretical framework and analytical methods of this problem; it provides a scientific decision analysis method for enterprise to make production plan and maintenance plan.

Integrating rolling stock scheduling with train unit shunting

DEFF Research Database (Denmark)

Haahr, Jørgen Thorlund; Lusby, Richard Martin

2017-01-01

In this paper, we consider integrating two important railway optimization problems, in particular the Rolling Stock Scheduling Problem and the Train Unit Shunting Problem. We present two similar branch-and-cut based approaches to solve this integrated problem and, in addition, provide a comparison......, sequential approach ends in infeasibility. Furthermore, for the considered instances, solutions are typically found within a few minutes, indicating the applicability of the methodology to short-term planning....

Applying fuzzy integral for evaluating intensity of knowledge work in jobs

Directory of Open Access Journals (Sweden)

Jalil Heidary Dahooie

2013-10-01

Full Text Available In this article, a framework is proposed to define and identify knowledge work intensity in jobs, quantitatively. For determining the Knowledge Work Intensity Score (KWIS of a job, it is supposed that the job comprises some tasks and KWIS of the job is determined based on knowledge intensity of these tasks. Functional Job Analysis (FJA method is applied to determine tasks of jobs and then Task’s Knowledge Intensity Score (TKIS is computed by using Fuzzy integral method. Besides, importance weight and time weight of tasks are determined by utilizing appropriate methods. Finally, KWIS is calculated by a formula composed of tasks’ TKISs and the weights. For evaluating applicability of the framework, it is applied to calculate KWISs of two jobs (Deputy of Finance and service, Laboratory technician.

Job system generation in grid taking into account user preferences

Directory of Open Access Journals (Sweden)

D. M. Yemelyanov

2016-01-01

Full Text Available Distributed computing environments like Grid are characterized by heterogeneity, low cohesion and dynamic structure of computing nodes. This is why the task of resource scheduling in such environments is complex. Different approaches to job scheduling in grid exist. Some of them use economic principles. Economic approaches to scheduling have shown their efficiency. One of such approaches is cyclic scheduling scheme which is considered in this paper.Cyclic scheduling scheme takes into account the preferences of computing environment users by means of an optimization criterion, which is included in the resource request. Besides, the scheme works cyclically by scheduling a certain job batch at each scheduling step. This is why there is a preliminary scheduling step which is job batch generation.The purpose of this study was to estimate the infl uence of job batch structure by the user criterion on the degree of its satisfaction. In other words we had to find the best way to form the batch with relation to the user optimization criterion. For example if it is more efficient to form the batch with jobs with the same criterion value or with different criterion values. Also we wanted to find the combination of criterion values which would give the most efficient scheduling results.To achieve this purpose an experiment in a simulation environment was conducted. The experiment consisted of scheduling of job batches with different values of the user criterion, other parameters of the resource request and the characteristics of the computing environment being the same. Three job batch generation strategies were considered. In the first strategy the batch consisted of jobs with the same criterion value. In the second strategy the batch consisted of jobs with all the considered criteria equally likely. The third strategy was similar to the second one, but only two certain criteria were considered. The third strategy was considered in order to find the most

Optimal Grid Scheduling Using Improved Artificial Bee Colony Algorithm

OpenAIRE

T. Vigneswari; M. A. Maluk Mohamed

2015-01-01

Job Scheduling plays an important role for efficient utilization of grid resources available across different domains and geographical zones. Scheduling of jobs is challenging and NPcomplete. Evolutionary / Swarm Intelligence algorithms have been extensively used to address the NP problem in grid scheduling. Artificial Bee Colony (ABC) has been proposed for optimization problems based on foraging behaviour of bees. This work proposes a modified ABC algorithm, Cluster Hete...

Multiple-Machine Scheduling with Learning Effects and Cooperative Games

Directory of Open Access Journals (Sweden)

Yiyuan Zhou

2015-01-01

Full Text Available Multiple-machine scheduling problems with position-based learning effects are studied in this paper. There is an initial schedule in this scheduling problem. The optimal schedule minimizes the sum of the weighted completion times; the difference between the initial total weighted completion time and the minimal total weighted completion time is the cost savings. A multiple-machine sequencing game is introduced to allocate the cost savings. The game is balanced if the normal processing times of jobs that are on the same machine are equal and an equal number of jobs are scheduled on each machine initially.

PENGEMBANGAN ALGORITMA PENJADUALAN PRODUKSI JOB SHOP UNTUK MEMINIMUMKAN TOTAL BIAYA EARLINESS DAN TARDINESS

Directory of Open Access Journals (Sweden)

Dian Retno Sari Dewi

2005-12-01

Full Text Available This paper develops job shop production scheduling using Non Delay algorithm through forward and backward-forward algorithm to minimize total earliness and tardiness costs. Backward approach has some disadvantages, such as, if the job is scheduled in backward, there is a possibility that the infeasible situation occurs, in which the job is scheduled at t<0. This paper used hypothetic data generated randomly. This job shop scheduling algorithm development was validated using LINDO software to check the effectiveness heuristic method, compared with the optimation method. The validation proves that the result of backward-forward scheduling method is better than the result of forward scheduling method.

Three hybridization models based on local search scheme for job shop scheduling problem

Science.gov (United States)

Balbi Fraga, Tatiana

2015-05-01

This work presents three different hybridization models based on the general schema of Local Search Heuristics, named Hybrid Successive Application, Hybrid Neighborhood, and Hybrid Improved Neighborhood. Despite similar approaches might have already been presented in the literature in other contexts, in this work these models are applied to analyzes the solution of the job shop scheduling problem, with the heuristics Taboo Search and Particle Swarm Optimization. Besides, we investigate some aspects that must be considered in order to achieve better solutions than those obtained by the original heuristics. The results demonstrate that the algorithms derived from these three hybrid models are more robust than the original algorithms and able to get better results than those found by the single Taboo Search.

Stochastic scheduling on unrelated machines

NARCIS (Netherlands)

Skutella, Martin; Sviridenko, Maxim; Uetz, Marc Jochen

2013-01-01

Two important characteristics encountered in many real-world scheduling problems are heterogeneous machines/processors and a certain degree of uncertainty about the actual sizes of jobs. The first characteristic entails machine dependent processing times of jobs and is captured by the classical

An FMS Dynamic Production Scheduling Algorithm Considering Cutting Tool Failure and Cutting Tool Life

International Nuclear Information System (INIS)

Setiawan, A; Wangsaputra, R; Halim, A H; Martawirya, Y Y

2016-01-01

This paper deals with Flexible Manufacturing System (FMS) production rescheduling due to unavailability of cutting tools caused either of cutting tool failure or life time limit. The FMS consists of parallel identical machines integrated with an automatic material handling system and it runs fully automatically. Each machine has a same cutting tool configuration that consists of different geometrical cutting tool types on each tool magazine. The job usually takes two stages. Each stage has sequential operations allocated to machines considering the cutting tool life. In the real situation, the cutting tool can fail before the cutting tool life is reached. The objective in this paper is to develop a dynamic scheduling algorithm when a cutting tool is broken during unmanned and a rescheduling needed. The algorithm consists of four steps. The first step is generating initial schedule, the second step is determination the cutting tool failure time, the third step is determination of system status at cutting tool failure time and the fourth step is the rescheduling for unfinished jobs. The approaches to solve the problem are complete-reactive scheduling and robust-proactive scheduling. The new schedules result differences starting time and completion time of each operations from the initial schedule. (paper)

Safe and healthy integration into semiskilled jobs: does gender matter?

Science.gov (United States)

Laberge, Marie; Vézina, Nicole; Saint-Charles, Johanne

2012-01-01

Women report fewer injuries than men when they are young, but report a higher proportion of professional diseases later in life (35 years +). Understanding early work conditions that lead to postponed health outcomes is necessary if we are to prevent women's injury as well as men's. Introduction to work and safe integration programs are often put forward to prevent injuries among youth. This paper aims to illustrate some differences in the job introduction / integration process for men and women and to discuss some gender-based Occupational Health and Safety (OHS) implications. Data come from two waves of interviews with 31 students enrolled in vocational training for a semiskilled trade. Results demonstrated differences between men and women: trades chosen, OHS complaints, supervising patterns, integration to work, etc. Women often choose customer service jobs, have less formal supervision and are often left to themselves when learning to do their job. Men declared more accidents while women reported more musculoskeletal symptoms. Findings from this research suggest young women's OHS issues should not be trivialized and that specific youth prevention programs for sectors where women are more present, such as customer service, should be developed.

How useful are preemptive schedules?

NARCIS (Netherlands)

Brucker, P.; Heitmann, S.; Hurink, J.L.

2001-01-01

Machine scheduling admits two options to process jobs. In a preemptive mode processing may be interrupted and resumed later even on a different machine. In a nonpreemptive mode interruptions are not allowed. Usually, the possibility to preempt jobs leads to better performance values. However, also

Multi-core processing and scheduling performance in CMS

International Nuclear Information System (INIS)

Hernández, J M; Evans, D; Foulkes, S

2012-01-01

Commodity hardware is going many-core. We might soon not be able to satisfy the job memory needs per core in the current single-core processing model in High Energy Physics. In addition, an ever increasing number of independent and incoherent jobs running on the same physical hardware not sharing resources might significantly affect processing performance. It will be essential to effectively utilize the multi-core architecture. CMS has incorporated support for multi-core processing in the event processing framework and the workload management system. Multi-core processing jobs share common data in memory, such us the code libraries, detector geometry and conditions data, resulting in a much lower memory usage than standard single-core independent jobs. Exploiting this new processing model requires a new model in computing resource allocation, departing from the standard single-core allocation for a job. The experiment job management system needs to have control over a larger quantum of resource since multi-core aware jobs require the scheduling of multiples cores simultaneously. CMS is exploring the approach of using whole nodes as unit in the workload management system where all cores of a node are allocated to a multi-core job. Whole-node scheduling allows for optimization of the data/workflow management (e.g. I/O caching, local merging) but efficient utilization of all scheduled cores is challenging. Dedicated whole-node queues have been setup at all Tier-1 centers for exploring multi-core processing workflows in CMS. We present the evaluation of the performance scheduling and executing multi-core workflows in whole-node queues compared to the standard single-core processing workflows.

Approximating Preemptive Stochastic Scheduling

OpenAIRE

Megow Nicole; Vredeveld Tjark

2009-01-01

We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...

An Integrated Constraint Programming Approach to Scheduling Sports Leagues with Divisional and Round-robin Tournaments

Energy Technology Data Exchange (ETDEWEB)

Carlsson, Mats; Johansson, Mikael; Larson, Jeffrey

2014-01-01

Previous approaches for scheduling a league with round-robin and divisional tournaments involved decomposing the problem into easier subproblems. This approach, used to schedule the top Swedish handball league Elitserien, reduces the problem complexity but can result in suboptimal schedules. This paper presents an integrated constraint programming model that allows to perform the scheduling in a single step. Particular attention is given to identifying implied and symmetry-breaking constraints that reduce the computational complexity significantly. The experimental evaluation of the integrated approach takes considerably less computational effort than the previous approach.

Duality-based algorithms for scheduling on unrelated parallel machines

NARCIS (Netherlands)

van de Velde, S.L.; van de Velde, S.L.

1993-01-01

We consider the following parallel machine scheduling problem. Each of n independent jobs has to be scheduled on one of m unrelated parallel machines. The processing of job J[sub l] on machine Mi requires an uninterrupted period of positive length p[sub lj]. The objective is to find an assignment of

Generic Formal Framework for Compositional Analysis of Hierarchical Scheduling Systems

DEFF Research Database (Denmark)

Boudjadar, Jalil; Hyun Kim, Jin; Thi Xuan Phan, Linh

We present a compositional framework for the specification and analysis of hierarchical scheduling systems (HSS). Firstly we provide a generic formal model, which can be used to describe any type of scheduling system. The concept of Job automata is introduced in order to model job instantiation...

MaGate Simulator: A Simulation Environment for a Decentralized Grid Scheduler

Science.gov (United States)

Huang, Ye; Brocco, Amos; Courant, Michele; Hirsbrunner, Beat; Kuonen, Pierre

This paper presents a simulator for of a decentralized modular grid scheduler named MaGate. MaGate’s design emphasizes scheduler interoperability by providing intelligent scheduling serving the grid community as a whole. Each MaGate scheduler instance is able to deal with dynamic scheduling conditions, with continuously arriving grid jobs. Received jobs are either allocated on local resources, or delegated to other MaGates for remote execution. The proposed MaGate simulator is based on GridSim toolkit and Alea simulator, and abstracts the features and behaviors of complex fundamental grid elements, such as grid jobs, grid resources, and grid users. Simulation of scheduling tasks is supported by a grid network overlay simulator executing distributed ant-based swarm intelligence algorithms to provide services such as group communication and resource discovery. For evaluation, a comparison of behaviors of different collaborative policies among a community of MaGates is provided. Results support the use of the proposed approach as a functional ready grid scheduler simulator.

Work-related factors, job satisfaction and intent to leave the current job among United States nurses.

Science.gov (United States)

Han, Kihye; Trinkoff, Alison M; Gurses, Ayse P

2015-11-01

To examine the relationships of work-related factors (e.g., autonomy, work schedule, supervisory and peer support) to nurses' job satisfaction and intent to leave their current position. Low job satisfaction and high turnover of nurses are major problems for health care. To improve nurse retention, work-related factors associated with job satisfaction and intent to leave should be investigated. A cross-sectional secondary data analysis. Data were obtained in 2004 from Wave 3 of the Nurses' Worklife and Health Study. A random sample of 5000 actively licenced nurses in Illinois and North Carolina (two U.S. states) were sent the survey in wave 1, of which 1641 actively working bedside nurses participated in wave 3. We examined associations of various work-related factors with job satisfaction and intent to leave the current position. Nurses who were dissatisfied with their job reported significantly higher psychological demands and lower autonomy than nurses who were satisfied. Nurses were significantly less satisfied with their jobs when they worked longer hours with inadequate breaks or sick days. Lack of support from peers and supervisors was also related to significantly lower odds of job satisfaction. For intention to leave, nurses who said they planned to leave their current job reported significantly lower autonomy and less support from their peers than nurses who intended to stay. A variety of modifiable work-related factors were significantly related to job satisfaction and intention to leave the current job among nurses. Future research should focus on developing interventions that could mitigate these factors (e.g., by improving work schedules, increasing autonomy and/or nurse support). The impact of such interventions on job satisfaction and intention to leave the current position could then be evaluated. To increase nurse retention, improved schedules, autonomy and supportive work environments should be promoted. © 2015 John Wiley & Sons Ltd.

Coordinating space telescope operations in an integrated planning and scheduling architecture

Science.gov (United States)

Muscettola, Nicola; Smith, Stephen F.; Cesta, Amedeo; D'Aloisi, Daniela

1992-01-01

The Heuristic Scheduling Testbed System (HSTS), a software architecture for integrated planning and scheduling, is discussed. The architecture has been applied to the problem of generating observation schedules for the Hubble Space Telescope. This problem is representative of the class of problems that can be addressed: their complexity lies in the interaction of resource allocation and auxiliary task expansion. The architecture deals with this interaction by viewing planning and scheduling as two complementary aspects of the more general process of constructing behaviors of a dynamical system. The principal components of the software architecture are described, indicating how to model the structure and dynamics of a system, how to represent schedules at multiple levels of abstraction in the temporal database, and how the problem solving machinery operates. A scheduler for the detailed management of Hubble Space Telescope operations that has been developed within HSTS is described. Experimental performance results are given that indicate the utility and practicality of the approach.

Interactive Anticipatory Scheduling for Two Military Applications

National Research Council Canada - National Science Library

Howe, Adele

2003-01-01

...; these models partially explain what makes some job shop scheduling problems difficult. For the second, several algorithms for Air Force Satellite Control Network scheduling have been compared on historical and recent data...

The Costs of Today's Jobs: Job Characteristics and Organizational Supports as Antecedents of Negative Spillover

Science.gov (United States)

Grotto, Angela R.; Lyness, Karen S.

2010-01-01

This study examined job characteristics and organizational supports as antecedents of negative work-to-nonwork spillover for 1178 U.S. employees. Based on hierarchical regression analyses of 2002 National Study of the Changing Workforce data and O*NET data, job demands (requirements to work at home beyond scheduled hours, job complexity, time and…

Gain Scheduling of Observer-Based Controllers with Integral Action

DEFF Research Database (Denmark)

Trangbæk, Klaus; Stoustrup, Jakob; Bendtsen, Jan Dimon

2006-01-01

 This paper presents a method for continuous gain scheduling of  observer-based controllers with integral action. Given two stabilising controllers for a given system, explicit state space formulae are presented, allowing to change gradually from one  controller to the other while preserving...

Apprenticeship Learning: Learning to Schedule from Human Experts

Science.gov (United States)

2016-06-09

identified by the heuristic . A spectrum of problems (i.e. traveling salesman, job-shop scheduling, multi-vehicle routing) was represented , as task locations...caus- ing the codification of this knowledge to become labori- ous. We propose a new approach for capturing domain- expert heuristics through a...demonstrate that this approach accu- rately learns multi-faceted heuristics on both a synthetic data set incorporating job-shop scheduling and vehicle

Job shop scheduling by simulated annealing

NARCIS (Netherlands)

Laarhoven, van P.J.M.; Aarts, E.H.L.; Lenstra, J.K.

1992-01-01

We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems. The generalization involves the acceptance of

Dynamic scheduling and analysis of real time systems with multiprocessors

Directory of Open Access Journals (Sweden)

M.D. Nashid Anjum

2016-08-01

Full Text Available This research work considers a scenario of cloud computing job-shop scheduling problems. We consider m realtime jobs with various lengths and n machines with different computational speeds and costs. Each job has a deadline to be met, and the profit of processing a packet of a job differs from other jobs. Moreover, considered deadlines are either hard or soft and a penalty is applied if a deadline is missed where the penalty is considered as an exponential function of time. The scheduling problem has been formulated as a mixed integer non-linear programming problem whose objective is to maximize net-profit. The formulated problem is computationally hard and not solvable in deterministic polynomial time. This research work proposes an algorithm named the Tube-tap algorithm as a solution to this scheduling optimization problem. Extensive simulation shows that the proposed algorithm outperforms existing solutions in terms of maximizing net-profit and preserving deadlines.

A meta-heuristic method for solving scheduling problem: crow search algorithm

Science.gov (United States)

Adhi, Antono; Santosa, Budi; Siswanto, Nurhadi

2018-04-01

Scheduling is one of the most important processes in an industry both in manufacturingand services. The scheduling process is the process of selecting resources to perform an operation on tasks. Resources can be machines, peoples, tasks, jobs or operations.. The selection of optimum sequence of jobs from a permutation is an essential issue in every research in scheduling problem. Optimum sequence becomes optimum solution to resolve scheduling problem. Scheduling problem becomes NP-hard problem since the number of job in the sequence is more than normal number can be processed by exact algorithm. In order to obtain optimum results, it needs a method with capability to solve complex scheduling problems in an acceptable time. Meta-heuristic is a method usually used to solve scheduling problem. The recently published method called Crow Search Algorithm (CSA) is adopted in this research to solve scheduling problem. CSA is an evolutionary meta-heuristic method which is based on the behavior in flocks of crow. The calculation result of CSA for solving scheduling problem is compared with other algorithms. From the comparison, it is found that CSA has better performance in term of optimum solution and time calculation than other algorithms.

Integrating and scheduling an open set of static analyses

DEFF Research Database (Denmark)

Eichberg, Michael; Mezini, Mira; Kloppenburg, Sven

2006-01-01

to keep the set of analyses open. We propose an approach to integrating and scheduling an open set of static analyses which decouples the individual analyses and coordinates the analysis executions such that the overall time and space consumption is minimized. The approach has been implemented...... for the Eclipse IDE and has been used to integrate a wide range of analyses such as finding bug patterns, detecting violations of design guidelines, or type system extensions for Java....

A Hierarchical Algorithm for Integrated Scheduling and Control With Applications to Power Systems

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Dinesen, Peter Juhler; Jørgensen, John Bagterp

2016-01-01

The contribution of this paper is a hierarchical algorithm for integrated scheduling and control via model predictive control of hybrid systems. The controlled system is a linear system composed of continuous control, state, and output variables. Binary variables occur as scheduling decisions in ...

Multi-core job submission and grid resource scheduling for ATLAS AthenaMP

CERN Document Server

Crooks, D; The ATLAS collaboration; Harrington, R; Purdie, S; Severini, H; Skipsey, S; Tsulaia, V; Washbrook, A

2012-01-01

AthenaMP is the multi-core implementation of the ATLAS software framework and allows the efficient sharing of memory pages between multiple threads of execution. This has now been validated for production and delivers a significant reduction on overall memory footprint with negligible CPU overhead. Before AthenaMP can be routinely run on the LHC Computing Grid, it must be determined how the computing resources available to ATLAS can best exploit the notable improvements delivered by switching to this multi-process model. In particular, there is a need to identify and assess the potential impact of scheduling issues where single core and multi-core job queues have access to the same underlying resources. A study into the effectiveness and scalability of AthenaMP in a production environment will be presented. Submitting AthenaMP tasks to the Tier-0 and candidate Tier-2 sites will allow detailed measurement of worker node performance and also highlight the relative performance of local resource management system...

20 CFR 628.420 - Job training plan.

Science.gov (United States)

2010-04-01

... 20 Employees' Benefits 3 2010-04-01 2010-04-01 false Job training plan. 628.420 Section 628.420... THE JOB TRAINING PARTNERSHIP ACT Local Service Delivery System § 628.420 Job training plan. (a) The Governor shall issue instructions and schedules to assure that job training plans and plan modifications...

Comparing Mixed & Integer Programming vs. Constraint Programming by solving Job-Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Renata Melo e Silva de Oliveira

2015-03-01

Full Text Available Scheduling is a key factor for operations management as well as for business success. From industrial Job-shop Scheduling problems (JSSP, many optimization challenges have emerged since de 1960s when improvements have been continuously required such as bottlenecks allocation, lead-time reductions and reducing response time to requests.  With this in perspective, this work aims to discuss 3 different optimization models for minimizing Makespan. Those 3 models were applied on 17 classical problems of examples JSSP and produced different outputs.  The first model resorts on Mixed and Integer Programming (MIP and it resulted on optimizing 60% of the studied problems. The other models were based on Constraint Programming (CP and approached the problem in two different ways: a model CP1 is a standard IBM algorithm whereof restrictions have an interval structure that fail to solve 53% of the proposed instances, b Model CP-2 approaches the problem with disjunctive constraints and optimized 88% of the instances. In this work, each model is individually analyzed and then compared considering: i Optimization success performance, ii Computational processing time, iii Greatest Resource Utilization and, iv Minimum Work-in-process Inventory. Results demonstrated that CP-2 presented best results on criteria i and ii, but MIP was superior on criteria iii and iv and those findings are discussed at the final section of this work.

Analyzing Integrated Cost-Schedule Risk for Complex Product Systems R&D Projects

Directory of Open Access Journals (Sweden)

Zhe Xu

2014-01-01

Full Text Available The vast majority of the research efforts in project risk management tend to assess cost risk and schedule risk independently. However, project cost and time are related in reality and the relationship between them should be analyzed directly. We propose an integrated cost and schedule risk assessment model for complex product systems R&D projects. Graphical evaluation review technique (GERT, Monte Carlo simulation, and probability distribution theory are utilized to establish the model. In addition, statistical analysis and regression analysis techniques are employed to analyze simulation outputs. Finally, a complex product systems R&D project as an example is modeled by the proposed approach and the simulation outputs are analyzed to illustrate the effectiveness of the risk assessment model. It seems that integrating cost and schedule risk assessment can provide more reliable risk estimation results.

Working atmosphere, job satisfaction and individual characteristics of community mental health professionals in integrated care.

Science.gov (United States)

Goetz, Katja; Kleine-Budde, Katja; Bramesfeld, Anke; Stegbauer, Constance

2018-03-01

Working requirements of community mental healthcare professionals in integrated care are complex. There is a lack of research concerning the relation of job satisfaction, working atmosphere and individual characteristics. For the current study, a survey evaluating job satisfaction and working atmosphere of mental healthcare professionals in integrated care was performed. About 321 community mental healthcare professionals were included in the survey; the response rate was 59.5%. The professional background of community mental healthcare professionals included nursing, social work and psychology. Community mental healthcare professionals reported the highest satisfaction with colleagues and the lowest satisfaction with income. Moreover, it could be shown that more responsibility, more recognition and more variety in job tasks lead to an increase of overall job satisfaction. Healthcare for mentally ill patients in the community setting is complex and requires well-structured care with appropriate responsibilities within the team. A co-operative relationship among colleagues as well as clearly defined responsibilities seem to be the key for the job satisfaction of community mental healthcare professionals in integrated care. © 2017 John Wiley & Sons Ltd.

Flexible Work Schedules. ERIC Digest.

Science.gov (United States)

Kerka, Sandra

Flexible work schedules are one response to changes in the composition of the work force, new life-styles, and changes in work attitudes. Types of alternative work schedules are part-time and temporary employment, job sharing, and flextime. Part-time workers are a diverse group--women, the very young, and older near-retirees. Although part-time…

Perceived Control and Psychological Contract Breach as Explanations of the Relationships Between Job Insecurity, Job Strain and Coping Reactions: Towards a Theoretical Integration.

Science.gov (United States)

Vander Elst, Tinne; De Cuyper, Nele; Baillien, Elfi; Niesen, Wendy; De Witte, Hans

2016-04-01

This study aims to further knowledge on the mechanisms through which job insecurity is related to negative outcomes. Based on appraisal theory, two explanations-perceived control and psychological contract breach-were theoretically integrated in a comprehensive model and simultaneously examined as mediators of the job insecurity-outcome relationship. Different categories of outcomes were considered, namely work-related (i.e. vigour and need for recovery) and general strain (i.e. mental and physical health complaints), as well as psychological (i.e. job satisfaction and organizational commitment) and behavioural coping reactions (i.e. self-rated performance and innovative work behaviour). The hypotheses were tested using data of a heterogeneous sample of 2413 Flemish employees by means of both single and multiple mediator structural equation modelling analyses (bootstrapping method). Particularly, psychological contract breach accounted for the relationship between job insecurity and strain. Both perceived control and psychological contract breach mediated the relationships between job insecurity and psychological coping reactions, although the indirect effects were larger for psychological contract breach. Finally, perceived control was more important than psychological contract breach in mediating the relationships between job insecurity and behavioural coping reactions. This study meets previous calls for a theoretical integration regarding mediators of the job insecurity-outcome relationship. Copyright © 2014 John Wiley & Sons, Ltd.

Disallowing Same-program Co-schedules to Improve Efficiency in Quad-core Servers

OpenAIRE

de Blanche, Andreas; Lundqvist, Thomas

2017-01-01

Programs running on different cores in a multicore server are often forced to share resources like off-chip memory, caches, I/O devices, etc. This resource sharing often leads to degraded performance, a slowdown, for the programs that share the resources. A job scheduler can improve performance by co-scheduling programs that use different resources on the same server. The most common approach to solve this co-scheduling problem has been to make job-schedulers resource aware, finding ways to c...

Bi-Objective Flexible Job-Shop Scheduling Problem Considering Energy Consumption under Stochastic Processing Times.

Science.gov (United States)

Yang, Xin; Zeng, Zhenxiang; Wang, Ruidong; Sun, Xueshan

2016-01-01

This paper presents a novel method on the optimization of bi-objective Flexible Job-shop Scheduling Problem (FJSP) under stochastic processing times. The robust counterpart model and the Non-dominated Sorting Genetic Algorithm II (NSGA-II) are used to solve the bi-objective FJSP with consideration of the completion time and the total energy consumption under stochastic processing times. The case study on GM Corporation verifies that the NSGA-II used in this paper is effective and has advantages to solve the proposed model comparing with HPSO and PSO+SA. The idea and method of the paper can be generalized widely in the manufacturing industry, because it can reduce the energy consumption of the energy-intensive manufacturing enterprise with less investment when the new approach is applied in existing systems.

Integration of Tactical Departure Scheduling and Traffic Flow Management, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — In the ATM Select topic area of Integrated Arrival, Departure and Surface (IADS) planning, this proposal addresses Tactical Departure Scheduling (TDS), which is a...

Perceived leader integrity and employee job satisfaction: A quantitative study of U.S. aerospace engineers

Science.gov (United States)

Harper, Kay E.

The goal of this quantitative study was to determine if there is a significant relationship between perceived leader integrity and employee job satisfaction. The population selected to be analyzed was U.S. Aerospace engineers. Two existing valid and reliable survey instruments were used to collect data. One of the surveys was the Perceived Leader Integrity Scale developed by Craig and Gustafson. The second survey was the Minnesota Satisfaction Questionnaire created by Weiss, Dawis, England, and Lofquist. The public professional networking site LinkedIn was used to invite U.S. Aerospace engineers to participate. The survey results were monitored by Survey Monkey and the sample data was analyzed using SPSS software. 184 responses were collected and of those, 96 were incomplete. 91 usable survey responses were left to be analyzed. When the results were plotted on an x-y plot, the data line had a slight negative slope. The plotted data showed a very small negative relationship between perceived leader integrity and employee job satisfaction. This relationship could be interpreted to mean that as perceived leader integrity improved, employee job satisfaction decreased only slightly. One explanation for this result could be that employees focused on their negative feelings about their current job assignment when they did not have to be concerned about the level of integrity with which their leader acted. The findings of this study reinforce the importance of employee's perception of a critical leader quality - integrity. For future research, a longitudinal study utilizing another sampling method other than convenience sampling may better statistically capture the relationship between perceived leader integrity and employee job satisfaction for U.S. aerospace engineers.

Integration of scheduling and discrete event simulation systems to improve production flow planning

Science.gov (United States)

Krenczyk, D.; Paprocka, I.; Kempa, W. M.; Grabowik, C.; Kalinowski, K.

2016-08-01

The increased availability of data and computer-aided technologies such as MRPI/II, ERP and MES system, allowing producers to be more adaptive to market dynamics and to improve production scheduling. Integration of production scheduling and computer modelling, simulation and visualization systems can be useful in the analysis of production system constraints related to the efficiency of manufacturing systems. A integration methodology based on semi-automatic model generation method for eliminating problems associated with complexity of the model and labour-intensive and time-consuming process of simulation model creation is proposed. Data mapping and data transformation techniques for the proposed method have been applied. This approach has been illustrated through examples of practical implementation of the proposed method using KbRS scheduling system and Enterprise Dynamics simulation system.

Baseline development, economic risk, and schedule risk: An integrated approach

International Nuclear Information System (INIS)

Tonkinson, J.A.

1994-01-01

The economic and schedule risks of Environmental Restoration (ER) projects are commonly analyzed toward the end of the baseline development process. Risk analysis is usually performed as the final element of the scheduling or estimating processes for the purpose of establishing cost and schedule contingency. However, there is an opportunity for earlier assessment of risks, during development of the technical scope and Work Breakdown Structure (WBS). Integrating the processes of risk management and baselining provides for early incorporation of feedback regarding schedule and cost risk into the proposed scope of work. Much of the information necessary to perform risk analysis becomes available during development of the technical baseline, as the scope of work and WBS are being defined. The analysis of risk can actually be initiated early on during development of the technical baseline and continue throughout development of the complete project baseline. Indeed, best business practices suggest that information crucial to the success of a project be analyzed and incorporated into project planning as soon as it is available and usable

28 CFR 345.83 - Job safety training.

Science.gov (United States)

2010-07-01

... 28 Judicial Administration 2 2010-07-01 2010-07-01 false Job safety training. 345.83 Section 345... INDUSTRIES (FPI) INMATE WORK PROGRAMS FPI Inmate Training and Scholarship Programs § 345.83 Job safety training. FPI provides inmates with regular job safety training which is developed and scheduled in...

Some extensions of the discrete lotsizing and scheduling problem

NARCIS (Netherlands)

M. Salomon (Marc); L.G. Kroon (Leo); R. Kuik (Roelof); L.N. van Wassenhove (Luk)

1991-01-01

textabstractIn this paper the Discrete Lotsizing and Scheduling Problem (DLSP) is considered. DLSP relates to capacitated lotsizing as well as to job scheduling problems and is concerned with determining a feasible production schedule with minimal total costs in a single-stage manufacturing process.

Optimal Algorithms and a PTAS for Cost-Aware Scheduling

NARCIS (Netherlands)

L. Chen; N. Megow; R. Rischke; L. Stougie (Leen); J. Verschae

2015-01-01

htmlabstractWe consider a natural generalization of classical scheduling problems in which using a time unit for processing a job causes some time-dependent cost which must be paid in addition to the standard scheduling cost. We study the scheduling objectives of minimizing the makespan and the

Occupations at Risk and Organizational Well-Being: An Empirical Test of a Job Insecurity Integrated Model.

Science.gov (United States)

Chirumbolo, Antonio; Urbini, Flavio; Callea, Antonino; Lo Presti, Alessandro; Talamo, Alessandra

2017-01-01

One of the more visible effects of the societal changes is the increased feelings of uncertainty in the workforce. In fact, job insecurity represents a crucial occupational risk factor and a major job stressor that has negative consequences on both organizational well-being and individual health. Many studies have focused on the consequences about the fear and the perception of losing the job as a whole (called quantitative job insecurity), while more recently research has begun to examine more extensively the worries and the perceptions of losing valued job features (called qualitative job insecurity). The vast majority of the studies, however, have investigated the effects of quantitative and qualitative job insecurity separately. In this paper, we proposed the Job Insecurity Integrated Model aimed to examine the effects of quantitative job insecurity and qualitative job insecurity on their short-term and long-term outcomes. This model was empirically tested in two independent studies, hypothesizing that qualitative job insecurity mediated the effects of quantitative job insecurity on different outcomes, such as work engagement and organizational identification (Study 1), and job satisfaction, commitment, psychological stress and turnover intention (Study 2). Study 1 was conducted on 329 employees in private firms, while Study 2 on 278 employees in both public sector and private firms. Results robustly showed that qualitative job insecurity totally mediated the effects of quantitative on all the considered outcomes. By showing that the effects of quantitative job insecurity on its outcomes passed through qualitative job insecurity, the Job Insecurity Integrated Model contributes to clarifying previous findings in job insecurity research and puts forward a framework that could profitably produce new investigations with important theoretical and practical implications.

Occupations at Risk and Organizational Well-Being: An Empirical Test of a Job Insecurity Integrated Model

Science.gov (United States)

Chirumbolo, Antonio; Urbini, Flavio; Callea, Antonino; Lo Presti, Alessandro; Talamo, Alessandra

2017-01-01

One of the more visible effects of the societal changes is the increased feelings of uncertainty in the workforce. In fact, job insecurity represents a crucial occupational risk factor and a major job stressor that has negative consequences on both organizational well-being and individual health. Many studies have focused on the consequences about the fear and the perception of losing the job as a whole (called quantitative job insecurity), while more recently research has begun to examine more extensively the worries and the perceptions of losing valued job features (called qualitative job insecurity). The vast majority of the studies, however, have investigated the effects of quantitative and qualitative job insecurity separately. In this paper, we proposed the Job Insecurity Integrated Model aimed to examine the effects of quantitative job insecurity and qualitative job insecurity on their short-term and long-term outcomes. This model was empirically tested in two independent studies, hypothesizing that qualitative job insecurity mediated the effects of quantitative job insecurity on different outcomes, such as work engagement and organizational identification (Study 1), and job satisfaction, commitment, psychological stress and turnover intention (Study 2). Study 1 was conducted on 329 employees in private firms, while Study 2 on 278 employees in both public sector and private firms. Results robustly showed that qualitative job insecurity totally mediated the effects of quantitative on all the considered outcomes. By showing that the effects of quantitative job insecurity on its outcomes passed through qualitative job insecurity, the Job Insecurity Integrated Model contributes to clarifying previous findings in job insecurity research and puts forward a framework that could profitably produce new investigations with important theoretical and practical implications. PMID:29250013

Occupations at Risk and Organizational Well-Being: An Empirical Test of a Job Insecurity Integrated Model

Directory of Open Access Journals (Sweden)

Antonio Chirumbolo

2017-11-01

Full Text Available One of the more visible effects of the societal changes is the increased feelings of uncertainty in the workforce. In fact, job insecurity represents a crucial occupational risk factor and a major job stressor that has negative consequences on both organizational well-being and individual health. Many studies have focused on the consequences about the fear and the perception of losing the job as a whole (called quantitative job insecurity, while more recently research has begun to examine more extensively the worries and the perceptions of losing valued job features (called qualitative job insecurity. The vast majority of the studies, however, have investigated the effects of quantitative and qualitative job insecurity separately. In this paper, we proposed the Job Insecurity Integrated Model aimed to examine the effects of quantitative job insecurity and qualitative job insecurity on their short-term and long-term outcomes. This model was empirically tested in two independent studies, hypothesizing that qualitative job insecurity mediated the effects of quantitative job insecurity on different outcomes, such as work engagement and organizational identification (Study 1, and job satisfaction, commitment, psychological stress and turnover intention (Study 2. Study 1 was conducted on 329 employees in private firms, while Study 2 on 278 employees in both public sector and private firms. Results robustly showed that qualitative job insecurity totally mediated the effects of quantitative on all the considered outcomes. By showing that the effects of quantitative job insecurity on its outcomes passed through qualitative job insecurity, the Job Insecurity Integrated Model contributes to clarifying previous findings in job insecurity research and puts forward a framework that could profitably produce new investigations with important theoretical and practical implications.

A Three-Stage Optimization Algorithm for the Stochastic Parallel Machine Scheduling Problem with Adjustable Production Rates

Directory of Open Access Journals (Sweden)

Rui Zhang

2013-01-01

Full Text Available We consider a parallel machine scheduling problem with random processing/setup times and adjustable production rates. The objective functions to be minimized consist of two parts; the first part is related with the due date performance (i.e., the tardiness of the jobs, while the second part is related with the setting of machine speeds. Therefore, the decision variables include both the production schedule (sequences of jobs and the production rate of each machine. The optimization process, however, is significantly complicated by the stochastic factors in the manufacturing system. To address the difficulty, a simulation-based three-stage optimization framework is presented in this paper for high-quality robust solutions to the integrated scheduling problem. The first stage (crude optimization is featured by the ordinal optimization theory, the second stage (finer optimization is implemented with a metaheuristic called differential evolution, and the third stage (fine-tuning is characterized by a perturbation-based local search. Finally, computational experiments are conducted to verify the effectiveness of the proposed approach. Sensitivity analysis and practical implications are also discussed.

Time-constrained project scheduling with adjacent resources

NARCIS (Netherlands)

Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.

We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with adjacent resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by

Time-constrained project scheduling with adjacent resources

NARCIS (Netherlands)

Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.

2008-01-01

We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with Adjacent Resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by

Nonstrict vector simulation in multi-operation scheduling

NARCIS (Netherlands)

Sevastianov, S.V.

1995-01-01

We consider several multi??operation scheduling problems with m machines and n jobs??, including fl??ow shop??, open shop,?? assembly line,?? and a few special cases of job shop with the makespan criterion. It is demonstrated that the problems in question can be effi??ciently solved by approximation

An corrigendum on the paper : Solving the job-shop scheduling problem optimally by dynamic programming (Computers and Operations Research 39(12) (2968–2977) (S0305054812000500) (10.1016/j.cor.2012.02.024))

NARCIS (Netherlands)

van Hoorn, Jelke J.; Nogueira, Agustín; Ojea, Ignacio; Gromicho Dos Santos, Joaquim Antonio

2017-01-01

In [1] an algorithm is proposed for solving the job-shop scheduling problem optimally using a dynamic programming strategy. This is, according to our knowledge, the first exact algorithm for the Job Shop problem which is not based on integer linear programming and branch and bound. Despite the

Job training planning and design for process plant operators

International Nuclear Information System (INIS)

Wirstad, J.

1983-01-01

A method is presented by which process plant operators for nuclear power plants are trained in Sweden. It works by a top-down method of systems analysis which can be integrated into the analysis, specification, and design of the process automation system. The training methods can also be adapted to existing automation systems and operating schedules. The author's method is based on the principle that training programs should be based on job requirements, e.g. operator tasks in common, less frequent, and rare operating conditions. Procedures have been tested for the following steps: Job analysis, analysis of knowledge and experience required, analysis of operator training requirements, set-up and organisation of the training programme, achievement control, evaluation of the training programme. (orig./HP) [de

Job training planning and design for process plant operators

Energy Technology Data Exchange (ETDEWEB)

Wirstad, J.

1983-01-01

A method is presented by which process plant operators for nuclear power plants are trained in Sweden. It works by a top-down method of systems analysis which can be integrated into the analysis, specification, and design of the process automation system. The training methods can also be adapted to existing automation systems and operating schedules. The author's method is based on the principle that training programs should be based on job requirements, e.g. operator tasks in common, less frequent, and rare operating conditions. Procedures have been tested for the following steps: Job analysis, analysis of knowledge and experience required, analysis of operator training requirements, set-up and organisation of the training programme, achievement control, evaluation of the training programme.

Multiagent scheduling models and algorithms

CERN Document Server

Agnetis, Alessandro; Gawiejnowicz, Stanisław; Pacciarelli, Dario; Soukhal, Ameur

2014-01-01

This book presents multi-agent scheduling models in which subsets of jobs sharing the same resources are evaluated by different criteria. It discusses complexity results, approximation schemes, heuristics and exact algorithms.

A Local and Global Search Combine Particle Swarm Optimization Algorithm for Job-Shop Scheduling to Minimize Makespan

Directory of Open Access Journals (Sweden)

Zhigang Lian

2010-01-01

Full Text Available The Job-shop scheduling problem (JSSP is a branch of production scheduling, which is among the hardest combinatorial optimization problems. Many different approaches have been applied to optimize JSSP, but for some JSSP even with moderate size cannot be solved to guarantee optimality. The original particle swarm optimization algorithm (OPSOA, generally, is used to solve continuous problems, and rarely to optimize discrete problems such as JSSP. In OPSOA, through research I find that it has a tendency to get stuck in a near optimal solution especially for middle and large size problems. The local and global search combine particle swarm optimization algorithm (LGSCPSOA is used to solve JSSP, where particle-updating mechanism benefits from the searching experience of one particle itself, the best of all particles in the swarm, and the best of particles in neighborhood population. The new coding method is used in LGSCPSOA to optimize JSSP, and it gets all sequences are feasible solutions. Three representative instances are made computational experiment, and simulation shows that the LGSCPSOA is efficacious for JSSP to minimize makespan.

Integration of look-ahead multicast and unicast scheduling for input-queued cell switches

DEFF Research Database (Denmark)

Yu, Hao; Ruepp, Sarah Renée; Berger, Michael Stübert

2012-01-01

This paper presents an integration of multicast and unicast traffic scheduling algorithms for input-queued cell switches. The multi-level round-robin multicast scheduling (ML-RRMS) algorithm with the look-ahead (LA) mechanism provides a highly scalable architecture and is able to reduce the head...... module that filters out the conflicting requests to ensure fairness. Simulation results show that comparing with the scheme using WBA for the multicast scheduling, the scheme proposed in this paper reduces the HOL blocking problem for multicast traffic and provides a significant improvement in terms...

An Extended Genetic Algorithm for Distributed Integration of Fuzzy Process Planning and Scheduling

Directory of Open Access Journals (Sweden)

Shuai Zhang

2016-01-01

Full Text Available The distributed integration of process planning and scheduling (DIPPS aims to simultaneously arrange the two most important manufacturing stages, process planning and scheduling, in a distributed manufacturing environment. Meanwhile, considering its advantage corresponding to actual situation, the triangle fuzzy number (TFN is adopted in DIPPS to represent the machine processing and transportation time. In order to solve this problem and obtain the optimal or near-optimal solution, an extended genetic algorithm (EGA with innovative three-class encoding method, improved crossover, and mutation strategies is proposed. Furthermore, a local enhancement strategy featuring machine replacement and order exchange is also added to strengthen the local search capability on the basic process of genetic algorithm. Through the verification of experiment, EGA achieves satisfactory results all in a very short period of time and demonstrates its powerful performance in dealing with the distributed integration of fuzzy process planning and scheduling (DIFPPS.

Solving a manpower scheduling problem for airline catering using metaheuristics

DEFF Research Database (Denmark)

Ho, Sin C.; Leung, Janny M. Y.

2010-01-01

We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take-off.  Jobs (flights) must...

Scheduling of Power System Cells Integrating Stochastic Power Generation

International Nuclear Information System (INIS)

Costa, L.M.

2008-12-01

Energy supply and climate change are nowadays two of the most outstanding problems which societies have to cope with under a context of increasing energy needs. Public awareness of these problems is driving political willingness to take actions for tackling them in a swift and efficient manner. Such actions mainly focus in increasing energy efficiency, in decreasing dependence on fossil fuels, and in reducing greenhouse gas emissions. In this context, power systems are undergoing important changes in the way they are planned and managed. On the one hand, vertically integrated structures are being replaced by market structures in which power systems are un-bundled. On the other, power systems that once relied on large power generation facilities are witnessing the end of these facilities' life-cycle and, consequently, their decommissioning. The role of distributed energy resources such as wind and solar power generators is becoming increasingly important in this context. However, the large-scale integration of such type of generation presents many challenges due, for instance, to the uncertainty associated to the variability of their production. Nevertheless, advanced forecasting tools may be combined with more controllable elements such as energy storage devices, gas turbines, and controllable loads to form systems that aim to reduce the impacts that may be caused by these uncertainties. This thesis addresses the management under market conditions of these types of systems that act like independent societies and which are herewith named power system cells. From the available literature, a unified view of power system scheduling problems is also proposed as a first step for managing sets of power system cells in a multi-cell management framework. Then, methodologies for performing the optimal day-ahead scheduling of single power system cells are proposed, discussed and evaluated under both a deterministic and a stochastic framework that directly integrates the

Heat integration in multipurpose batch plants using a robust scheduling framework

CSIR Research Space (South Africa)

Seid, ER

2014-07-01

Full Text Available This case study was taken from the petro- chemical plant by Kallrath [46] and used as a benchmark problem in the scheduling environment for multipurpose batch plants. We adapted this case study to incorporate energy integration. The recipe representa- tion...

Mistral Supercomputer Job History Analysis

OpenAIRE

Zasadziński, Michał; Muntés-Mulero, Victor; Solé, Marc; Ludwig, Thomas

2018-01-01

In this technical report, we show insights and results of operational data analysis from petascale supercomputer Mistral, which is ranked as 42nd most powerful in the world as of January 2018. Data sources include hardware monitoring data, job scheduler history, topology, and hardware information. We explore job state sequences, spatial distribution, and electric power patterns.

Operational Excellence through Schedule Optimization and Production Simulation of Application Specific Integrated Circuits.

Energy Technology Data Exchange (ETDEWEB)

Flory, John Andrew [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Padilla, Denise D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gauthier, John H. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Zwerneman, April Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Miller, Steven P [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2016-05-01

Upcoming weapon programs require an aggressive increase in Application Specific Integrated Circuit (ASIC) production at Sandia National Laboratories (SNL). SNL has developed unique modeling and optimization tools that have been instrumental in improving ASIC production productivity and efficiency, identifying optimal operational and tactical execution plans under resource constraints, and providing confidence in successful mission execution. With ten products and unprecedented levels of demand, a single set of shared resources, highly variable processes, and the need for external supplier task synchronization, scheduling is an integral part of successful manufacturing. The scheduler uses an iterative multi-objective genetic algorithm and a multi-dimensional performance evaluator. Schedule feasibility is assessed using a discrete event simulation (DES) that incorporates operational uncertainty, variability, and resource availability. The tools provide rapid scenario assessments and responses to variances in the operational environment, and have been used to inform major equipment investments and workforce planning decisions in multiple SNL facilities.

FLOW-SHOP SCHEDULING WITH MULTIPLE OPERATIONS AND TIME LAGS

NARCIS (Netherlands)

RIEZEBOS, J; GAALMAN, GJC; GUPTA, JND

A scheduling system is proposed and developed for a special type of flow shop. Ln this flow shop there is one machine at each stage. A job may require multiple operations at each stage. The first operation of a job on stage j cannot start until the last operation of the job on stage j - 1 has

Neural nets for job-shop scheduling, will they do the job?

NARCIS (Netherlands)

Rooda, J.E.; Willems, T.M.; Goodwin, G.C.; Evans, R.J.

1993-01-01

A neural net structure has been developed which is capable of solving deterministic jobshop scheduling problems, part of the large class of np-complete problems. The problem was translated in an integer linear-programming format which facilitated translation in an adequate neural net structure. Use

Scheduling in Heterogeneous Grid Environments: The Effects of DataMigration

Energy Technology Data Exchange (ETDEWEB)

Oliker, Leonid; Biswas, Rupak; Shan, Hongzhang; Smith, Warren

2004-01-01

Computational grids have the potential for solving large-scale scientific problems using heterogeneous and geographically distributed resources. However, a number of major technical hurdles must be overcome before this goal can be fully realized. One problem critical to the effective utilization of computational grids is efficient job scheduling. Our prior work addressed this challenge by defining a grid scheduling architecture and several job migration strategies. The focus of this study is to explore the impact of data migration under a variety of demanding grid conditions. We evaluate our grid scheduling algorithms by simulating compute servers, various groupings of servers into sites, and inter-server networks, using real workloads obtained from leading supercomputing centers. Several key performance metrics are used to compare the behavior of our algorithms against reference local and centralized scheduling schemes. Results show the tremendous benefits of grid scheduling, even in the presence of input/output data migration - while highlighting the importance of utilizing communication-aware scheduling schemes.

A Market-Based Approach to Multi-factory Scheduling

Science.gov (United States)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

Active Job Monitoring in Pilots

Science.gov (United States)

Kuehn, Eileen; Fischer, Max; Giffels, Manuel; Jung, Christopher; Petzold, Andreas

2015-12-01

Recent developments in high energy physics (HEP) including multi-core jobs and multi-core pilots require data centres to gain a deep understanding of the system to monitor, design, and upgrade computing clusters. Networking is a critical component. Especially the increased usage of data federations, for example in diskless computing centres or as a fallback solution, relies on WAN connectivity and availability. The specific demands of different experiments and communities, but also the need for identification of misbehaving batch jobs, requires an active monitoring. Existing monitoring tools are not capable of measuring fine-grained information at batch job level. This complicates network-aware scheduling and optimisations. In addition, pilots add another layer of abstraction. They behave like batch systems themselves by managing and executing payloads of jobs internally. The number of real jobs being executed is unknown, as the original batch system has no access to internal information about the scheduling process inside the pilots. Therefore, the comparability of jobs and pilots for predicting run-time behaviour or network performance cannot be ensured. Hence, identifying the actual payload is important. At the GridKa Tier 1 centre a specific tool is in use that allows the monitoring of network traffic information at batch job level. This contribution presents the current monitoring approach and discusses recent efforts and importance to identify pilots and their substructures inside the batch system. It will also show how to determine monitoring data of specific jobs from identified pilots. Finally, the approach is evaluated.

Solving a manpower scheduling problem for airline catering using tabu search

DEFF Research Database (Denmark)

Ho, Sin C.; Leung, Janny M. Y.

We study a manpower scheduling problem with job time-windows and job-skills compatibility constraints. This problem is motivated by airline catering operations, whereby airline meals and other supplies are delivered to aircrafts on the tarmac just before the flights take off. Jobs (flights) must...

A multi-group and preemptable scheduling of cloud resource based on HTCondor

Science.gov (United States)

Jiang, Xiaowei; Zou, Jiaheng; Cheng, Yaodong; Shi, Jingyan

2017-10-01

Due to the features of virtual machine-flexibility, easy controlling and various system environments, more and more fields utilize the virtualization technology to construct the distributed system with the virtual resources, also including high energy physics. This paper introduce a method used in high energy physics that supports multiple resource group and preemptable cloud resource scheduling, combining virtual machine with HTCondor (a batch system). It makes resource controlling more flexible and more efficient and makes resource scheduling independent of job scheduling. Firstly, the resources belong to different experiment-groups, and the type of user-groups mapping to resource-groups(same as experiment-group) is one-to-one or many-to-one. In order to make the confused group simply to be managed, we designed the permission controlling component to ensure that the different resource-groups can get the suitable jobs. Secondly, for the purpose of elastically allocating resources for suitable resource-group, it is necessary to schedule resources like scheduling jobs. So this paper designs the cloud resource scheduling to maintain a resource queue and allocate an appropriate amount of virtual resources to the request resource-group. Thirdly, in some kind of situations, because of the resource occupied for a long time, resources need to be preempted. This paper adds the preemption function for the resource scheduling that implement resource preemption based on the group priority. Additionally, the way to preempting is soft that when virtual resources are preempted, jobs will not be killed but also be held and rematched later. It is implemented with the help of HTCondor, storing the held job information in scheduler, releasing the job to idle status and doing second matcher. In IHEP (institute of high energy physics), we have built a batch system based on HTCondor with a virtual resources pool based on Openstack. And this paper will show some cases of experiment JUNO

25 CFR 26.22 - May a tribe integrate Job Placement and Training funds into its Public Law 102-477 Plan?

Science.gov (United States)

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false May a tribe integrate Job Placement and Training funds... THE INTERIOR HUMAN SERVICES JOB PLACEMENT AND TRAINING PROGRAM General Applicability § 26.22 May a tribe integrate Job Placement and Training funds into its Public Law 102-477 Plan? Yes, Indian tribes...

Grid Service for User-Centric Job

Energy Technology Data Exchange (ETDEWEB)

Lauret, Jerome

2009-07-31

The User Centric Monitoring (UCM) project was aimed at developing a toolkit that provides the Virtual Organization (VO) with tools to build systems that serve a rich set of intuitive job and application monitoring information to the VO’s scientists so that they can be more productive. The tools help collect and serve the status and error information through a Web interface. The proposed UCM toolkit is composed of a set of library functions, a database schema, and a Web portal that will collect and filter available job monitoring information from various resources and present it to users in a user-centric view rather than and administrative-centric point of view. The goal is to create a set of tools that can be used to augment grid job scheduling systems, meta-schedulers, applications, and script sets in order to provide the UCM information. The system provides various levels of an application programming interface that is useful through out the Grid environment and at the application level for logging messages, which are combined with the other user-centric monitoring information in a abstracted “data store”. A planned monitoring portal will also dynamically present the information to users in their web browser in a secure manor, which is also easily integrated into any JSR-compliant portal deployment that a VO might employ. The UCM is meant to be flexible and modular in the ways that it can be adopted to give the VO many choices to build a solution that works for them with special attention to the smaller VOs that do not have the resources to implement home-grown solutions.

A new mathematical model for single machine batch scheduling problem for minimizing maximum lateness with deteriorating jobs

Directory of Open Access Journals (Sweden)

Ahmad Zeraatkar Moghaddam

2012-01-01

Full Text Available This paper presents a mathematical model for the problem of minimizing the maximum lateness on a single machine when the deteriorated jobs are delivered to each customer in various size batches. In reality, this issue may happen within a supply chain in which delivering goods to customers entails cost. Under such situation, keeping completed jobs to deliver in batches may result in reducing delivery costs. In literature review of batch scheduling, minimizing the maximum lateness is known as NP-Hard problem; therefore the present issue aiming at minimizing the costs of delivering, in addition to the aforementioned objective function, remains an NP-Hard problem. In order to solve the proposed model, a Simulation annealing meta-heuristic is used, where the parameters are calibrated by Taguchi approach and the results are compared to the global optimal values generated by Lingo 10 software. Furthermore, in order to check the efficiency of proposed method to solve larger scales of problem, a lower bound is generated. The results are also analyzed based on the effective factors of the problem. Computational study validates the efficiency and the accuracy of the presented model.

Integrated Cost and Schedule using Monte Carlo Simulation of a CPM Model - 12419

Energy Technology Data Exchange (ETDEWEB)

Hulett, David T. [Hulett and Associates, LLC (United States); Nosbisch, Michael R. [Project Time and Cost, Inc. (United States)

2012-07-01

This discussion of the recommended practice (RP) 57R-09 of AACE International defines the integrated analysis of schedule and cost risk to estimate the appropriate level of cost and schedule contingency reserve on projects. The main contribution of this RP is to include the impact of schedule risk on cost risk and hence on the need for cost contingency reserves. Additional benefits include the prioritizing of the risks to cost, some of which are risks to schedule, so that risk mitigation may be conducted in a cost-effective way, scatter diagrams of time-cost pairs for developing joint targets of time and cost, and probabilistic cash flow which shows cash flow at different levels of certainty. Integrating cost and schedule risk into one analysis based on the project schedule loaded with costed resources from the cost estimate provides both: (1) more accurate cost estimates than if the schedule risk were ignored or incorporated only partially, and (2) illustrates the importance of schedule risk to cost risk when the durations of activities using labor-type (time-dependent) resources are risky. Many activities such as detailed engineering, construction or software development are mainly conducted by people who need to be paid even if their work takes longer than scheduled. Level-of-effort resources, such as the project management team, are extreme examples of time-dependent resources, since if the project duration exceeds its planned duration the cost of these resources will increase over their budgeted amount. The integrated cost-schedule risk analysis is based on: - A high quality CPM schedule with logic tight enough so that it will provide the correct dates and critical paths during simulation automatically without manual intervention. - A contingency-free estimate of project costs that is loaded on the activities of the schedule. - Resolves inconsistencies between cost estimate and schedule that often creep into those documents as project execution proceeds

Job Sharing: An Employment Alternative for the Career Services Professional.

Science.gov (United States)

Johnson, Louise; Meerdink, Lois A.

1985-01-01

Describes and assesses job sharing as an employment alternative for career services professionals. Discusses the job-sharing format with regard to fringe benefits, scheduling, advantages, client reactions, potential problems, and specific factors that contribute to successful job sharing. (BH)

Scheduling permutation flowshops with initial availability constraint: Analysis of solutions and constructive heuristics

OpenAIRE

Pérez González, Paz; Framiñán Torres, José Manuel

2009-01-01

In this paper, we address the problem of scheduling a set of jobs in a flowshop with makespan objective. In contrast to the usual assumption of machine availability presented in most research, we consider that machines may not be available at the beginning of the planning period, due to processing of previously scheduled jobs. We first formulate the problem, analyse the structure of solutions depending on a number of factors (such as machines, jobs, structure of the processing times, availabi...

Scheduling with Learning Effects and/or Time-Dependent Processing Times to Minimize the Weighted Number of Tardy Jobs on a Single Machine

Directory of Open Access Journals (Sweden)

Jianbo Qian

2013-01-01

Full Text Available We consider single machine scheduling problems with learning/deterioration effects and time-dependent processing times, with due date assignment consideration, and our objective is to minimize the weighted number of tardy jobs. By reducing all versions of the problem to an assignment problem, we solve them in O(n4 time. For some important special cases, the time complexity can be improved to be O(n2 using dynamic programming techniques.

Providing Better University Personnel through Job Sharing.

Science.gov (United States)

Hutton, Clifford E.; McFarlin, Joy Simon

1982-01-01

Universities could benefit by offering more flexible part-time job opportunities such as job-sharing, following an apparent national trend in accommodating social and economic needs. Institutions have many options in scheduling and allocating tasks. Possible benefits include improved employee attitude and productivity. (MSE)

Robust and Flexible Scheduling with Evolutionary Computation

DEFF Research Database (Denmark)

Jensen, Mikkel T.

Over the last ten years, there have been numerous applications of evolutionary algorithms to a variety of scheduling problems. Like most other research on heuristic scheduling, the primary aim of the research has been on deterministic formulations of the problems. This is in contrast to real world...... scheduling problems which are usually not deterministic. Usually at the time the schedule is made some information about the problem and processing environment is available, but this information is uncertain and likely to change during schedule execution. Changes frequently encountered in scheduling...... environments include machine breakdowns, uncertain processing times, workers getting sick, materials being delayed and the appearance of new jobs. These possible environmental changes mean that a schedule which was optimal for the information available at the time of scheduling can end up being highly...

Die funksie van Elihu (Job 32-37 in die boek Job

Directory of Open Access Journals (Sweden)

H. Viviers

1995-09-01

Full Text Available The function of Elihu (Job 32-37 in the book of Job. The Elihu speeches (Job 32-37 in the design of the book of Job are usually evaluated either totally redundant or literary fitting and functional. Why were they integrated in the book of Job, without adding anything new or profound? A literary-pragmatic analysis was done on these speeches to detennine their function in Job. The text was analysed narratologically and poetically. This was complemented with insights from reception-criticism ("implied author", "implied reader" and pragmatics (politeness strategies in order to also. read "between the lines". The exigency for the integration of the Elihu speeches in the book of Job seems to be the ironic exposure of the doctrine of retribution.

OL-DEC-MDP Model for Multiagent Online Scheduling with a Time-Dependent Probability of Success

Directory of Open Access Journals (Sweden)

Cheng Zhu

2014-01-01

Full Text Available Focusing on the on-line multiagent scheduling problem, this paper considers the time-dependent probability of success and processing duration and proposes an OL-DEC-MDP (opportunity loss-decentralized Markov Decision Processes model to include opportunity loss into scheduling decision to improve overall performance. The success probability of job processing as well as the process duration is dependent on the time at which the processing is started. The probability of completing the assigned job by an agent would be higher when the process is started earlier, but the opportunity loss could also be high due to the longer engaging duration. As a result, OL-DEC-MDP model introduces a reward function considering the opportunity loss, which is estimated based on the prediction of the upcoming jobs by a sampling method on the job arrival. Heuristic strategies are introduced in computing the best starting time for an incoming job by each agent, and an incoming job will always be scheduled to the agent with the highest reward among all agents with their best starting policies. The simulation experiments show that the OL-DEC-MDP model will improve the overall scheduling performance compared with models not considering opportunity loss in heavy-loading environment.

Non preemptive soft real time scheduler: High deadline meeting rate on overload

Science.gov (United States)

Khalib, Zahereel Ishwar Abdul; Ahmad, R. Badlishah; El-Shaikh, Mohamed

2015-05-01

While preemptive scheduling has gain more attention among researchers, current work in non preemptive scheduling had shown promising result in soft real time jobs scheduling. In this paper we present a non preemptive scheduling algorithm meant for soft real time applications, which is capable of producing better performance during overload while maintaining excellent performance during normal load. The approach taken by this algorithm has shown more promising results compared to other algorithms including its immediate predecessor. We will present the analysis made prior to inception of the algorithm as well as simulation results comparing our algorithm named gutEDF with EDF and gEDF. We are convinced that grouping jobs utilizing pure dynamic parameters would produce better performance.

Highly Accurate Prediction of Jobs Runtime Classes

OpenAIRE

Reiner-Benaim, Anat; Grabarnick, Anna; Shmueli, Edi

2016-01-01

Separating the short jobs from the long is a known technique to improve scheduling performance. In this paper we describe a method we developed for accurately predicting the runtimes classes of the jobs to enable this separation. Our method uses the fact that the runtimes can be represented as a mixture of overlapping Gaussian distributions, in order to train a CART classifier to provide the prediction. The threshold that separates the short jobs from the long jobs is determined during the ev...

GLOA: A New Job Scheduling Algorithm for Grid Computing

Directory of Open Access Journals (Sweden)

Zahra Pooranian

2013-03-01

Full Text Available The purpose of grid computing is to produce a virtual supercomputer by using free resources available through widespread networks such as the Internet. This resource distribution, changes in resource availability, and an unreliable communication infrastructure pose a major challenge for efficient resource allocation. Because of the geographical spread of resources and their distributed management, grid scheduling is considered to be a NP-complete problem. It has been shown that evolutionary algorithms offer good performance for grid scheduling. This article uses a new evaluation (distributed algorithm inspired by the effect of leaders in social groups, the group leaders' optimization algorithm (GLOA, to solve the problem of scheduling independent tasks in a grid computing system. Simulation results comparing GLOA with several other evaluation algorithms show that GLOA produces shorter makespans.

Decentralization and mechanism design for online machine scheduling

NARCIS (Netherlands)

Arge, Lars; Heydenreich, Birgit; Müller, Rudolf; Freivalds, Rusins; Uetz, Marc Jochen

We study the online version of the classical parallel machine scheduling problem to minimize the total weighted completion time from a new perspective: We assume that the data of each job, namely its release date $r_j$, its processing time $p_j$ and its weight $w_j$ is only known to the job itself,

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

OpenAIRE

Bożek Andrzej; Wysocki Marian

2016-01-01

A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also ...

Integrated project scheduling and staff assignment with controllable processing times.

Science.gov (United States)

Fernandez-Viagas, Victor; Framinan, Jose M

2014-01-01

This paper addresses a decision problem related to simultaneously scheduling the tasks in a project and assigning the staff to these tasks, taking into account that a task can be performed only by employees with certain skills, and that the length of each task depends on the number of employees assigned. This type of problems usually appears in service companies, where both tasks scheduling and staff assignment are closely related. An integer programming model for the problem is proposed, together with some extensions to cope with different situations. Additionally, the advantages of the controllable processing times approach are compared with the fixed processing times. Due to the complexity of the integrated model, a simple GRASP algorithm is implemented in order to obtain good, approximate solutions in short computation times.

Integrated Project Scheduling and Staff Assignment with Controllable Processing Times

Directory of Open Access Journals (Sweden)

Victor Fernandez-Viagas

2014-01-01

Full Text Available This paper addresses a decision problem related to simultaneously scheduling the tasks in a project and assigning the staff to these tasks, taking into account that a task can be performed only by employees with certain skills, and that the length of each task depends on the number of employees assigned. This type of problems usually appears in service companies, where both tasks scheduling and staff assignment are closely related. An integer programming model for the problem is proposed, together with some extensions to cope with different situations. Additionally, the advantages of the controllable processing times approach are compared with the fixed processing times. Due to the complexity of the integrated model, a simple GRASP algorithm is implemented in order to obtain good, approximate solutions in short computation times.

TECHNICAL COORDINATION, SCHEDULE AND INTEGRATION

CERN Multimedia

A. Ball

Introduction Since the lowering of YB0 in February, less spectacular but nonetheless crucial progress has been made along the critical path to CMS completion. The YB0 has been aligned with the beamline to a fraction of a mm, and the HCAL has been fully installed. Cabling scaffolding for YB0 services has been built and one half (-z end) of the ECAL barrel has been installed. The YB0 services installation has begun, with two of the major technical challenges delaying bulk installation, namely PP1 detailed design, manufacture and installation plus Tracker cooling pipe insulation, now apparently solved. Significant difficulties in detailed design, integration and procurement of cable ducts remain. Despite this, the design of the +end is close to complete, and Tracker power cable installation on two sectors of the +end is well advanced. A new master schedule, v36.0, is being prepared to account for the updated actual situation at point 5 and for the revised LHC machine planning. Safety The enormous amount of...

An economic lot and delivery scheduling problem with the fuzzy shelf life in a flexible job shop with unrelated parallel machines

Directory of Open Access Journals (Sweden)

S. Dousthaghi

2012-08-01

Full Text Available This paper considers an economic lot and delivery scheduling problem (ELDSP in a fuzzy environment with the fuzzy shelf life for each product. This problem is formulated in a flexible job shop with unrelated parallel machines, when the planning horizon is finite and it determines lot sizing, scheduling and sequencing, simultaneously. The proposed model of this paper is based on the basic period (BP approach. In this paper, a mixed-integer nonlinear programming (MINLP model is presented and then it is changed into two models in the fuzzy shelf life. The main model is dependent to the multiple basic periods and it is difficult to solve the resulted proposed model for large-scale problems in reasonable amount of time; thus, an efficient heuristic method is proposed to solve the problem. The performance of the proposed model is demonstrated using some numerical examples.

Processing time tolerance-based ACO algorithm for solving job-shop scheduling problem

Science.gov (United States)

Luo, Yabo; Waden, Yongo P.

2017-06-01

Ordinarily, Job Shop Scheduling Problem (JSSP) is known as NP-hard problem which has uncertainty and complexity that cannot be handled by a linear method. Thus, currently studies on JSSP are concentrated mainly on applying different methods of improving the heuristics for optimizing the JSSP. However, there still exist many problems for efficient optimization in the JSSP, namely, low efficiency and poor reliability, which can easily trap the optimization process of JSSP into local optima. Therefore, to solve this problem, a study on Ant Colony Optimization (ACO) algorithm combined with constraint handling tactics is carried out in this paper. Further, the problem is subdivided into three parts: (1) Analysis of processing time tolerance-based constraint features in the JSSP which is performed by the constraint satisfying model; (2) Satisfying the constraints by considering the consistency technology and the constraint spreading algorithm in order to improve the performance of ACO algorithm. Hence, the JSSP model based on the improved ACO algorithm is constructed; (3) The effectiveness of the proposed method based on reliability and efficiency is shown through comparative experiments which are performed on benchmark problems. Consequently, the results obtained by the proposed method are better, and the applied technique can be used in optimizing JSSP.

Shift work, mental distress and job satisfaction among Palestinian nurses.

Science.gov (United States)

Jaradat, Y M; Nielsen, M B; Kristensen, P; Bast-Pettersen, R

2017-01-01

Associations between shift work (SW) schedules, mental distress and job satisfaction have never been completely described. To examine gender-specific associations of SW with mental distress and job satisfaction in nurses in Hebron District, Palestine, in 2012. Detailed information on work schedules (day versus shift), socio-demographic status, mental distress (General Health Questionnaire, GHQ-30) and job satisfaction (Generic Job Satisfaction Scale) in nurses employed in Hebron District, Palestine, was obtained through a questionnaire survey. Associations of SW and outcomes were examined by linear regression analysis. Of 372 nurses eligible for the study, 309 and 338 completed surveys regarding mental distress and job satisfaction, respectively. The sample comprised 62% women and 38% men. After adjusting for covariates, women working shifts reported significantly higher levels of mean mental distress [β coefficient 3.6; 95% confidence interval (CI) 0.3-7.0] compared with women working regular day shifts. Men working shifts reported significantly lower levels of job satisfaction (-3.3; 95% CI -6.2 to -0.5) than men working regular day shifts. Women reported higher levels of mental distress than men, but this was unrelated to work schedule. In this study, nurses working shifts reported higher levels of mental distress and lower levels of job satisfaction, although these associations were weaker when adjusted for potential covariates. There was no evidence of a gender differential in the association between SW and mental distress and job satisfaction. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine.

Working Less and Enjoying It More: Alternative Work Schedules.

Science.gov (United States)

Shanks, Katherine

1984-01-01

Explores three forms of alternative work schedules that research has shown improve job performance and decrease absenteeism: flextime (starting and stopping times vary within limits); permanent part-time employment (regular employment carried out during shorter working hours); and job sharing (two or more part-time employees share one full-time…

From Preemptive to Non-preemptive Scheduling Using Rejections

OpenAIRE

Lucarelli , Giorgio; Srivastav , Abhinav; Trystram , Denis

2016-01-01

International audience; We study the classical problem of scheduling a set of independent jobs with release dates on a single machine. There exists a huge literature on the preemptive version of the problem, where the jobs can be interrupted at any moment. However, we focus here on the non-preemptive case, which is harder, but more relevant in practice. For instance, the jobs submitted to actual high performance platforms cannot be interrupted or migrated once they start their execution (due ...

Parallel Machine Scheduling with Batch Delivery to Two Customers

Directory of Open Access Journals (Sweden)

Xueling Zhong

2015-01-01

Full Text Available In some make-to-order supply chains, the manufacturer needs to process and deliver products for customers at different locations. To coordinate production and distribution operations at the detailed scheduling level, we study a parallel machine scheduling model with batch delivery to two customers by vehicle routing method. In this model, the supply chain consists of a processing facility with m parallel machines and two customers. A set of jobs containing n1 jobs from customer 1 and n2 jobs from customer 2 are first processed in the processing facility and then delivered to the customers directly without intermediate inventory. The problem is to find a joint schedule of production and distribution such that the tradeoff between maximum arrival time of the jobs and total distribution cost is minimized. The distribution cost of a delivery shipment consists of a fixed charge and a variable cost proportional to the total distance of the route taken by the shipment. We provide polynomial time heuristics with worst-case performance analysis for the problem. If m=2 and (n1-b(n2-b<0, we propose a heuristic with worst-case ratio bound of 3/2, where b is the capacity of the delivery shipment. Otherwise, the worst-case ratio bound of the heuristic we propose is 2-2/(m+1.

Outsourcing and scheduling for a two-machine flow shop with release times

Science.gov (United States)

Ahmadizar, Fardin; Amiri, Zeinab

2018-03-01

This article addresses a two-machine flow shop scheduling problem where jobs are released intermittently and outsourcing is allowed. The first operations of outsourced jobs are processed by the first subcontractor, they are transported in batches to the second subcontractor for processing their second operations, and finally they are transported back to the manufacturer. The objective is to select a subset of jobs to be outsourced, to schedule both the in-house and the outsourced jobs, and to determine a transportation plan for the outsourced jobs so as to minimize the sum of the makespan and the outsourcing and transportation costs. Two mathematical models of the problem and several necessary optimality conditions are presented. A solution approach is then proposed by incorporating the dominance properties with an ant colony algorithm. Finally, computational experiments are conducted to evaluate the performance of the models and solution approach.

Accelerating customer integration into innovation processes using Pico-Jobs

OpenAIRE

Blohm, Ivo;Fähling, Jens;Leimeister, Jan Marco;Krcmar, Helmut;Fischer, Jan

2014-01-01

Crowdsourcing marketplaces emerged in the internet and enable the integration of customers in various tasks along the innovation process. Marketplaces such as Amazon?s Mechanical Turk install a member base for third parties, where they can offer small, highly structured paid tasks which can hardly be solved automatically with ICT which we call Pico Jobs. In this paper a new method for systematically utilizing the creative potential of the users of these marketplaces for new product developmen...

SPANR planning and scheduling

Science.gov (United States)

Freund, Richard F.; Braun, Tracy D.; Kussow, Matthew; Godfrey, Michael; Koyama, Terry

2001-07-01

SPANR (Schedule, Plan, Assess Networked Resources) is (i) a pre-run, off-line planning and (ii) a runtime, just-in-time scheduling mechanism. It is designed to support primarily commercial applications in that it optimizes throughput rather than individual jobs (unless they have highest priority). Thus it is a tool for a commercial production manager to maximize total work. First the SPANR Planner is presented showing the ability to do predictive 'what-if' planning. It can answer such questions as, (i) what is the overall effect of acquiring new hardware or (ii) what would be the effect of a different scheduler. The ability of the SPANR Planner to formulate in advance tree-trimming strategies is useful in several commercial applications, such as electronic design or pharmaceutical simulations. The SPANR Planner is demonstrated using a variety of benchmarks. The SPANR Runtime Scheduler (RS) is briefly presented. The SPANR RS can provide benefit for several commercial applications, such as airframe design and financial applications. Finally a design is shown whereby SPANR can provide scheduling advice to most resource management systems.

Data Model Approach And Markov Chain Based Analysis Of Multi-Level Queue Scheduling

Directory of Open Access Journals (Sweden)

Diwakar Shukla

2010-01-01

Full Text Available There are many CPU scheduling algorithms inliterature like FIFO, Round Robin, Shortest-Job-First and so on.The Multilevel-Queue-Scheduling is superior to these due to itsbetter management of a variety of processes. In this paper, aMarkov chain model is used for a general setup of Multilevelqueue-scheduling and the scheduler is assumed to performrandom movement on queue over the quantum of time.Performance of scheduling is examined through a rowdependent data model. It is found that with increasing value of αand d, the chance of system going over the waiting state reduces.At some of the interesting combinations of α and d, it diminishesto zero, thereby, provides us some clue regarding better choice ofqueues over others for high priority jobs. It is found that ifqueue priorities are added in the scheduling intelligently thenbetter performance could be obtained. Data model helpschoosing appropriate preferences.

Single machine scheduling with time-dependent linear deterioration and rate-modifying maintenance

OpenAIRE

Rustogi, Kabir; Strusevich, Vitaly A.

2015-01-01

We study single machine scheduling problems with linear time-dependent deterioration effects and maintenance activities. Maintenance periods (MPs) are included into the schedule, so that the machine, that gets worse during the processing, can be restored to a better state. We deal with a job-independent version of the deterioration effects, that is, all jobs share a common deterioration rate. However, we introduce a novel extension to such models and allow the deterioration rates to change af...

Maximizing work integration in job placement of individuals facing mental health problems: Supervisor experiences.

Science.gov (United States)

Skarpaas, Lisebet Skeie; Ramvi, Ellen; Løvereide, Lise; Aas, Randi Wågø

2015-01-01

Many people confronting mental health problems are excluded from participation in paid work. Supervisor engagement is essential for successful job placement. To elicit supervisor perspectives on the challenges involved in fostering integration to support individuals with mental health problems (trainees) in their job placement at ordinary companies. Explorative, qualitative designed study with a phenomenological approach, based on semi-structured interviews with 15 supervisors involved in job placements for a total of 105 trainees (mean 7, min-max. 1-30, SD 8). Data were analysed using qualitative content analysis. Superviors experience two interrelated dilemmas concerning knowledge of the trainee and degree of preferential treatment. Challenges to obtaining successful integration were; motivational: 1) Supervisors previous experience with trainees encourages future engagement, 2) Developing a realistic picture of the situation, and 3) Disclosure and knowledge of mental health problems, and continuity challenges: 4) Sustaining trainee cooperation throughout the placement process, 5) Building and maintaining a good relationship between supervisor and trainee, and 6) Ensuring continuous cooperation with the social security system and other stakeholders. Supervisors experience relational dilemmas regarding pre-judgment, privacy and equality. Job placement seem to be maximized when the stakeholders are motivated and recognize that cooperation must be a continuous process.

Flow-shop scheduling problem under uncertainties: Review and trends

OpenAIRE

Eliana María González-Neira; Jairo R. Montoya-Torres; David Barrera

2017-01-01

Among the different tasks in production logistics, job scheduling is one of the most important at the operational decision-making level to enable organizations to achieve competiveness. Scheduling consists in the allocation of limited resources to activities over time in order to achieve one or more optimization objectives. Flow-shop (FS) scheduling problems encompass the sequencing processes in environments in which the activities or operations are performed in a serial flow. This type of co...

Job sharing in clinical nutrition management: a plan for successful implementation.

Science.gov (United States)

Visocan, B J; Herold, L S; Mulcahy, M J; Schlosser, M F

1993-10-01

While women continue to enter the American work force in record numbers; many experience difficulty in juggling career and family obligations. Flexible scheduling is one option used to ease work and family pressures. Women's changing work roles have potentially noteworthy implications for clinical nutrition management, a traditionally female-dominated profession where the recruitment and retention of valued, experienced registered dietitians can prove to be a human resources challenge. Job sharing, one type of flexible scheduling, is applicable to the nutrition management arena. This article describes and offers a plan for overcoming obstacles to job sharing, including determining feasibility, gaining support of top management, establishing program design, announcing the job share program, and using implementation, monitoring, and fine-tuning strategies. Benefits that can be derived from a successful job share are reduced absenteeism, decreased turnover, enhanced recruitment, improved morale, increased productivity, improved job coverage, and enhanced skills and knowledge base. A case study illustrates one method for achieving job sharing success in clinical nutrition management.

Shift schedules, work factors, and mental health among onshore and offshore workers in the Norwegian petroleum industry

Science.gov (United States)

BERTHELSEN, Mona; PALLESEN, Ståle; BJORVATN, Bjørn; KNARDAHL, Stein

2015-01-01

The purpose of the present study was to answer the following research questions: (1) Do workers in different shift schedules differ in mental distress? (2) Do workers in different shift schedules differ in neuroticism? (3) Do shift schedules differ in psychosocial work exposures? (4) Do psychosocial work exposures contribute to mental distress among onshore- and offshore workers? (5) Does neuroticism confound the association between work exposures and mental distress? Workers on six shift-schedules answered a questionnaire (1,471 of 2,628 employees). Psychological and social work factors were measured by QPSNordic, mental distress was measured by HADS and neuroticism was measured by EPQ. The results showed 1) No differences in mental distress between workers in different shift schedules, 2) Revolving-shift workers reported higher neuroticism compared to day workers, 3) Swing-shift workers and revolving-shift workers reported lower job control compared to permanent-night and -day workers, 4) Job demands and role conflict were associated with more mental distress. Job control, role clarity, support, and leadership were associated with lower mental distress, 5) Neuroticism influenced the relationship between psychosocial work factors and mental distress. The present study did not find differences in mental distress between shift schedules. Job characteristics may be contributing factors when determining health effects of shift work. PMID:25740007

Developing optimal nurses work schedule using integer programming

Science.gov (United States)

Shahidin, Ainon Mardhiyah; Said, Mohd Syazwan Md; Said, Noor Hizwan Mohamad; Sazali, Noor Izatie Amaliena

2017-08-01

Time management is the art of arranging, organizing and scheduling one's time for the purpose of generating more effective work and productivity. Scheduling is the process of deciding how to commit resources between varieties of possible tasks. Thus, it is crucial for every organization to have a good work schedule for their staffs. The job of Ward nurses at hospitals runs for 24 hours every day. Therefore, nurses will be working using shift scheduling. This study is aimed to solve the nurse scheduling problem at an emergency ward of a private hospital. A 7-day work schedule for 7 consecutive weeks satisfying all the constraints set by the hospital will be developed using Integer Programming. The work schedule for the nurses obtained gives an optimal solution where all the constraints are being satisfied successfully.

Scheduling with target start times

NARCIS (Netherlands)

Hoogeveen, J.A.; Velde, van de S.L.; Klein Haneveld, W.K.; Vrieze, O.J.; Kallenberg, L.C.M.

1997-01-01

We address the single-machine problem of scheduling n independent jobs subject to target start times. Target start times are essentially release times that may be violated at a certain cost. The goal is to minimize an objective function that is composed of total completion time and maximum

Integrated Fractional Load and Packet Scheduling for OFDMA Systems

DEFF Research Database (Denmark)

Monghal, Guillaume Damien; Kumar, S.; Pedersen, Klaus I.

2009-01-01

This paper study the performance of an orthogonal frequency division multiple access (OFDMA) system under fractional load based in long term evolution (LTE) downlink. Fractional load is defined by a situation where only a fraction of the bandwidth is used for transmission due to lack of traffic....... This type of situation should result in a global increase of signal to interference and noise ratio (SINR) conditions in the network. We propose different methods integrating the transmission pattern selection to the packet scheduling functionality of the enode-B depending only on the channel quality...

Onboard Autonomous Scheduling Intelligence System, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Scheduling the daily activities of the crew on a human space mission is currently a cumbersome job performed by a large team of operations experts on the ground....

BR-SIPP: PETROBRAS Integrated Scheduling System; BR-SIPP: Sistema Integrado de Progamacao de Producao da PETROBRAS

Energy Technology Data Exchange (ETDEWEB)

Pereira, Cristiane S.; Joly, Marcel; Hassimotto, Marcelo K.; Magalhaes, Marcus Vinicius O. [PETROBRAS S.A., Rio de Janeiro, RJ (Brazil)

2008-07-01

The lack of a computational aided technology to support short-term scheduling activity in the oil and petrochemical sector has been identified as one of the major obstacles to the harmonic integration of production objectives subsequent to the implementation of the advanced control systems and the consolidation of important benefits at the process unit level. Such technology refers to an analytical tool able to capture plant operational information consistent with the scheduling layer demands, modeling the production system economic performance, and providing mechanisms to consider commercial, operation and technological uncertainties. In this context, PETROBRAS has continuously dedicated effort to develop, implement and enhance its own refinery scheduling solution. Nowadays at its second version, the PETROBRAS Integrated Scheduling System (BR-SIPP - INPI grant 00067400) has become the focus of corporate care, given its critical role on the link between planning objectives and plant operations, according to the hierarchical decision strategy currently adopted by PETROBRAS. This paper presents an overview of the tool and illustrates some real-world applications and main realized benefits. (author)

An Integrated Approach to Locality-Conscious Processor Allocation and Scheduling of Mixed-Parallel Applications

Energy Technology Data Exchange (ETDEWEB)

Vydyanathan, Naga; Krishnamoorthy, Sriram; Sabin, Gerald M.; Catalyurek, Umit V.; Kurc, Tahsin; Sadayappan, Ponnuswamy; Saltz, Joel H.

2009-08-01

Complex parallel applications can often be modeled as directed acyclic graphs of coarse-grained application-tasks with dependences. These applications exhibit both task- and data-parallelism, and combining these two (also called mixedparallelism), has been shown to be an effective model for their execution. In this paper, we present an algorithm to compute the appropriate mix of task- and data-parallelism required to minimize the parallel completion time (makespan) of these applications. In other words, our algorithm determines the set of tasks that should be run concurrently and the number of processors to be allocated to each task. The processor allocation and scheduling decisions are made in an integrated manner and are based on several factors such as the structure of the taskgraph, the runtime estimates and scalability characteristics of the tasks and the inter-task data communication volumes. A locality conscious scheduling strategy is used to improve inter-task data reuse. Evaluation through simulations and actual executions of task graphs derived from real applications as well as synthetic graphs shows that our algorithm consistently generates schedules with lower makespan as compared to CPR and CPA, two previously proposed scheduling algorithms. Our algorithm also produces schedules that have lower makespan than pure taskand data-parallel schedules. For task graphs with known optimal schedules or lower bounds on the makespan, our algorithm generates schedules that are closer to the optima than other scheduling approaches.

Using System Architecture, Review Entry Criteria, and Standard Work Package Data to Enable Rapid Development of Integrated Master Schedules

Science.gov (United States)

2016-03-01

critical path, EVM, project management, systems engineering, CVN, obsolescence , integrated master schedule , portfolio schedule 15. NUMBER OF PAGES...after the decision to swap deployments between the CVN-69 and CVN-75. C. COTS OBSOLESCENCE While CVN deadlines impose schedule constraints...Elements The context diagram shows how a CVN IT program SEP and IMS interact with COTS obsolescence , the CPA availability schedule , and other internal

Scheduling by positional completion times: analysis of a two-stage flow shop problem with a batching machine

NARCIS (Netherlands)

Hoogeveen, J.A.; Velde, van de S.L.

1998-01-01

We consider a scheduling problem introduced by Ahmadi et al., Batching and scheduling jobs on batch and discrete processors, Operation Research 40 (1992) 750–763, in which each job has to be prepared before it can be processed. The preparation is performed by a batching machine; it can prepare at

A Single-Machine Two-Agent Scheduling Problem by a Branch-and-Bound and Three Simulated Annealing Algorithms

Directory of Open Access Journals (Sweden)

Shangchia Liu

2015-01-01

Full Text Available In the field of distributed decision making, different agents share a common processing resource, and each agent wants to minimize a cost function depending on its jobs only. These issues arise in different application contexts, including real-time systems, integrated service networks, industrial districts, and telecommunication systems. Motivated by its importance on practical applications, we consider two-agent scheduling on a single machine where the objective is to minimize the total completion time of the jobs of the first agent with the restriction that an upper bound is allowed the total completion time of the jobs for the second agent. For solving the proposed problem, a branch-and-bound and three simulated annealing algorithms are developed for the optimal solution, respectively. In addition, the extensive computational experiments are also conducted to test the performance of the algorithms.

DESIGN OF A HYPERHEURISTIC FOR PRODUCTION SCHEDULING IN JOB SHOP ENVIRONMENTS DISEÑO DE UNA HIPERHEURISTICA PARA LA PROGRAMACION DE LA PRODUCCIÓN EN AMBIENTES JOB SHOP

Directory of Open Access Journals (Sweden)

Omar Danilo Castrillón

2010-08-01

Full Text Available The objective of the present work is to diminish the total process time (Makespan and to increase the machine process time, by diminishing the idle time in a job-shop environment. Through the design of a hyper-heuristic based on an ant colony and genetic algorithms. This work is developed in two phases: in the first phase, a hyper-heuristic identification and definition is carried out for sequencing processes in job shop environments. In the second phase, the system effectiveness in the traditional production programming is shown. In the investigation project, an enterprise from the metal mechanic sector was chosen, where by means of a combination of an ant colony and genetic algorithms, the optimal route for an order is scheduled, achieving the optimization or suboptimization of its respective total process time in an upper percentage of 95%.El objetivo del presente trabajo es disminuir el tiempo de proceso (Makespan e incrementar el tiempo de trabajo de las maquinas, diminuyendo el tiempo de ocio en ambientes de Job Shop, a través del diseño de una Hiper-heurística basada en colonia de hormigas y algoritmos genéticos. Este trabajo se desarrolla en dos etapas: en la primera se realiza la definición e identificación de una Hiper-heurística para la secuenciación de procesos en ambientes Job shop. En la segunda etapa, es mostrada la efectividad del sistema en la programación de la producción. En el proyecto de investigación, se seleccionó una empresa del sector metalmecánico, donde por medio de una combinación de colonia de hormigas y algoritmos genéticos, se programa la ruta óptima para un pedido, logrando la optimización o suboptimización de su respectivo tiempo total de proceso en un porcentaje superior al 95%.

Analyzing data flows of WLCG jobs at batch job level

Science.gov (United States)

Kuehn, Eileen; Fischer, Max; Giffels, Manuel; Jung, Christopher; Petzold, Andreas

2015-05-01

With the introduction of federated data access to the workflows of WLCG, it is becoming increasingly important for data centers to understand specific data flows regarding storage element accesses, firewall configurations, as well as the scheduling of batch jobs themselves. As existing batch system monitoring and related system monitoring tools do not support measurements at batch job level, a new tool has been developed and put into operation at the GridKa Tier 1 center for monitoring continuous data streams and characteristics of WLCG jobs and pilots. Long term measurements and data collection are in progress. These measurements already have been proven to be useful analyzing misbehaviors and various issues. Therefore we aim for an automated, realtime approach for anomaly detection. As a requirement, prototypes for standard workflows have to be examined. Based on measurements of several months, different features of HEP jobs are evaluated regarding their effectiveness for data mining approaches to identify these common workflows. The paper will introduce the actual measurement approach and statistics as well as the general concept and first results classifying different HEP job workflows derived from the measurements at GridKa.

Data analysis with the DIANA meta-scheduling approach

International Nuclear Information System (INIS)

Anjum, A; McClatchey, R; Willers, I

2008-01-01

The concepts, design and evaluation of the Data Intensive and Network Aware (DIANA) meta-scheduling approach for solving the challenges of data analysis being faced by CERN experiments are discussed in this paper. Our results suggest that data analysis can be made robust by employing fault tolerant and decentralized meta-scheduling algorithms supported in our DIANA meta-scheduler. The DIANA meta-scheduler supports data intensive bulk scheduling, is network aware and follows a policy centric meta-scheduling. In this paper, we demonstrate that a decentralized and dynamic meta-scheduling approach is an effective strategy to cope with increasing numbers of users, jobs and datasets. We present 'quality of service' related statistics for physics analysis through the application of a policy centric fair-share scheduling model. The DIANA meta-schedulers create a peer-to-peer hierarchy of schedulers to accomplish resource management that changes with evolving loads and is dynamic and adapts to the volatile nature of the resources

Single machine scheduling with slack due dates assignment

Science.gov (United States)

Liu, Weiguo; Hu, Xiangpei; Wang, Xuyin

2017-04-01

This paper considers a single machine scheduling problem in which each job is assigned an individual due date based on a common flow allowance (i.e. all jobs have slack due date). The goal is to find a sequence for jobs, together with a due date assignment, that minimizes a non-regular criterion comprising the total weighted absolute lateness value and common flow allowance cost, where the weight is a position-dependent weight. In order to solve this problem, an ? time algorithm is proposed. Some extensions of the problem are also shown.

Job stress and job satisfaction among new graduate nurses during the first year of employment in Taiwan.

Science.gov (United States)

Cheng, Ching-Yu; Liou, Shwu-Ru; Tsai, Hsiu-Min; Chang, Chia-Hao

2015-08-01

Nurse graduates are leaving their first employment at an alarming rate. The purpose of this study was to explore the relationships between job stress, job satisfaction and related factors over time among these nurses. This study applied a longitudinal design with three follow-ups after nurse graduates' first employment began. Using convenience sampling, participants were 206 new graduates from a university. The Work Environment Nursing Satisfaction Survey and the Clinical Stress Scale were used in this study. Results indicated that job stress remained moderate across three time points. Participants working 12 h shifts exhibited less job stress. Job satisfaction significantly increased in the twelfth month. Participants working 12 h shifts had a higher degree of job satisfaction. Job stress was negatively correlated with job satisfaction. The 12 h work shifts were related to job stress and job satisfaction. These results implied that health-care administrators need to provide longer orientation periods and flexible shift schedules for new graduate nurses to adapt to their work environment. © 2014 Wiley Publishing Asia Pty Ltd.

The Impact of Job Stress and Job Satisfaction on Workforce Productivity in an Iranian Petrochemical Industry.

Science.gov (United States)

Hoboubi, Naser; Choobineh, Alireza; Kamari Ghanavati, Fatemeh; Keshavarzi, Sareh; Akbar Hosseini, Ali

2017-03-01

Job stress and job satisfaction are important factors affecting workforce productivity. This study was carried out to investigate the job stress, job satisfaction, and workforce productivity levels, to examine the effects of job stress and job satisfaction on workforce productivity, and to identify factors associated with productivity decrement among employees of an Iranian petrochemical industry. In this study, 125 randomly selected employees of an Iranian petrochemical company participated. The data were collected using the demographic questionnaire, Osipow occupational stress questionnaire to investigate the level of job stress, Job Descriptive Index to examine job satisfaction, and Hersey and Goldsmith questionnaire to investigate productivity in the study population. The levels of employees' perceived job stress and job satisfaction were moderate-high and moderate, respectively. Also, their productivity was evaluated as moderate. Although the relationship between job stress and productivity indices was not statistically significant, the positive correlation between job satisfaction and productivity indices was statistically significant. The regression modeling demonstrated that productivity was significantly associated with shift schedule, the second and the third dimensions of job stress (role insufficiency and role ambiguity), and the second dimension of job satisfaction (supervision). Corrective measures are necessary to improve the shift work system. "Role insufficiency" and "role ambiguity" should be improved and supervisor support must be increased to reduce job stress and increase job satisfaction and productivity.

Mix-oriented manufacturing control (MOMC): a quasi-optimal procedure for dynamic scheduling control

Science.gov (United States)

Cristofari, Marco; Caron, Franco; McDuffie, Ernest L.

1997-12-01

The total system throughput (ST) is one of the most important decision variables at the planning/scheduling phase of a manufacturing system. Material requirement planning (MRP) and master production schedule (MPS) are based on the assumption that ST is known. All the subsequent developments (e.g. jobs- release, system work-load, input-product mix, etc.) depends on such an assumption. If this assumption is incorrect, the production activity control (PAC) will not be able to satisfy the planned targets during the scheduling phase. Delays and bottlenecks will be unavoidable in the system. In case of random flexible manufacturing system (FMS) (or, in general, job-shop production), the measure of ST can not be evaluated a priori without running simulations or observing the actual flow of the operations in the system. The way entities enter the system (sequencing and percentage of the input products) effects the value of ST in such a way that estimation based on historical data are highly risky. The methodology proposed in this paper allows the scheduler to assess the analytical functions which link ST, and other output performance variables, to the input product mix (IPM). This way the robustness of the scheduling plan can be verified before the actual release of the jobs into the system.

The Impact of Social Integration Interventions and Job Coaches in Work Settings.

Science.gov (United States)

Chadsey, Janis G.; Linneman, Dan; Rusch, Frank R.; Cimera, Robert E.

1997-01-01

A study investigated effects of two intervention strategies (contextual and coworker) on the social interactions and integration with peers of five workers with mental retardation. Neither intervention had a significant impact on the frequency of interactions; however, it appeared that the presence of a job coach suppressed interaction rates.…

Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system

International Nuclear Information System (INIS)

Logenthiran, T.; Srinivasan, Dipti; Khambadkone, Ashwin M.

2011-01-01

This paper proposes a multi-agent system for energy resource scheduling of an islanded power system with distributed resources, which consists of integrated microgrids and lumped loads. Distributed intelligent multi-agent technology is applied to make the power system more reliable, efficient and capable of exploiting and integrating alternative sources of energy. The algorithm behind the proposed energy resource scheduling has three stages. The first stage is to schedule each microgrid individually to satisfy its internal demand. The next stage involves finding the best possible bids for exporting power to the network and compete in a whole sale energy market. The final stage is to reschedule each microgrid individually to satisfy the total demand, which is the addition of internal demand and the demand from the results of the whole sale energy market simulation. The simulation results of a power system with distributed resources comprising three microgrids and five lumped loads show that the proposed multi-agent system allows efficient management of micro-sources with minimum operational cost. The case studies demonstrate that the system is successfully monitored, controlled and operated by means of the developed multi-agent system. (author)

Multi-agent system for energy resource scheduling of integrated microgrids in a distributed system

Energy Technology Data Exchange (ETDEWEB)

Logenthiran, T.; Srinivasan, Dipti; Khambadkone, Ashwin M. [Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576 (Singapore)

2011-01-15

This paper proposes a multi-agent system for energy resource scheduling of an islanded power system with distributed resources, which consists of integrated microgrids and lumped loads. Distributed intelligent multi-agent technology is applied to make the power system more reliable, efficient and capable of exploiting and integrating alternative sources of energy. The algorithm behind the proposed energy resource scheduling has three stages. The first stage is to schedule each microgrid individually to satisfy its internal demand. The next stage involves finding the best possible bids for exporting power to the network and compete in a whole sale energy market. The final stage is to reschedule each microgrid individually to satisfy the total demand, which is the addition of internal demand and the demand from the results of the whole sale energy market simulation. The simulation results of a power system with distributed resources comprising three microgrids and five lumped loads show that the proposed multi-agent system allows efficient management of micro-sources with minimum operational cost. The case studies demonstrate that the system is successfully monitored, controlled and operated by means of the developed multi-agent system. (author)

Integration of Openstack cloud resources in BES III computing cluster

Science.gov (United States)

Li, Haibo; Cheng, Yaodong; Huang, Qiulan; Cheng, Zhenjing; Shi, Jingyan

2017-10-01

Cloud computing provides a new technical means for data processing of high energy physics experiment. However, the resource of each queue is fixed and the usage of the resource is static in traditional job management system. In order to make it simple and transparent for physicist to use, we developed a virtual cluster system (vpmanager) to integrate IHEPCloud and different batch systems such as Torque and HTCondor. Vpmanager provides dynamic virtual machines scheduling according to the job queue. The BES III use case results show that resource efficiency is greatly improved.

Algorithms for classical and modern scheduling problems

OpenAIRE

Ott, Sebastian

2016-01-01

Subject of this thesis is the design and the analysis of algorithms for scheduling problems. In the first part, we focus on energy-efficient scheduling, where one seeks to minimize the energy needed for processing certain jobs via dynamic adjustments of the processing speed (speed scaling). We consider variations and extensions of the standard model introduced by Yao, Demers, and Shenker in 1995 [79], including the addition of a sleep state, the avoidance of preemption, and variable speed lim...

Analysis of Application Power and Schedule Composition in a High Performance Computing Environment

Energy Technology Data Exchange (ETDEWEB)

Elmore, Ryan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gruchalla, Kenny [National Renewable Energy Lab. (NREL), Golden, CO (United States); Phillips, Caleb [National Renewable Energy Lab. (NREL), Golden, CO (United States); Purkayastha, Avi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Wunder, Nick [National Renewable Energy Lab. (NREL), Golden, CO (United States)

2016-01-05

As the capacity of high performance computing (HPC) systems continues to grow, small changes in energy management have the potential to produce significant energy savings. In this paper, we employ an extensive informatics system for aggregating and analyzing real-time performance and power use data to evaluate energy footprints of jobs running in an HPC data center. We look at the effects of algorithmic choices for a given job on the resulting energy footprints, and analyze application-specific power consumption, and summarize average power use in the aggregate. All of these views reveal meaningful power variance between classes of applications as well as chosen methods for a given job. Using these data, we discuss energy-aware cost-saving strategies based on reordering the HPC job schedule. Using historical job and power data, we present a hypothetical job schedule reordering that: (1) reduces the facility's peak power draw and (2) manages power in conjunction with a large-scale photovoltaic array. Lastly, we leverage this data to understand the practical limits on predicting key power use metrics at the time of submission.

Job-related resources and the pressures of working life.

Science.gov (United States)

Schieman, Scott

2013-03-01

Data from a 2011 representative sample of Canadian workers are used to test the resource versus the stress of higher status hypotheses. Drawing on the Job Demands-Resources model (JD-R), the resource hypothesis predicts that job-related resources reduce job pressure. The stress of higher status hypothesis predicts that job-related resources increase job pressure. Findings tend to favor the resource hypothesis for job autonomy and schedule control, while supporting the stress of higher status for job authority and challenging work. These findings help elaborate on the "resource" concept in the JD-R model and identify unique ways that such resources might contribute to the pressures of working life. Copyright © 2012 Elsevier Inc. All rights reserved.

A short-term operating room surgery scheduling problem integrating multiple nurses roster constraints.

Science.gov (United States)

Xiang, Wei; Yin, Jiao; Lim, Gino

2015-02-01

Operating room (OR) surgery scheduling determines the individual surgery's operation start time and assigns the required resources to each surgery over a schedule period, considering several constraints related to a complete surgery flow and the multiple resources involved. This task plays a decisive role in providing timely treatments for the patients while balancing hospital resource utilization. The originality of the present study is to integrate the surgery scheduling problem with real-life nurse roster constraints such as their role, specialty, qualification and availability. This article proposes a mathematical model and an ant colony optimization (ACO) approach to efficiently solve such surgery scheduling problems. A modified ACO algorithm with a two-level ant graph model is developed to solve such combinatorial optimization problems because of its computational complexity. The outer ant graph represents surgeries, while the inner graph is a dynamic resource graph. Three types of pheromones, i.e. sequence-related, surgery-related, and resource-related pheromone, fitting for a two-level model are defined. The iteration-best and feasible update strategy and local pheromone update rules are adopted to emphasize the information related to the good solution in makespan, and the balanced utilization of resources as well. The performance of the proposed ACO algorithm is then evaluated using the test cases from (1) the published literature data with complete nurse roster constraints, and 2) the real data collected from a hospital in China. The scheduling results using the proposed ACO approach are compared with the test case from both the literature and the real life hospital scheduling. Comparison results with the literature shows that the proposed ACO approach has (1) an 1.5-h reduction in end time; (2) a reduction in variation of resources' working time, i.e. 25% for ORs, 50% for nurses in shift 1 and 86% for nurses in shift 2; (3) an 0.25h reduction in

Selection and scheduling of jobs with time-dependent duration

African Journals Online (AJOL)

†Department of Logistics, University of Stellenbosch, Private Bag X1, ... station must apply to occupy the test station and sometimes may even choose ... are considered where the job duration and cost are dependent on the time and sequence.

Optimal Rules for Single Machine Scheduling with Stochastic Breakdowns

Directory of Open Access Journals (Sweden)

Jinwei Gu

2014-01-01

Full Text Available This paper studies the problem of scheduling a set of jobs on a single machine subject to stochastic breakdowns, where jobs have to be restarted if preemptions occur because of breakdowns. The breakdown process of the machine is independent of the jobs processed on the machine. The processing times required to complete the jobs are constants if no breakdown occurs. The machine uptimes are independently and identically distributed (i.i.d. and are subject to a uniform distribution. It is proved that the Longest Processing Time first (LPT rule minimizes the expected makespan. For the large-scale problem, it is also showed that the Shortest Processing Time first (SPT rule is optimal to minimize the expected total completion times of all jobs.

Job prioritization in LHCb

CERN Document Server

Castellani, G

2007-01-01

LHCb is one of the four high-energy experiments running in the near future at the Large Hadron Collider (LHC) at CERN. LHCb will try to answer some fundamental questions about the asymmetry between matter and anti-matter. The experiment is expected to produce about 2PB of data per year. Those will be distributed to several laboratories all over Europe and then analyzed by the Physics community. To achieve this target LHCb fully uses the Grid to reprocess, replicate and analyze data. The access to the Grid happens through LHCb's own distributed production and analysis system, DIRAC (Distributed Infrastructure with Remote Agent Control). Dirac implements the ‘pull’ job scheduling paradigm, where all the jobs are stored in a central task queues and then pulled via generic grid jobs called Pilot Agents. The whole LHCb community (about 600 people) is divided in sets of physicists, developers, production and software managers that have different needs about their jobs on the Grid. While a Monte Carlo simulation...

Joint optimization of production scheduling and machine group preventive maintenance

International Nuclear Information System (INIS)

Xiao, Lei; Song, Sanling; Chen, Xiaohui; Coit, David W.

2016-01-01

Joint optimization models were developed combining group preventive maintenance of a series system and production scheduling. In this paper, we propose a joint optimization model to minimize the total cost including production cost, preventive maintenance cost, minimal repair cost for unexpected failures and tardiness cost. The total cost depends on both the production process and the machine maintenance plan associated with reliability. For the problems addressed in this research, any machine unavailability leads to system downtime. Therefore, it is important to optimize the preventive maintenance of machines because their performance impacts the collective production processing associated with all machines. Too lengthy preventive maintenance intervals may be associated with low scheduled machine maintenance cost, but may incur expensive costs for unplanned failure due to low machine reliability. Alternatively, too frequent preventive maintenance activities may achieve the desired high reliability machines, but unacceptably high scheduled maintenance cost. Additionally, product scheduling plans affect tardiness and maintenance cost. Two results are obtained when solving the problem; the optimal group preventive maintenance interval for machines, and the assignment of each job, including the corresponding start time and completion time. To solve this non-deterministic polynomial-time problem, random keys genetic algorithms are used, and a numerical example is solved to illustrate the proposed model. - Highlights: • Group preventive maintenance (PM) planning and production scheduling are jointed. • Maintenance interval and assignment of jobs are decided by minimizing total cost. • Relationships among system age, PM, job processing time are quantified. • Random keys genetic algorithms (GA) are used to solve the NP-hard problem. • Random keys GA and Particle Swarm Optimization (PSO) are compared.

A Computer-Based, Interactive Videodisc Job Aid and Expert System for Electron Beam Lithography Integration and Diagnostic Procedures.

Science.gov (United States)

Stevenson, Kimberly

This master's thesis describes the development of an expert system and interactive videodisc computer-based instructional job aid used for assisting in the integration of electron beam lithography devices. Comparable to all comprehensive training, expert system and job aid development require a criterion-referenced systems approach treatment to…

An Improved Multiobjective PSO for the Scheduling Problem of Panel Block Construction

Directory of Open Access Journals (Sweden)

Zhi Yang

2016-01-01

Full Text Available Uncertainty is common in ship construction. However, few studies have focused on scheduling problems under uncertainty in shipbuilding. This paper formulates the scheduling problem of panel block construction as a multiobjective fuzzy flow shop scheduling problem (FSSP with a fuzzy processing time, a fuzzy due date, and the just-in-time (JIT concept. An improved multiobjective particle swarm optimization called MOPSO-M is developed to solve the scheduling problem. MOPSO-M utilizes a ranked-order-value rule to convert the continuous position of particles into the discrete permutations of jobs, and an available mapping is employed to obtain the precedence-based permutation of the jobs. In addition, to improve the performance of MOPSO-M, archive maintenance is combined with global best position selection, and mutation and a velocity constriction mechanism are introduced into the algorithm. The feasibility and effectiveness of MOPSO-M are assessed in comparison with general MOPSO and nondominated sorting genetic algorithm-II (NSGA-II.

Project orie:nta.teci pla.:n:ni:ng, scheduling a.:nci controlling technique

African Journals Online (AJOL)

Review Technique. By October 1958 it ... (CPM) to schedule and control a very large project. and during the ... objectives are identified and the total job is broken down into ..... jobs in a single shop or shops in the plant, to scheduf- ing plants ...

A Hybrid Genetic Algorithm to Minimize Total Tardiness for Unrelated Parallel Machine Scheduling with Precedence Constraints

Directory of Open Access Journals (Sweden)

Chunfeng Liu

2013-01-01

Full Text Available The paper presents a novel hybrid genetic algorithm (HGA for a deterministic scheduling problem where multiple jobs with arbitrary precedence constraints are processed on multiple unrelated parallel machines. The objective is to minimize total tardiness, since delays of the jobs may lead to punishment cost or cancellation of orders by the clients in many situations. A priority rule-based heuristic algorithm, which schedules a prior job on a prior machine according to the priority rule at each iteration, is suggested and embedded to the HGA for initial feasible schedules that can be improved in further stages. Computational experiments are conducted to show that the proposed HGA performs well with respect to accuracy and efficiency of solution for small-sized problems and gets better results than the conventional genetic algorithm within the same runtime for large-sized problems.

Mixed waste focus area integrated master schedule (current as of May 6, 1996)

International Nuclear Information System (INIS)

1996-01-01

The mission of the Mixed Waste Characterization, Treatment, and Disposal Focus Area (MWFA) is to provide acceptable treatment systems, developed in partnership with users and with the participation of stakeholders, tribal governments, and regulators, that are capable of treating the Department of Energy's (DOE's) mixed wastes. In support of this mission, the MWTA produced the Mixed Waste Focus Area Integrated Technical Baseline Report, Phase I Volume 1, January 16, 1996, which identified a prioritized list of 30 national mixed waste technology deficiencies. The MWFA is targeting funding toward technology development projects that address the current list of deficiencies. A clear connection between the technology development projects and the EM-30 and EM-40 treatment systems that they support is essential for optimizing the MWFA efforts. The purpose of the Integrated Master Schedule (IMS) is to establish and document these connections and to ensure that all technology development activities performed by the MWFA are developed for timely use in those treatment systems. The IMS is a list of treatment systems from the Site Treatment Plans (STPs)/Consent Orders that have been assigned technology development needs with associated time-driven schedules, Technology deficiencies and associated technology development (TD) needs have been identified for each treatment system based on the physical, chemical, and radiological characteristics of the waste targeted for the treatment system. The schedule, the technology development activities, and the treatment system have been verified through the operations contact from the EM-30 organization at the site

Facilitating Integration of Electron Beam Lithography Devices with Interactive Videodisc, Computer-Based Simulation and Job Aids.

Science.gov (United States)

Von Der Linn, Robert Christopher

A needs assessment of the Grumman E-Beam Systems Group identified the requirement for additional skill mastery for the engineers who assemble, integrate, and maintain devices used to manufacture integrated circuits. Further analysis of the tasks involved led to the decision to develop interactive videodisc, computer-based job aids to enable…

Online Scheduling in Distributed Message Converter Systems

NARCIS (Netherlands)

Risse, Thomas; Wombacher, Andreas; Surridge, Mike; Taylor, Steve; Aberer, Karl

The optimal distribution of jobs among hosts in distributed environments is an important factor to achieve high performance. The optimal strategy depends on the application. In this paper we present a new online scheduling strategy for distributed EDI converter system. The strategy is based on the

An MILP approach to shelf life integrated planning and scheduling in scalded sausage production

DEFF Research Database (Denmark)

Günther, H.O.; van Beek, P.; Grunow, Martin

2006-01-01

in which shelf life aspects are integrated into operational production planning and scheduling functions. Specifically we make use of so-called Mixed Integer Linear Programming (MILP) models. Our research is based on an industrial case study of yogurt production. Relying on the principle of block planning...

An unit cost adjusting heuristic algorithm for the integrated planning and scheduling of a two-stage supply chain

Directory of Open Access Journals (Sweden)

Jianhua Wang

2014-10-01

Full Text Available Purpose: The stable relationship of one-supplier-one-customer is replaced by a dynamic relationship of multi-supplier-multi-customer in current market gradually, and efficient scheduling techniques are important tools of the dynamic supply chain relationship establishing process. This paper studies the optimization of the integrated planning and scheduling problem of a two-stage supply chain with multiple manufacturers and multiple retailers to obtain a minimum supply chain operating cost, whose manufacturers have different production capacities, holding and producing cost rates, transportation costs to retailers.Design/methodology/approach: As a complex task allocation and scheduling problem, this paper sets up an INLP model for it and designs a Unit Cost Adjusting (UCA heuristic algorithm that adjust the suppliers’ supplying quantity according to their unit costs step by step to solve the model.Findings: Relying on the contrasting analysis between the UCA and the Lingo solvers for optimizing many numerical experiments, results show that the INLP model and the UCA algorithm can obtain its near optimal solution of the two-stage supply chain’s planning and scheduling problem within very short CPU time.Research limitations/implications: The proposed UCA heuristic can easily help managers to optimizing the two-stage supply chain scheduling problems which doesn’t include the delivery time and batch of orders. For two-stage supply chains are the most common form of actual commercial relationships, so to make some modification and study on the UCA heuristic should be able to optimize the integrated planning and scheduling problems of a supply chain with more reality constraints.Originality/value: This research proposes an innovative UCA heuristic for optimizing the integrated planning and scheduling problem of two-stage supply chains with the constraints of suppliers’ production capacity and the orders’ delivering time, and has a great

Non-clairvoyant weighted flow time scheduling with rejection penalty

DEFF Research Database (Denmark)

Chan, Ho-Leung; Chan, Sze-Hang; Lam, Tak-Wah

2012-01-01

is defined as the weighted flow time of the job plus the penalty if it is rejected before completion. Previous work on minimizing the total user cost focused on the clairvoyant single-processor setting [BBC+03,CLL11] and has produced O(1)-competitive online algorithm for jobs with arbitrary weights...... algorithm has to decide job rejection and determine the order and speed of job execution. It is interesting to study the tradeoff between the above-mentioned user cost and energy. This paper gives two O(1)-competitive non-clairvoyant algorithms for minimizing the user cost plus energy on a single processor......This paper initiates the study of online scheduling with rejection penalty in the non-clairvoyant setting, i.e., the size (processing time) of a job is not assumed to be known at its release time. In the rejection penalty model, jobs can be rejected with a penalty, and the user cost of a job...

Nontraditional work schedules for pharmacists.

Science.gov (United States)

Mahaney, Lynnae; Sanborn, Michael; Alexander, Emily

2008-11-15

Nontraditional work schedules for pharmacists at three institutions are described. The demand for pharmacists and health care in general continues to increase, yet significant material changes are occurring in the pharmacy work force. These changing demographics, coupled with historical vacancy rates and turnover trends for pharmacy staff, require an increased emphasis on workplace changes that can improve staff recruitment and retention. At William S. Middleton Memorial Veterans Affairs Hospital in Madison, Wisconsin, creative pharmacist work schedules and roles are now mainstays to the recruitment and retention of staff. The major challenge that such scheduling presents is the 8 hours needed to prepare a six-week schedule. Baylor Medical Center at Grapevine in Dallas, Texas, has a total of 45 pharmacy employees, and slightly less than half of the 24.5 full-time-equivalent staff work full-time, with most preferring to work one, two, or three days per week. As long as the coverage needs of the facility are met, Envision Telepharmacy in Alpine, Texas, allows almost any scheduling arrangement preferred by individual pharmacists or the pharmacist group covering the facility. Staffing involves a great variety of shift lengths and intervals, with shifts ranging from 2 to 10 hours. Pharmacy leaders must be increasingly aware of opportunities to provide staff with unique scheduling and operational enhancements that can provide for a better work-life balance. Compressed workweeks, job-sharing, and team scheduling were the most common types of alternative work schedules implemented at three different institutions.

Scheduling Model for Renewable Energy Sources Integration in an Insular Power System

Directory of Open Access Journals (Sweden)

Gerardo J. Osório

2018-01-01

Full Text Available Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has brought more uncertainty to production management. In this work, an innovative scheduling model is proposed, which considers the integration of wind and solar resources in an insular power system in Portugal, with a strong conventional generation basis. This study aims to show the benefits of increasing the integration of renewable energy resources in this insular power system, and the objectives are related to minimizing the time for which conventional generation is in operation, maximizing profits, reducing production costs, and consequently, reducing greenhouse gas emissions.

Automatic Integration Testbeds validation on Open Science Grid

International Nuclear Information System (INIS)

Caballero, J; Potekhin, M; Thapa, S; Gardner, R

2011-01-01

A recurring challenge in deploying high quality production middleware is the extent to which realistic testing occurs before release of the software into the production environment. We describe here an automated system for validating releases of the Open Science Grid software stack that leverages the (pilot-based) PanDA job management system developed and used by the ATLAS experiment. The system was motivated by a desire to subject the OSG Integration Testbed to more realistic validation tests. In particular those which resemble to every extent possible actual job workflows used by the experiments thus utilizing job scheduling at the compute element (CE), use of the worker node execution environment, transfer of data to/from the local storage element (SE), etc. The context is that candidate releases of OSG compute and storage elements can be tested by injecting large numbers of synthetic jobs varying in complexity and coverage of services tested. The native capabilities of the PanDA system can thus be used to define jobs, monitor their execution, and archive the resulting run statistics including success and failure modes. A repository of generic workflows and job types to measure various metrics of interest has been created. A command-line toolset has been developed so that testbed managers can quickly submit 'VO-like' jobs into the system when newly deployed services are ready for testing. A system for automatic submission has been crafted to send jobs to integration testbed sites, collecting the results in a central service and generating regular reports for performance and reliability.

Automatic Integration Testbeds validation on Open Science Grid

Science.gov (United States)

Caballero, J.; Thapa, S.; Gardner, R.; Potekhin, M.

2011-12-01

A recurring challenge in deploying high quality production middleware is the extent to which realistic testing occurs before release of the software into the production environment. We describe here an automated system for validating releases of the Open Science Grid software stack that leverages the (pilot-based) PanDA job management system developed and used by the ATLAS experiment. The system was motivated by a desire to subject the OSG Integration Testbed to more realistic validation tests. In particular those which resemble to every extent possible actual job workflows used by the experiments thus utilizing job scheduling at the compute element (CE), use of the worker node execution environment, transfer of data to/from the local storage element (SE), etc. The context is that candidate releases of OSG compute and storage elements can be tested by injecting large numbers of synthetic jobs varying in complexity and coverage of services tested. The native capabilities of the PanDA system can thus be used to define jobs, monitor their execution, and archive the resulting run statistics including success and failure modes. A repository of generic workflows and job types to measure various metrics of interest has been created. A command-line toolset has been developed so that testbed managers can quickly submit "VO-like" jobs into the system when newly deployed services are ready for testing. A system for automatic submission has been crafted to send jobs to integration testbed sites, collecting the results in a central service and generating regular reports for performance and reliability.

An Extended Flexible Job Shop Scheduling Model for Flight Deck Scheduling with Priority, Parallel Operations, and Sequence Flexibility

Directory of Open Access Journals (Sweden)

Lianfei Yu

2017-01-01

Full Text Available Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.

Optimization of multi-objective integrated process planning and scheduling problem using a priority based optimization algorithm

Science.gov (United States)

Ausaf, Muhammad Farhan; Gao, Liang; Li, Xinyu

2015-12-01

For increasing the overall performance of modern manufacturing systems, effective integration of process planning and scheduling functions has been an important area of consideration among researchers. Owing to the complexity of handling process planning and scheduling simultaneously, most of the research work has been limited to solving the integrated process planning and scheduling (IPPS) problem for a single objective function. As there are many conflicting objectives when dealing with process planning and scheduling, real world problems cannot be fully captured considering only a single objective for optimization. Therefore considering multi-objective IPPS (MOIPPS) problem is inevitable. Unfortunately, only a handful of research papers are available on solving MOIPPS problem. In this paper, an optimization algorithm for solving MOIPPS problem is presented. The proposed algorithm uses a set of dispatching rules coupled with priority assignment to optimize the IPPS problem for various objectives like makespan, total machine load, total tardiness, etc. A fixed sized external archive coupled with a crowding distance mechanism is used to store and maintain the non-dominated solutions. To compare the results with other algorithms, a C-matric based method has been used. Instances from four recent papers have been solved to demonstrate the effectiveness of the proposed algorithm. The experimental results show that the proposed method is an efficient approach for solving the MOIPPS problem.

Planning and Optimization of AGV Jobs by Petri Net and Genetic Algorithm

Directory of Open Access Journals (Sweden)

Anita Gudelj

2012-12-01

Full Text Available The following article presents the possibilities of job optimization on a maritime container terminal, in order to increase the system productivity and optimize the terminal capacity. Automated guided vehicles (AGVs are now becoming popular mode of container transport in seaport terminals. The moving of vehicles can be described as the set of discrete events and states. Some of these states can be undesirable such as conflicts and deadlocks. It is necessary to apply adequate control policy to avoid deadlocks and block the vehicles’ moving only in the case of dangerous situation.This paper addresses the use a Petri net as modeling and scheduling tool in this context. The aim of AGV scheduling is to dispatch a set of AGVs to improve the productivity of a system and reduce delay in a batch of pickup/drop-off jobs under certain constraints such as deadlines, priority, etc. The final goals are related to optimization of processing time and minimization of the number of AGVs involved while maintaining the system throughput.To find better solutions, the authors propose the integration MRF1 class of Petri net (MRF1PN with a genetic algorithm. Also, the use of a matrix based formal method is proposed to analyze discrete event dynamic system (DEDS. The algorithm is described to deal with multi-project, multi-constrained scheduling problem with shared resources. The developed model was tested and validated by simulation of typical scenarios of the container terminal of Port Koper. Modularity and simplicity of the approach allow using the model to monitor and test the efficiency of the processes, and also to propose future alternative solutions to optimize the schedule of operations and the employment of AGV at the terminal.

Integrated Cost and Schedule Control Systems for Nuclear Power Plant Construction: Leveraging Strategic Advantages to Owners and EPC Firms

Directory of Open Access Journals (Sweden)

Youngsoo Jung

2015-01-01

Full Text Available As the owners expect that the cost and time for nuclear power plant construction would decrease with new entrants into the market, there will be severer competition in the nuclear industry. In order to achieve performance improvement and to attain competitive advantages under the globalized competition, practitioners and researchers in the nuclear industry have recently exerted efforts to develop an advanced and efficient management methodology for the nuclear mega-projects. Among several candidates, integrated cost and schedule control system is of great concern because it can effectively manage the three most important project performances including cost, time, and quality. In this context, the purpose of this paper is to develop a project numbering system (PNS of integrated cost and schedule control system for nuclear power plant construction. Distinct attributes of nuclear power plant construction were investigated first in order to identify influencing variables that characterize real-world implementation of advanced cost and schedule controls. A scenario was then developed and analysed to simulate a case-project. By using this case-project, proposed management requirements, management methods, measurement techniques, data structure, and data collection methods for integrated cost and schedule PNS were illustrated. Finally, findings and implications are outlined, and recommendations for further research are presented.

A note on resource allocation scheduling with group technology and learning effects on a single machine

Science.gov (United States)

Lu, Yuan-Yuan; Wang, Ji-Bo; Ji, Ping; He, Hongyu

2017-09-01

In this article, single-machine group scheduling with learning effects and convex resource allocation is studied. The goal is to find the optimal job schedule, the optimal group schedule, and resource allocations of jobs and groups. For the problem of minimizing the makespan subject to limited resource availability, it is proved that the problem can be solved in polynomial time under the condition that the setup times of groups are independent. For the general setup times of groups, a heuristic algorithm and a branch-and-bound algorithm are proposed, respectively. Computational experiments show that the performance of the heuristic algorithm is fairly accurate in obtaining near-optimal solutions.

Job satisfaction and subjective well-being among Czech nurses.

Science.gov (United States)

Gurková, Elena; Haroková, Sylvie; Džuka, Jozef; Žiaková, Katarína

2014-04-01

The aim of the present study was to investigate the relationship between domains of the job satisfaction and components of subjective well-being in nurses. A convenience sample of hospital nurses was recruited from six hospitals in Czech Republic. Data were collected using a set of questionnaires that included the McCloskey/Mueller Satisfaction Scale, the Positive Affect Scale, the Negative Affect Scale and the Personal Well-being Index. We confirmed low association between job satisfaction and subjective well-being of nurses. Satisfaction with extrinsic rewards, co-workers and family/work balance accounted for only a small percentage of variance in cognitive component of subjective well-being. Positive affect was predicted by interaction opportunities and scheduling. Negative affect was predicted by interaction opportunities and scheduling and intention to leave the actual workplace. Low percentage of the variance suggests that subjective well-being is not strongly influenced by job satisfaction. © 2013 Wiley Publishing Asia Pty Ltd.

Scheduling nurses’ shifts at PGI Cikini Hospital

Science.gov (United States)

Nainggolan, J. C. T.; Kusumastuti, R. D.

2018-03-01

Hospitals play an essential role in the community by providing medical services to the public. In order to provide high quality medical services, hospitals must manage their resources (including nurses) effectively and efficiently. Scheduling of nurses’ work shifts, in particular, is crucial, and must be conducted carefully to ensure availability and fairness. This research discusses the job scheduling system for nurses in PGI Cikini Hospital, Jakarta with Goal Programming approach. The research objectives are to identify nurse scheduling criteria and find the best schedule that can meet the criteria. The model has hospital regulations (including government regulations) as hard constraints, and nurses’ preferences as soft constraints. We gather primary data (hospital regulations and nurses’ preferences) through interviews with three Head Nurses and distributing questionnaires to fifty nurses. The results show that on the best schedule, all hard constraints can be satisfied. However, only two out of four soft constraints are satisfied. Compared to current scheduling practice, the resulting schedule ensures the availability of nurses as it satisfies all hospital’s regulations and it has a higher level of fairness as it can accommodate some of the nurses’ preferences.

Permutation flow-shop scheduling problem to optimize a quadratic objective function

Science.gov (United States)

Ren, Tao; Zhao, Peng; Zhang, Da; Liu, Bingqian; Yuan, Huawei; Bai, Danyu

2017-09-01

A flow-shop scheduling model enables appropriate sequencing for each job and for processing on a set of machines in compliance with identical processing orders. The objective is to achieve a feasible schedule for optimizing a given criterion. Permutation is a special setting of the model in which the processing order of the jobs on the machines is identical for each subsequent step of processing. This article addresses the permutation flow-shop scheduling problem to minimize the criterion of total weighted quadratic completion time. With a probability hypothesis, the asymptotic optimality of the weighted shortest processing time schedule under a consistency condition (WSPT-CC) is proven for sufficiently large-scale problems. However, the worst case performance ratio of the WSPT-CC schedule is the square of the number of machines in certain situations. A discrete differential evolution algorithm, where a new crossover method with multiple-point insertion is used to improve the final outcome, is presented to obtain high-quality solutions for moderate-scale problems. A sequence-independent lower bound is designed for pruning in a branch-and-bound algorithm for small-scale problems. A set of random experiments demonstrates the performance of the lower bound and the effectiveness of the proposed algorithms.

A canned food scheduling problem with batch due date

Science.gov (United States)

Chung, Tsui-Ping; Liao, Ching-Jong; Smith, Milton

2014-09-01

This article considers a canned food scheduling problem where jobs are grouped into several batches. Jobs can be sent to the next operation only when all the jobs in the same batch have finished their processing, i.e. jobs in a batch, have a common due date. This batch due date problem is quite common in canned food factories, but there is no efficient heuristic to solve the problem. The problem can be formulated as an identical parallel machine problem with batch due date to minimize the total tardiness. Since the problem is NP hard, two heuristics are proposed to find the near-optimal solution. Computational results comparing the effectiveness and efficiency of the two proposed heuristics with an existing heuristic are reported and discussed.

How job demands affect partners' experience of exhaustion: integrating work-family conflict and crossover theory.

Science.gov (United States)

Bakker, Arnold B; Demerouti, Evangelia; Dollard, Maureen F

2008-07-01

This study among 168 couples of dual-earner parents uses insights from previous work-family conflict and crossover research to propose an integrative model delineating how job demands experienced by men and women carry over to the home domain. The authors hypothesized that for both men and women, job demands foster their own work-family conflict (WFC), which in turn contributes to their partners' home demands, family-work conflict (FWC), and exhaustion. In addition, they hypothesized that social undermining mediates the relationship between individuals' WFC and their partners' home demands. The results of structural equation modeling analyses provided strong support for the proposed model. The hypothesis that gender would moderate the model relationships was rejected. These findings integrate previous findings on work-family conflict and crossover theories and suggest fluid boundaries between the work and home domains.

Job satisfaction among a multigenerational nursing workforce.

Science.gov (United States)

Wilson, Barbara; Squires, Mae; Widger, Kimberley; Cranley, Lisa; Tourangeau, Ann

2008-09-01

To explore generational differences in job satisfaction. Effective retention strategies are required to mitigate the international nursing shortage. Job satisfaction, a strong and consistent predictor of retention, may differ across generations. Understanding job satisfaction generational differences may lead to increasing clarity about generation-specific retention approaches. The Ontario Nurse Survey collected data from 6541 Registered Nurses. Participants were categorized as Baby Boomer, Generation X or Generation Y based on birth year. Multivariate analysis of variance explored generational differences for overall and specific satisfaction components. In overall job satisfaction and five specific satisfaction components, Baby Boomers were significantly more satisfied than Generations X and Y. It is imperative to improve job satisfaction for younger generations of nurses. Strategies to improve job satisfaction for younger generations of nurses may include creating a shared governance framework where nurses are empowered to make decisions. Implementing shared governance, through nurse-led unit-based councils, may lead to greater job satisfaction, particularly for younger nurses. Opportunities to self schedule or job share may be other potential approaches to increase job satisfaction, especially for younger generations of nurses. Another potential strategy would be to aggressively provide and support education and career-development opportunities.

User interface issues in supporting human-computer integrated scheduling

Science.gov (United States)

Cooper, Lynne P.; Biefeld, Eric W.

1991-01-01

The topics are presented in view graph form and include the following: characteristics of Operations Mission Planner (OMP) schedule domain; OMP architecture; definition of a schedule; user interface dimensions; functional distribution; types of users; interpreting user interaction; dynamic overlays; reactive scheduling; and transitioning the interface.

Heuristics for no-wait flow shop scheduling problem

Directory of Open Access Journals (Sweden)

Kewal Krishan Nailwal

2016-09-01

Full Text Available No-wait flow shop scheduling refers to continuous flow of jobs through different machines. The job once started should have the continuous processing through the machines without wait. This situation occurs when there is a lack of an intermediate storage between the processing of jobs on two consecutive machines. The problem of no-wait with the objective of minimizing makespan in flow shop scheduling is NP-hard; therefore the heuristic algorithms are the key to solve the problem with optimal solution or to approach nearer to optimal solution in simple manner. The paper describes two heuristics, one constructive and an improvement heuristic algorithm obtained by modifying the constructive one for sequencing n-jobs through m-machines in a flow shop under no-wait constraint with the objective of minimizing makespan. The efficiency of the proposed heuristic algorithms is tested on 120 Taillard’s benchmark problems found in the literature against the NEH under no-wait and the MNEH heuristic for no-wait flow shop problem. The improvement heuristic outperforms all heuristics on the Taillard’s instances by improving the results of NEH by 27.85%, MNEH by 22.56% and that of the proposed constructive heuristic algorithm by 24.68%. To explain the computational process of the proposed algorithm, numerical illustrations are also given in the paper. Statistical tests of significance are done in order to draw the conclusions.

Job sharing as an employment alternative in group medical practice.

Science.gov (United States)

Vanek, E P; Vanek, J A

2001-01-01

Although physicians discuss quality-of-life and employment issues with their patients, they often fail to consider flexible scheduling and reduced employment options to lessen their own job stress. We examined one of these options by surveying two community-based, private practice groups with a combined 13-year experience with job sharing. We found that a majority of respondents rated job sharing as successful, and most wanted it to continue. Job sharers derived considerable personal benefit from the arrangement and had significantly more positive attitudes toward work than full-time physicians. Job sharing appeared to have little impact on practice parameters. Dependability, flexibility and willingness to cooperate were the most important attributes in choosing a job-sharing partner. Job sharing is an employment alternative worth exploring to retain physicians in medical group practice.

Evolutionary approaches for scheduling a flexible manufacturing system with automated guided vehicles and robots

Directory of Open Access Journals (Sweden)

Ramaraj Natarajan

2012-08-01

Full Text Available This paper addresses the scheduling of machines, an Automated Guided Vehicle (AGV and two robots in a Flexible Manufacturing System (FMS formed in three loop layouts, with objectives to minimize the makespan, mean flow time and mean tardiness. The scheduling optimization is carried out using Sheep Flock Heredity Algorithm (SFHA and Artificial Immune System (AIS algorithm. AGV is used for carrying jobs between the Load/Unload station and the machines. The robots are used for loading and unloading the jobs in the machines, and also used for transferring jobs between the machines. The algorithms are applied for test problems taken from the literature and the results obtained using the two algorithms are compared. The results indicate that SFHA performs better than AIS for this problem.

Job adjustment as a means to reduce sickness absence during pregnancy.

Science.gov (United States)

Strand, K; Wergeland, E; Bjerkedal, T

1997-10-01

This study examined the effect of job adjustment on sickness absence during pregnancy and also determined the conditions under which such adjustments are obtained. Data were derived from a nationally representative survey on work conditions during pregnancy in Norway in 1989. For employees (N = 2713) remaining in the same job throughout pregnancy, the percentage of women on sick leave immediately before delivery was determined according to the need for job adjustment and the obtainment of job adjustment. Those obtaining job adjustment were grouped according to workplace size, labor-market sector, co-worker gender, educational level, work schedules, weekly workhours, children under 16 years of age in the household, and age. All told, 1691 women (62.3%) needed job adjustment, among whom 936 (55.4%) obtained such adjustment. The proportions of those on sick leave before delivery were 45.2% for "no need", 67.9% for "need - adjustment obtained", and 79.2% for "need - adjustment not obtained". In the last category, the difference (versus "adjustment obtained") constituted 44.5% of the weeks lost because of sickness absence in the last half of pregnancy. The odds ratio (OR) for obtaining job adjustment was larger for workplaces with more than 50 employees (OR 1.4) and smaller for jobs with work schedules other than daytime or shift work (OR 0.5) and also for women living with children under 16 years of age (OR 0.8). Job adjustment is associated with reduced sickness absence during pregnancy. Further studies should explore workplace characteristics that make it difficult to obtain such adjustments, as required by law.

Hybrid Pareto artificial bee colony algorithm for multi-objective single machine group scheduling problem with sequence-dependent setup times and learning effects.

Science.gov (United States)

Yue, Lei; Guan, Zailin; Saif, Ullah; Zhang, Fei; Wang, Hao

2016-01-01

Group scheduling is significant for efficient and cost effective production system. However, there exist setup times between the groups, which require to decrease it by sequencing groups in an efficient way. Current research is focused on a sequence dependent group scheduling problem with an aim to minimize the makespan in addition to minimize the total weighted tardiness simultaneously. In most of the production scheduling problems, the processing time of jobs is assumed as fixed. However, the actual processing time of jobs may be reduced due to "learning effect". The integration of sequence dependent group scheduling problem with learning effects has been rarely considered in literature. Therefore, current research considers a single machine group scheduling problem with sequence dependent setup times and learning effects simultaneously. A novel hybrid Pareto artificial bee colony algorithm (HPABC) with some steps of genetic algorithm is proposed for current problem to get Pareto solutions. Furthermore, five different sizes of test problems (small, small medium, medium, large medium, large) are tested using proposed HPABC. Taguchi method is used to tune the effective parameters of the proposed HPABC for each problem category. The performance of HPABC is compared with three famous multi objective optimization algorithms, improved strength Pareto evolutionary algorithm (SPEA2), non-dominated sorting genetic algorithm II (NSGAII) and particle swarm optimization algorithm (PSO). Results indicate that HPABC outperforms SPEA2, NSGAII and PSO and gives better Pareto optimal solutions in terms of diversity and quality for almost all the instances of the different sizes of problems.

A Hybrid Metaheuristic Approach for Minimizing the Total Flow Time in A Flow Shop Sequence Dependent Group Scheduling Problem

Directory of Open Access Journals (Sweden)

Antonio Costa

2014-07-01

Full Text Available Production processes in Cellular Manufacturing Systems (CMS often involve groups of parts sharing the same technological requirements in terms of tooling and setup. The issue of scheduling such parts through a flow-shop production layout is known as the Flow-Shop Group Scheduling (FSGS problem or, whether setup times are sequence-dependent, the Flow-Shop Sequence-Dependent Group Scheduling (FSDGS problem. This paper addresses the FSDGS issue, proposing a hybrid metaheuristic procedure integrating features from Genetic Algorithms (GAs and Biased Random Sampling (BRS search techniques with the aim of minimizing the total flow time, i.e., the sum of completion times of all jobs. A well-known benchmark of test cases, entailing problems with two, three, and six machines, is employed for both tuning the relevant parameters of the developed procedure and assessing its performances against two metaheuristic algorithms recently presented by literature. The obtained results and a properly arranged ANOVA analysis highlight the superiority of the proposed approach in tackling the scheduling problem under investigation.

Scheduling lessons learned from the Autonomous Power System

Science.gov (United States)

Ringer, Mark J.

1992-01-01

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

A distributed scheduling algorithm for heterogeneous real-time systems

Science.gov (United States)

Zeineldine, Osman; El-Toweissy, Mohamed; Mukkamala, Ravi

1991-01-01

Much of the previous work on load balancing and scheduling in distributed environments was concerned with homogeneous systems and homogeneous loads. Several of the results indicated that random policies are as effective as other more complex load allocation policies. The effects of heterogeneity on scheduling algorithms for hard real time systems is examined. A distributed scheduler specifically to handle heterogeneities in both nodes and node traffic is proposed. The performance of the algorithm is measured in terms of the percentage of jobs discarded. While a random task allocation is very sensitive to heterogeneities, the algorithm is shown to be robust to such non-uniformities in system components and load.

Off-Line and Dynamic Production Scheduling – A Comparative Case Study

Directory of Open Access Journals (Sweden)

Bożek Andrzej

2016-03-01

Full Text Available A comprehensive case study of manufacturing scheduling solutions development is given. It includes highly generalized scheduling problem as well as a few scheduling modes, methods and problem models. The considered problem combines flexible job shop structure, lot streaming with variable sublots, transport times, setup times, and machine calendars. Tabu search metaheuristic and constraint programming methods have been used for the off-line scheduling. Two dynamic scheduling methods have also been implemented, i.e., dispatching rules for the completely reactive scheduling and a multi-agent system for the predictivereactive scheduling. In these implementations three distinct models of the problem have been used, based on: graph representation, optimal constraint satisfaction, and Petri net formalism. Each of these solutions has been verified in computational experiments. The results are compared and some findings about advantages, disadvantages, and suggestions on using the solutions are formulated.

Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management.

Science.gov (United States)

Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

2018-02-25

The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

Science.gov (United States)

Silva, Bhagya Nathali; Khan, Murad; Han, Kijun

2018-01-01

The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST) algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism. PMID:29495346

Load Balancing Integrated Least Slack Time-Based Appliance Scheduling for Smart Home Energy Management

Directory of Open Access Journals (Sweden)

Bhagya Nathali Silva

2018-02-01

Full Text Available The emergence of smart devices and smart appliances has highly favored the realization of the smart home concept. Modern smart home systems handle a wide range of user requirements. Energy management and energy conservation are in the spotlight when deploying sophisticated smart homes. However, the performance of energy management systems is highly influenced by user behaviors and adopted energy management approaches. Appliance scheduling is widely accepted as an effective mechanism to manage domestic energy consumption. Hence, we propose a smart home energy management system that reduces unnecessary energy consumption by integrating an automated switching off system with load balancing and appliance scheduling algorithm. The load balancing scheme acts according to defined constraints such that the cumulative energy consumption of the household is managed below the defined maximum threshold. The scheduling of appliances adheres to the least slack time (LST algorithm while considering user comfort during scheduling. The performance of the proposed scheme has been evaluated against an existing energy management scheme through computer simulation. The simulation results have revealed a significant improvement gained through the proposed LST-based energy management scheme in terms of cost of energy, along with reduced domestic energy consumption facilitated by an automated switching off mechanism.

A transportation-scheduling system for managing silvicultural projects

Science.gov (United States)

Jorge F. Valenzuela; H. Hakan Balci; Timothy McDonald

2005-01-01

A silvicultural project encompasses tasks such as sitelevel planning, regeneration, harvestin, and stand-tending treatments. an essential problem in managing silvicultural projects is to efficiently schedule the operations while considering project task due dates and costs of moving scarce resources to specific job locations. Transportation costs represent a...

Evolutionary Hybrid Particle Swarm Optimization Algorithm for Solving NP-Hard No-Wait Flow Shop Scheduling Problems

Directory of Open Access Journals (Sweden)

Laxmi A. Bewoor

2017-10-01

Full Text Available The no-wait flow shop is a flowshop in which the scheduling of jobs is continuous and simultaneous through all machines without waiting for any consecutive machines. The scheduling of a no-wait flow shop requires finding an appropriate sequence of jobs for scheduling, which in turn reduces total processing time. The classical brute force method for finding the probabilities of scheduling for improving the utilization of resources may become trapped in local optima, and this problem can hence be observed as a typical NP-hard combinatorial optimization problem that requires finding a near optimal solution with heuristic and metaheuristic techniques. This paper proposes an effective hybrid Particle Swarm Optimization (PSO metaheuristic algorithm for solving no-wait flow shop scheduling problems with the objective of minimizing the total flow time of jobs. This Proposed Hybrid Particle Swarm Optimization (PHPSO algorithm presents a solution by the random key representation rule for converting the continuous position information values of particles to a discrete job permutation. The proposed algorithm initializes population efficiently with the Nawaz-Enscore-Ham (NEH heuristic technique and uses an evolutionary search guided by the mechanism of PSO, as well as simulated annealing based on a local neighborhood search to avoid getting stuck in local optima and to provide the appropriate balance of global exploration and local exploitation. Extensive computational experiments are carried out based on Taillard’s benchmark suite. Computational results and comparisons with existing metaheuristics show that the PHPSO algorithm outperforms the existing methods in terms of quality search and robustness for the problem considered. The improvement in solution quality is confirmed by statistical tests of significance.

Age-Differential Effects of Job Characteristics on Job Attraction: A Policy-Capturing Study.

Science.gov (United States)

Zacher, Hannes; Dirkers, Bodil T; Korek, Sabine; Hughes, Brenda

2017-01-01

Based on an integration of job design and lifespan developmental theories, Truxillo et al. (2012) proposed that job characteristics interact with employee age in predicting important work outcomes. Using an experimental policy-capturing design, we investigated age-differential effects of four core job characteristics (i.e., job autonomy, task variety, task significance, and feedback from the job) on job attraction (i.e., individuals' rating of job attractiveness). Eighty-two employees between 19 and 65 years ( M age = 41, SD = 14) indicated their job attraction for each of 40 hypothetical job descriptions in which the four job characteristics were systematically manipulated (in total, participants provided 3,280 ratings). Results of multilevel analyses showed that the positive effects of task variety, task significance, and feedback from the job were stronger for younger compared to older employees, whereas we did not find significant age-differential effects of job autonomy on job attraction. These findings are only partially consistent with propositions of Truxillo et al.'s (2012) lifespan perspective on job design.

Delivering Integrated Care to the Frail Elderly: The Impact on Professionals’ Objective Burden and Job Satisfaction

Directory of Open Access Journals (Sweden)

Benjamin Janse

2016-08-01

Full Text Available Background: The impact of integrated working on professionals’ objective burden and job satisfaction was examined. An evidence-based intervention targeting frail elderly patients was implemented in the Walcheren region of the Netherlands in 2010. The intervention involved the primary care practice as a single entry point, and included proactive frailty screening, a comprehensive assessment of patient needs, case management, multidisciplinary teams, care plans and protocols, task delegation and task specialisation, a shared information system, a geriatric care network and integrated funding. Methods: A quasi-experimental design with a control group was used. Data regarding objective burden involved the professionals’ time investments over a 12-month period that were collected from patient medical records (n = 377 time registrations, transcripts of meetings and patient questionnaires. Data regarding job satisfaction were collected using questionnaires that were distributed to primary care and home-care professionals (n = 180 after the intervention’s implementation. Within- and between-groups comparisons and regression analyses were performed.  Results: Non-patient related time was significantly higher in the experimental group than in the control group, whereas patient-related time did not differ. Job satisfaction remained unaffected by the intervention. Conclusion and Discussion: Integrated working is likely to increase objective burden as it requires professionals to perform additional activities that are largely unrelated to actual patient care. Implications for research and practice are discussed. [Current Controlled Trials ISRCTN05748494].

A Study on the Enhanced Best Performance Algorithm for the Just-in-Time Scheduling Problem

Directory of Open Access Journals (Sweden)

Sivashan Chetty

2015-01-01

Full Text Available The Just-In-Time (JIT scheduling problem is an important subject of study. It essentially constitutes the problem of scheduling critical business resources in an attempt to optimize given business objectives. This problem is NP-Hard in nature, hence requiring efficient solution techniques. To solve the JIT scheduling problem presented in this study, a new local search metaheuristic algorithm, namely, the enhanced Best Performance Algorithm (eBPA, is introduced. This is part of the initial study of the algorithm for scheduling problems. The current problem setting is the allocation of a large number of jobs required to be scheduled on multiple and identical machines which run in parallel. The due date of a job is characterized by a window frame of time, rather than a specific point in time. The performance of the eBPA is compared against Tabu Search (TS and Simulated Annealing (SA. SA and TS are well-known local search metaheuristic algorithms. The results show the potential of the eBPA as a metaheuristic algorithm.

Ant Foraging Behavior for Job Shop Problem

Directory of Open Access Journals (Sweden)

Mahad Diyana Abdul

2016-01-01

Full Text Available Ant Colony Optimization (ACO is a new algorithm approach, inspired by the foraging behavior of real ants. It has frequently been applied to many optimization problems and one such problem is in solving the job shop problem (JSP. The JSP is a finite set of jobs processed on a finite set of machine where once a job initiates processing on a given machine, it must complete processing and uninterrupted. In solving the Job Shop Scheduling problem, the process is measure by the amount of time required in completing a job known as a makespan and minimizing the makespan is the main objective of this study. In this paper, we developed an ACO algorithm to minimize the makespan. A real set of problems from a metal company in Johor bahru, producing 20 parts with jobs involving the process of clinching, tapping and power press respectively. The result from this study shows that the proposed ACO heuristics managed to produce a god result in a short time.

Integrated scheduled waste management system in Kuala Lumpur ...

African Journals Online (AJOL)

GREGORY

2011-12-16

Dec 16, 2011 ... Over the past decade, Malaysia has enjoyed tremendous growth in its economy. This has brought about a population growth together with a great influx of foreign workforce to the cities. This resulted in an increase in the amount of scheduled waste generated. Furthermore, scheduled waste management ...

Scheduling strategies for cycle scavenging in multicluster grid systems

NARCIS (Netherlands)

Sonmez, O.O.; Grundeken, B.; Mohamed, H.H.; Iosup, A.; Epema, D.H.J.

2009-01-01

The use of today's multicluster grids exhibits periods of submission bursts with periods of normal use and even of idleness. To avoid resource contention, many users employ observational scheduling, that is, they postpone the submission of relatively low-priority jobs until a cluster becomes

Analysis of Issues for Project Scheduling by Multiple, Dispersed Schedulers (distributed Scheduling) and Requirements for Manual Protocols and Computer-based Support

Science.gov (United States)

Richards, Stephen F.

1991-01-01

Although computerized operations have significant gains realized in many areas, one area, scheduling, has enjoyed few benefits from automation. The traditional methods of industrial engineering and operations research have not proven robust enough to handle the complexities associated with the scheduling of realistic problems. To address this need, NASA has developed the computer-aided scheduling system (COMPASS), a sophisticated, interactive scheduling tool that is in wide-spread use within NASA and the contractor community. Therefore, COMPASS provides no explicit support for the large class of problems in which several people, perhaps at various locations, build separate schedules that share a common pool of resources. This research examines the issue of distributing scheduling, as applied to application domains characterized by the partial ordering of tasks, limited resources, and time restrictions. The focus of this research is on identifying issues related to distributed scheduling, locating applicable problem domains within NASA, and suggesting areas for ongoing research. The issues that this research identifies are goals, rescheduling requirements, database support, the need for communication and coordination among individual schedulers, the potential for expert system support for scheduling, and the possibility of integrating artificially intelligent schedulers into a network of human schedulers.

Scheduling for decommissioning projects

International Nuclear Information System (INIS)

Podmajersky, O.E.

1987-01-01

This paper describes the Project Scheduling system being employed by the Decommissioning Operations Contractor at the Shippingport Station Decommissioning Project (SSDP). Results from the planning system show that the project continues to achieve its cost and schedule goals. An integrated cost and schedule control system (C/SCS) which uses the concept of earned value for measurement of performance was instituted in accordance with DOE orders. The schedule and cost variances generated by the C/SCS system are used to confirm management's assessment of project status. This paper describes the types of schedules and tools used on the SSDP project to plan and monitor the work, and identifies factors that are unique to a decommissioning project that make scheduling critical to the achievement of the project's goals. 1 fig

Program reference schedule baseline

International Nuclear Information System (INIS)

1986-07-01

This Program Reference Schedule Baseline (PRSB) provides the baseline Program-level milestones and associated schedules for the Civilian Radioactive Waste Management Program. It integrates all Program-level schedule-related activities. This schedule baseline will be used by the Director, Office of Civilian Radioactive Waste Management (OCRWM), and his staff to monitor compliance with Program objectives. Chapter 1 includes brief discussions concerning the relationship of the PRSB to the Program Reference Cost Baseline (PRCB), the Mission Plan, the Project Decision Schedule, the Total System Life Cycle Cost report, the Program Management Information System report, the Program Milestone Review, annual budget preparation, and system element plans. Chapter 2 includes the identification of all Level 0, or Program-level, milestones, while Chapter 3 presents and discusses the critical path schedules that correspond to those Level 0 milestones

Delivering integrated care to the frail elderly: The impact on professionals’ objective burden and job satisfaction

NARCIS (Netherlands)

B. Janse (Benjamin); R. Huijsman (Robbert); R.D.M. de Kuyper (Ruben Dennis Maurice); I.N. Fabbricotti (Isabelle)

2016-01-01

textabstractBackground: The impact of integrated working on professionals’ objective burden and job satisfaction was examined. An evidence-based intervention targeting frail elderly patients was implemented in the Walcheren region of the Netherlands in 2010. The intervention involved the primary

How job demands affect partners' experience of exhaustion : integrating work-family conflict and crossover theory

NARCIS (Netherlands)

Bakker, A.B.; Demerouti, E.; Dollard, M.F.

2008-01-01

This study among 168 couples of dual-earner parents uses insights from previous work-family conflict and crossover research to propose an integrative model delineating how job demands experienced by men and women carry over to the home domain. The authors hypothesized that for both men and women,

Optimizing integrated airport surface and terminal airspace operations under uncertainty

Science.gov (United States)

Bosson, Christabelle S.

In airports and surrounding terminal airspaces, the integration of surface, arrival and departure scheduling and routing have the potential to improve the operations efficiency. Moreover, because both the airport surface and the terminal airspace are often altered by random perturbations, the consideration of uncertainty in flight schedules is crucial to improve the design of robust flight schedules. Previous research mainly focused on independently solving arrival scheduling problems, departure scheduling problems and surface management scheduling problems and most of the developed models are deterministic. This dissertation presents an alternate method to model the integrated operations by using a machine job-shop scheduling formulation. A multistage stochastic programming approach is chosen to formulate the problem in the presence of uncertainty and candidate solutions are obtained by solving sample average approximation problems with finite sample size. The developed mixed-integer-linear-programming algorithm-based scheduler is capable of computing optimal aircraft schedules and routings that reflect the integration of air and ground operations. The assembled methodology is applied to a Los Angeles case study. To show the benefits of integrated operations over First-Come-First-Served, a preliminary proof-of-concept is conducted for a set of fourteen aircraft evolving under deterministic conditions in a model of the Los Angeles International Airport surface and surrounding terminal areas. Using historical data, a representative 30-minute traffic schedule and aircraft mix scenario is constructed. The results of the Los Angeles application show that the integration of air and ground operations and the use of a time-based separation strategy enable both significant surface and air time savings. The solution computed by the optimization provides a more efficient routing and scheduling than the First-Come-First-Served solution. Additionally, a data driven analysis is

How do employees prioritise when they schedule their own shifts?

DEFF Research Database (Denmark)

Nabe-Nielsen, Kirsten; Lund, Henrik; Hansen, Åse Marie

2013-01-01

to their family life, having consecutive time off, leisure-time activities, rest between shifts, sleep, regularity of their everyday life, health and that the work schedule balanced. Thus, employees consider both their own and the workplace's needs when they have the opportunity to schedule their own shifts. Age......We investigated how employees prioritised when they scheduled their own shifts and whether priorities depended on age, gender, educational level, cohabitation and health status. We used cross-sectional questionnaire data from the follow-up survey of an intervention study investigating the effect...... of self-scheduling (n = 317). Intervention group participants were asked about their priorities when scheduling their own shifts succeeded by 17 items covering family/private life, economy, job content, health and sleep. At least half of the participants reported that they were giving high priority...

Greedy and metaheuristics for the offline scheduling problem in grid computing

DEFF Research Database (Denmark)

Gamst, Mette

In grid computing a number of geographically distributed resources connected through a wide area network, are utilized as one computations unit. The NP-hard offline scheduling problem in grid computing consists of assigning jobs to resources in advance. In this paper, five greedy heuristics and two....... All heuristics solve instances with up to 2000 jobs and 1000 resources, thus the results are useful both with respect to running times and to solution values....

75 FR 28071 - Records Schedules; Availability and Request for Comments

Science.gov (United States)

2010-05-19

... authorized for disposal or reduce the retention period of records already authorized for disposal. NARA... this accumulation, agency records managers prepare schedules proposing retention periods for records... information concerning evaluations of enlisted personnel. Included are job ratings as well as information...

Network scheduling at Belene NPP construction site

International Nuclear Information System (INIS)

Matveev, A.

2010-01-01

Four types of schedules differing in the level of their detail are singled out to enhance the efficiency of Belene NPP Project implementation planning and monitoring: Level 1 Schedule–Summary Integrated Overall Time Schedule (SIOTS) is an appendix to EPC Contract. The main purpose of SIOTS is the large scale presentation of the current information on the Project implementation. Level 2 Schedule–Integrated Overall Time Schedule (IOTS)is the contract schedule for the Contractor (ASE JSC) and their subcontractors.The principal purpose of IOTS is the work progress planning and monitoring, the analysis of the effect of activities implementation upon the progress of the Project as a whole. IOTS is the reporting schedule at the Employer –Contractor level. Level 3 Schedules, Detail Time Schedules(DTS) are developed by those who actually perform the work and are agreed upon with Atomstroyexport JSC.The main purpose of DTS is the detail planning of Atomstroyexport subcontractor's activities. DTSare the reporting schedules at the level of Contractor-Subcontractor. Level 4 Schedules are the High Detail Time Schedules (HDTS), which are the day-to-day plans of work implementation and are developed, as a rule, for a week's time period.Each lower level time schedule details the activities of the higher level time schedule

Revisiting the NEH algorithm- the power of job insertion technique for optimizing the makespan in permutation flow shop scheduling

Directory of Open Access Journals (Sweden)

A. Baskar

2016-04-01

Full Text Available Permutation flow shop scheduling problems have been an interesting area of research for over six decades. Out of the several parameters, minimization of makespan has been studied much over the years. The problems are widely regarded as NP-Complete if the number of machines is more than three. As the computation time grows exponentially with respect to the problem size, heuristics and meta-heuristics have been proposed by many authors that give reasonably accurate and acceptable results. The NEH algorithm proposed in 1983 is still considered as one of the best simple, constructive heuristics for the minimization of makespan. This paper analyses the powerful job insertion technique used by NEH algorithm and proposes seven new variants, the complexity level remains same. 120 numbers of problem instances proposed by Taillard have been used for the purpose of validating the algorithms. Out of the seven, three produce better results than the original NEH algorithm.

WP 121 - Occupational segregation and gender inequality in job quality

OpenAIRE

Haya Stier; Yaish, M. (Meir)

2012-01-01

We examine gender differences in perceived quality of employment (achievement, content, job insecurity, job flexibility, and physical and emotional conditions). We ask whether women’s occupations provide better conditions in areas that facilitate their dual role in society, such as flexible working schedule, as a tradeoff for low monetary rewards. Specifically, we examine how closely women’s concentration in broader occupational categories, embedded in particular national contexts, is associa...

Problem specific heuristics for group scheduling problems in cellular manufacturing

OpenAIRE

Neufeld, Janis Sebastian

2016-01-01

The group scheduling problem commonly arises in cellular manufacturing systems, where parts are grouped into part families. It is characterized by a sequencing task on two levels: on the one hand, a sequence of jobs within each part family has to be identified while, on the other hand, a family sequence has to be determined. In order to solve this NP-hard problem usually heuristic solution approaches are used. In this thesis different aspects of group scheduling are discussed and problem spec...

An optimal algorithm for preemptive on-line scheduling

NARCIS (Netherlands)

Chen, B.; Vliet, van A.; Woeginger, G.J.

1995-01-01

We investigate the problem of on-line scheduling jobs on m identical parallel machines where preemption is allowed. The goal is to minimize the makespan. We derive an approximation algorithm with worst-case guarantee mm/(mm - (m - 1)m) for every m 2, which increasingly tends to e/(e - 1) ˜ 1.58 as m

DLTAP: A Network-efficient Scheduling Method for Distributed Deep Learning Workload in Containerized Cluster Environment

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Qiao Wei

2017-01-01

Full Text Available Deep neural networks (DNNs have recently yielded strong results on a range of applications. Training these DNNs using a cluster of commodity machines is a promising approach since training is time consuming and compute-intensive. Furthermore, putting DNN tasks into containers of clusters would enable broader and easier deployment of DNN-based algorithms. Toward this end, this paper addresses the problem of scheduling DNN tasks in the containerized cluster environment. Efficiently scheduling data-parallel computation jobs like DNN over containerized clusters is critical for job performance, system throughput, and resource utilization. It becomes even more challenging with the complex workloads. We propose a scheduling method called Deep Learning Task Allocation Priority (DLTAP which performs scheduling decisions in a distributed manner, and each of scheduling decisions takes aggregation degree of parameter sever task and worker task into account, in particularly, to reduce cross-node network transmission traffic and, correspondingly, decrease the DNN training time. We evaluate the DLTAP scheduling method using a state-of-the-art distributed DNN training framework on 3 benchmarks. The results show that the proposed method can averagely reduce 12% cross-node network traffic, and decrease the DNN training time even with the cluster of low-end servers.

Genetic programming for evolving due-date assignment models in job shop environments.

Science.gov (United States)

Nguyen, Su; Zhang, Mengjie; Johnston, Mark; Tan, Kay Chen

2014-01-01

Due-date assignment plays an important role in scheduling systems and strongly influences the delivery performance of job shops. Because of the stochastic and dynamic nature of job shops, the development of general due-date assignment models (DDAMs) is complicated. In this study, two genetic programming (GP) methods are proposed to evolve DDAMs for job shop environments. The experimental results show that the evolved DDAMs can make more accurate estimates than other existing dynamic DDAMs with promising reusability. In addition, the evolved operation-based DDAMs show better performance than the evolved DDAMs employing aggregate information of jobs and machines.

Robust Parallel Machine Scheduling Problem with Uncertainties and Sequence-Dependent Setup Time

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Hongtao Hu

2016-01-01

Full Text Available A parallel machine scheduling problem in plastic production is studied in this paper. In this problem, the processing time and arrival time are uncertain but lie in their respective intervals. In addition, each job must be processed together with a mold while jobs which belong to one family can share the same mold. Therefore, time changing mold is required for two consecutive jobs that belong to different families, which is known as sequence-dependent setup time. This paper aims to identify a robust schedule by min–max regret criterion. It is proved that the scenario incurring maximal regret for each feasible solution lies in finite extreme scenarios. A mixed integer linear programming formulation and an exact algorithm are proposed to solve the problem. Moreover, a modified artificial bee colony algorithm is developed to solve large-scale problems. The performance of the presented algorithm is evaluated through extensive computational experiments and the results show that the proposed algorithm surpasses the exact method in terms of objective value and computational time.

Integration of virtualized worker nodes in standard batch systems

International Nuclear Information System (INIS)

Buege, Volker; Kunze, Marcel; Oberst, Oliver; Quast, Guenter; Scheurer, Armin; Hessling, Hermann; Kemp, Yves; Synge, Owen

2010-01-01

Current experiments in HEP only use a limited number of operating system flavours. Their software might only be validated on one single OS platform. Resource providers might have other operating systems of choice for the installation of the batch infrastructure. This is especially the case if a cluster is shared with other communities, or communities that have stricter security requirements. One solution would be to statically divide the cluster into separated sub-clusters. In such a scenario, no opportunistic distribution of the load can be achieved, resulting in a poor overall utilization efficiency. Another approach is to make the batch system aware of virtualization, and to provide each community with its favoured operating system in a virtual machine. Here, the scheduler has full flexibility, resulting in a better overall efficiency of the resources. In our contribution, we present a lightweight concept for the integration of virtual worker nodes into standard batch systems. The virtual machines are started on the worker nodes just before jobs are executed there. No meta-scheduling is introduced. We demonstrate two prototype implementations, one based on the Sun Grid Engine (SGE), the other using Maui/Torque as a batch system. Both solutions support local job as well as Grid job submission. The hypervisors currently used are Xen and KVM, a port to another system is easily envisageable. To better handle different virtual machines on the physical host, the management solution VmImageManager is developed. We will present first experience from running the two prototype implementations. In a last part, we will show the potential future use of this lightweight concept when integrated into high-level (i.e. Grid) work-flows.

Planning and execution of jobs in nuclear power plants according to IWRS II. Pt. 1

International Nuclear Information System (INIS)

Hilmer, R.; Hauck, W.

1986-01-01

This paper deals with various efforts taken for a reduction of the radiation exposure of nuclear power plant staff. Health physics considerations range from the design of plants to include components requiring less time for maintenance and repair, to plant operation and optimization of job processes with special consideration of requirements made by radiation protection and maintenance. The paper presents in detail legal provisions and their translation into job process organization, job assignment and job schedulling. (HAG) [de

Maximum Lateness Scheduling on Two-Person Cooperative Games with Variable Processing Times and Common Due Date

OpenAIRE

Liu, Peng; Wang, Xiaoli

2017-01-01

A new maximum lateness scheduling model in which both cooperative games and variable processing times exist simultaneously is considered in this paper. The job variable processing time is described by an increasing or a decreasing function dependent on the position of a job in the sequence. Two persons have to cooperate in order to process a set of jobs. Each of them has a single machine and their processing cost is defined as the minimum value of maximum lateness. All jobs have a common due ...

Identical parallel machine scheduling with nonlinear deterioration and multiple rate modifying activities

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Ömer Öztürkoğlu

2017-07-01

Full Text Available This study focuses on identical parallel machine scheduling of jobs with deteriorating processing times and rate-modifying activities. We consider non linearly increasing processing times of jobs based on their position assignment. Rate modifying activities are also considered to recover the increase in processing times of jobs due to deterioration. We also propose heuristics algorithms that rely on ant colony optimization and simulated annealing algorithms to solve the problem with multiple RMAs in a reasonable amount of time. Finally, we show that ant colony optimization algorithm generates close optimal solutions and superior results than simulated annealing algorithm.

Job decision latitude, job demands, and cardiovascular disease: a prospective study of Swedish men.

Science.gov (United States)

Karasek, R; Baker, D; Marxer, F; Ahlbom, A; Theorell, T

1981-07-01

The association between specific job characteristics and subsequent cardiovascular disease was tested using a large random sample of the male working Swedish population. The prospective development of coronary heart disease (CHD) symptoms and signs was analyzed using a multivariate logistic regression technique. Additionally, a case-controlled study was used to analyze all cardiovascular-cerebrovascular (CHD-CVD) deaths during a six-year follow-up. The indicator of CHD symptoms and signs was validated in a six-year prospective study of CHD deaths (standardized mortality ratio 5.0; p less than or equal to .001). A hectic and psychologically demanding job increases the risk of developing CHD symptoms and signs (standardized odds ratio 1.29, p less than 0.25) and premature CHD-CVD death (relative risk 4.0, p less than .01). Low decision latitude-expressed as low intellectual discretion and low personal schedule freedom-is also associated with increased risk of cardiovascular disease. Low intellectual discretion predicts the development of CHD symptoms and signs (SOR 1.44, p less than .01), while low personal schedule freedom among the majority of workers with the minimum statutory education increases the risk of CHD-CVD death (RR 6.6, p less than .0002). The associations exist after controlling for age, education, smoking, and overweight.

Analysis of dispatching rules in a stochastic dynamic job shop manufacturing system with sequence-dependent setup times

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Sharma, Pankaj; Jain, Ajai

2014-12-01

Stochastic dynamic job shop scheduling problem with consideration of sequence-dependent setup times are among the most difficult classes of scheduling problems. This paper assesses the performance of nine dispatching rules in such shop from makespan, mean flow time, maximum flow time, mean tardiness, maximum tardiness, number of tardy jobs, total setups and mean setup time performance measures viewpoint. A discrete event simulation model of a stochastic dynamic job shop manufacturing system is developed for investigation purpose. Nine dispatching rules identified from literature are incorporated in the simulation model. The simulation experiments are conducted under due date tightness factor of 3, shop utilization percentage of 90% and setup times less than processing times. Results indicate that shortest setup time (SIMSET) rule provides the best performance for mean flow time and number of tardy jobs measures. The job with similar setup and modified earliest due date (JMEDD) rule provides the best performance for makespan, maximum flow time, mean tardiness, maximum tardiness, total setups and mean setup time measures.

Automated Planning and Scheduling for Space Mission Operations

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Chien, Steve; Jonsson, Ari; Knight, Russell

2005-01-01

Research Trends: a) Finite-capacity scheduling under more complex constraints and increased problem dimensionality (subcontracting, overtime, lot splitting, inventory, etc.) b) Integrated planning and scheduling. c) Mixed-initiative frameworks. d) Management of uncertainty (proactive and reactive). e) Autonomous agent architectures and distributed production management. e) Integration of machine learning capabilities. f) Wider scope of applications: 1) analysis of supplier/buyer protocols & tradeoffs; 2) integration of strategic & tactical decision-making; and 3) enterprise integration.

Solving the flexible job shop problem by hybrid metaheuristics-based multiagent model

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Nouri, Houssem Eddine; Belkahla Driss, Olfa; Ghédira, Khaled

2018-03-01

The flexible job shop scheduling problem (FJSP) is a generalization of the classical job shop scheduling problem that allows to process operations on one machine out of a set of alternative machines. The FJSP is an NP-hard problem consisting of two sub-problems, which are the assignment and the scheduling problems. In this paper, we propose how to solve the FJSP by hybrid metaheuristics-based clustered holonic multiagent model. First, a neighborhood-based genetic algorithm (NGA) is applied by a scheduler agent for a global exploration of the search space. Second, a local search technique is used by a set of cluster agents to guide the research in promising regions of the search space and to improve the quality of the NGA final population. The efficiency of our approach is explained by the flexible selection of the promising parts of the search space by the clustering operator after the genetic algorithm process, and by applying the intensification technique of the tabu search allowing to restart the search from a set of elite solutions to attain new dominant scheduling solutions. Computational results are presented using four sets of well-known benchmark literature instances. New upper bounds are found, showing the effectiveness of the presented approach.

Parallel-Machine Scheduling with Time-Dependent and Machine Availability Constraints

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Cuixia Miao

2015-01-01

Full Text Available We consider the parallel-machine scheduling problem in which the machines have availability constraints and the processing time of each job is simple linear increasing function of its starting times. For the makespan minimization problem, which is NP-hard in the strong sense, we discuss the Longest Deteriorating Rate algorithm and List Scheduling algorithm; we also provide a lower bound of any optimal schedule. For the total completion time minimization problem, we analyze the strong NP-hardness, and we present a dynamic programming algorithm and a fully polynomial time approximation scheme for the two-machine problem. Furthermore, we extended the dynamic programming algorithm to the total weighted completion time minimization problem.

Clustering and Genetic Algorithm Based Hybrid Flowshop Scheduling with Multiple Operations

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Yingfeng Zhang

2014-01-01

Full Text Available This research is motivated by a flowshop scheduling problem of our collaborative manufacturing company for aeronautic products. The heat-treatment stage (HTS and precision forging stage (PFS of the case are selected as a two-stage hybrid flowshop system. In HTS, there are four parallel machines and each machine can process a batch of jobs simultaneously. In PFS, there are two machines. Each machine can install any module of the four modules for processing the workpeices with different sizes. The problem is characterized by many constraints, such as batching operation, blocking environment, and setup time and working time limitations of modules, and so forth. In order to deal with the above special characteristics, the clustering and genetic algorithm is used to calculate the good solution for the two-stage hybrid flowshop problem. The clustering is used to group the jobs according to the processing ranges of the different modules of PFS. The genetic algorithm is used to schedule the optimal sequence of the grouped jobs for the HTS and PFS. Finally, a case study is used to demonstrate the efficiency and effectiveness of the designed genetic algorithm.

Influence of working conditions on job satisfaction in anaesthetists.

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Kinzl, J F; Knotzer, H; Traweger, C; Lederer, W; Heidegger, T; Benzer, A

2005-02-01

We studied job satisfaction, physical health, emotional well-being and working conditions in 125 Austrian and Swiss anaesthetists. Responses to self-reporting questionnaires were evaluated. Dependent variables included job satisfaction, emotional well-being and physical health. Independent variables included age, sex, marital status, position and working conditions as assessed by the Instrument for Stress-related Job Analysis. Control over work shows a strong effect on job satisfaction in anaesthetists, for example influence on handling tasks (P=0.001), time control (P=0.002) and participation (P=0.001), whereas task demands and task-related problems did not have any effect. Anaesthetists in leading positions and specialists reported lower job satisfaction (P=0.012) than did anaesthetists in non-leading positions. Job satisfaction was associated with better physical health (P=0.001) and better emotional well-being (P=0.005). Our results suggest that a high level of job satisfaction in anaesthetists correlates with interesting work demands and the opportunity to contribute skills and ideas. To improve job satisfaction, more attention should be paid to improving working conditions, including control over decision-making, and allowing anaesthetists to have more influence on their own work pace and work schedule.

A non-permutation flowshop scheduling problem with lot streaming: A Mathematical model

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Daniel Rossit

2016-06-01

Full Text Available In this paper we investigate the use of lot streaming in non-permutation flowshop scheduling problems. The objective is to minimize the makespan subject to the standard flowshop constraints, but where it is now permitted to reorder jobs between machines. In addition, the jobs can be divided into manageable sublots, a strategy known as lot streaming. Computational experiments show that lot streaming reduces the makespan up to 43% for a wide range of instances when compared to the case in which no job splitting is applied. The benefits grow as the number of stages in the production process increases but reach a limit. Beyond a certain point, the division of jobs into additional sublots does not improve the solution.

Job sharing: a viable option for the clinical nurse specialist.

Science.gov (United States)

Haibeck, S V; Howard, J L

1991-01-01

NUMEROUS WORK TIME options have been developed to attract, retain and meet the various needs of nurses. Job sharing, a work option little known to nurses, can be a successful alternative for balancing professional and personal lifestyle. The business literature supports job sharing and other innovative work options as successful mechanisms in retaining quality employees in their respective professions. After exploring the literature in this area, a proposal for job sharing the oncology clinical nurse specialist (CNS) position was presented to the Personnel Director and Vice President of Nursing at our institution. The proposal addressed the advantages and disadvantages of the concept. These included: (1) scheduling flexibility, (2) reduced absenteeism and turnover, (3) increased productivity, (4) handling fringe benefits, and (5) job satisfaction. The proposal was accepted, and the job sharing position has been successfully implemented for more than 2 years now. This paper describes issues relevant to designing and implementing job sharing in a CNS position.

Factors related to job burnout among nurses in the Razi Psychiatric Hospital, Iran.

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Rezaei, Omid; Habibi, Kamelia; Arab Ghahestany, Davood; Sayadnasiri, Mohammad; Armoon, Bahram; Khan, Vida; Fattah Moghadam, Ladan

2018-03-03

Background One of the most prevalent problems in work places that is considered as an important risk factor for the health of the employee is job burnout (JB). JB could be harmful to employees, their families and society. Therefore, decreasing JB among individuals and determining factors associated with it is important to improve the working environment and prevent its negative outcomes. This study aims to elicit the conditions and factors that cause job burnout among nurses of the Razi Psychiatric Hospital, Iran. Methods This study was a descriptive correlational and cross-sectional survey which the demographic and occupational burnout variables of nurses were measured. The study was conducted from January to April 2016. Accordingly, with a type I error probability of 0.05 and a power of 0.80, the sample size was determined to be 100 nurses for each group (men and women). Then, 200 were selected in the Razi Psychiatric Hospital (of whom approx. 60% worked in a rotating shift schedule). The data were collected in two phases: the first step was created by the authors, including gathering demographic data with questionnaire such as gender, age, marital status, education level, years of professional experience, hours of overtime working per month, shift schedules, and their working hospitals and wards. The second step was the Maslach burnout inventory (MBI), human services survey (HSS) version, developed by Maslach and Jackson to assess the three dimensions of burnout. Descriptive statistics (frequency distribution) were used for integrating the demographic variables. Additionally, logistical regression was applied to realize the association between demographic characteristics with the job burnout in SPSS software V.19. Results Our findings indicated that age, hours of work per week, nursing skills, management experience and work experiences accounted for 30% of the variance of depersonalization. Formal employment was significantly associated with emotional exhaustion

IMPACT OF E-RECRUITMENT AND JOB-SEEKERS PERCEPTION ON INTENTION TO PURSUE THE JOBS

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Naveed R. KHAN

2014-06-01

Full Text Available The study highlighted the significance of e-recruitment in the firms. In current epoch technology integrated the information in a sophisticated manner and has influenced on every setting of daily affaires. Hence job seekers are also get benefited with the internet era and start searching the jobs on internet. This study examined the relationship between the recruitment sources, job seekers’ perception and intention to pursue the job. Data was collected from 257 respondents and analysed in relation with the research objectives. The findings of the study showed that internet is the most preferred source to search the job among other recruitment sources. Furthermore, it is also suggested that the effectiveness of e-recruitment depends upon the placement of advertisement and salary is the most influential motivator to find interest in the job applied. Lastly, statistics of the study found that the recruitment sources and applicant’s perceptions of job significantly influence the intention to pursue the position applied by the job seeker.

Sport Tournament Automated Scheduling System

OpenAIRE

Raof R. A. A; Sudin S.; Mahrom N.; Rosli A. N. C

2018-01-01

The organizer of sport events often facing problems such as wrong calculations of marks and scores, as well as difficult to create a good and reliable schedule. Most of the time, the issues about the level of integrity of committee members and also issues about errors made by human came into the picture. Therefore, the development of sport tournament automated scheduling system is proposed. The system will be able to automatically generate the tournament schedule as well as automatically calc...

Spirituality and job satisfaction among hospice interdisciplinary team members.

Science.gov (United States)

Clark, Leah; Leedy, Stephen; McDonald, Laurie; Muller, Barbara; Lamb, Cheryl; Mendez, Tracy; Kim, Sehwan; Schonwetter, Ronald

2007-12-01

As a continuing effort to enhance the quality of palliative care for the dying, this study examined (1) the prevalence of spirituality among hospice interdisciplinary team (IDT) members; (2) whether spirituality is related to job satisfaction; and (3) the structural path relationships among four variables: spiritual belief, integration of spirituality at work, self actualization and job satisfaction. The study surveyed 215 hospice IDT members who completed the Jarel Spiritual Well-Being Scale, the Chamiec-Case Spirituality Integration and Job Satisfaction Scales. Multiple regression and structural path modeling methods were applied to explain the path relationships involving all four variables. The IDT members surveyed were: nurses, 46.4%; home health aids, 24.9%; social workers, 17.4%; chaplains, 4.2%; physicians, 2.3%; and other, 4.8%. Ninety-eight percent of the respondents viewed themselves as having spiritual well-being. On a 0-100 scale, IDT staff reported high spiritual belief (mean = 89.4) and they were self-actualizing (mean = 82.6). Most reported high job satisfaction (mean = 79.3) and spiritual integration (mean = 67.9). In multiple regression, spirituality, integration and self-actualization explained 22% of the variation in job satisfaction (R = 0.48; adjusted R(2) = 0.218; df = 3,175; F = 17.2; p = 0.001). Structural path models revealed that job satisfaction is more likely to be realized by a model that transforms one's spirituality into processes of integrating spirituality at work and self actualization (chi(2) = 0.614; df = 1; p = 0.433) than a model that establishes a direct path from spirituality to job satisfaction (chi(2) = 1.65; df = 1; p = 0.199). Hospice IDT member's integration of their spirituality at work and greater self actualization significantly improve job satisfaction.

Relationships among organizational family support, job autonomy, perceived control, and employee well-being.

Science.gov (United States)

Thompson, Cynthia A; Prottas, David J

2006-01-01

The authors analyzed data from the 2002 National Study of the Changing Workforce (N = 3,504) to investigate relationships among availability of formal organizational family support (family benefits and alternative schedules), job autonomy, informal organizational support (work-family culture, supervisor support, and coworker support), perceived control, and employee attitudes and well-being. Using hierarchical regression, the authors found that the availability of family benefits was associated with stress, life satisfaction, and turnover intentions, and the availability of alternative schedules was not related to any of the outcomes. Job autonomy and informal organizational support were associated with almost all the outcomes, including positive spillover. Perceived control mediated most of the relationships. Copyright 2006 APA.

The skill-divide in job quality: a cross-national analysis of 28 countries.

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Stier, Haya

2015-01-01

This study focuses on the skill divide in job quality and the role of social institutions in structuring the relation of workers' qualifications to the attributes of their jobs. Four measures of job quality are examined: job security, job achievement, job content and work schedule flexibility. The study is based on the 2005 ISSP module on work orientations and encompasses 28 countries. Obtained through multilevel modeling, the findings show that low-skilled workers are disadvantaged in all aspects of job quality. However, skill inequality in the quality of employment depends on countries' characteristics, with declining inequality in countries at higher levels of technological development and to some extent also in times of technological growth. At times of high unemployment, skill disparities in job security widen while on other measures of job quality they decline. Under high market regulation, the low skilled enjoy better job security but on other measures, skill inequalities increase. Copyright © 2014 Elsevier Inc. All rights reserved.

Scheduling multimedia services in cloud computing environment

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Liu, Yunchang; Li, Chunlin; Luo, Youlong; Shao, Yanling; Zhang, Jing

2018-02-01

Currently, security is a critical factor for multimedia services running in the cloud computing environment. As an effective mechanism, trust can improve security level and mitigate attacks within cloud computing environments. Unfortunately, existing scheduling strategy for multimedia service in the cloud computing environment do not integrate trust mechanism when making scheduling decisions. In this paper, we propose a scheduling scheme for multimedia services in multi clouds. At first, a novel scheduling architecture is presented. Then, We build a trust model including both subjective trust and objective trust to evaluate the trust degree of multimedia service providers. By employing Bayesian theory, the subjective trust degree between multimedia service providers and users is obtained. According to the attributes of QoS, the objective trust degree of multimedia service providers is calculated. Finally, a scheduling algorithm integrating trust of entities is proposed by considering the deadline, cost and trust requirements of multimedia services. The scheduling algorithm heuristically hunts for reasonable resource allocations and satisfies the requirement of trust and meets deadlines for the multimedia services. Detailed simulated experiments demonstrate the effectiveness and feasibility of the proposed trust scheduling scheme.

Solving a mathematical model integrating unequal-area facilities layout and part scheduling in a cellular manufacturing system by a genetic algorithm.

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Ebrahimi, Ahmad; Kia, Reza; Komijan, Alireza Rashidi

2016-01-01

In this article, a novel integrated mixed-integer nonlinear programming model is presented for designing a cellular manufacturing system (CMS) considering machine layout and part scheduling problems simultaneously as interrelated decisions. The integrated CMS model is formulated to incorporate several design features including part due date, material handling time, operation sequence, processing time, an intra-cell layout of unequal-area facilities, and part scheduling. The objective function is to minimize makespan, tardiness penalties, and material handling costs of inter-cell and intra-cell movements. Two numerical examples are solved by the Lingo software to illustrate the results obtained by the incorporated features. In order to assess the effects and importance of integration of machine layout and part scheduling in designing a CMS, two approaches, sequentially and concurrent are investigated and the improvement resulted from a concurrent approach is revealed. Also, due to the NP-hardness of the integrated model, an efficient genetic algorithm is designed. As a consequence, computational results of this study indicate that the best solutions found by GA are better than the solutions found by B&B in much less time for both sequential and concurrent approaches. Moreover, the comparisons between the objective function values (OFVs) obtained by sequential and concurrent approaches demonstrate that the OFV improvement is averagely around 17 % by GA and 14 % by B&B.

Physical and Organizational Job Stressors in Pregnancy and Associations With Primary Cesarean Deliveries.

Science.gov (United States)

Guendelman, Sylvia; Gemmill, Alison; Hosang, Nap; MacDonald, Leslie A

2017-06-01

The aim of this study was to assess the relationship between exposure to physical and organizational job stressors during pregnancy and cesarean delivery. We sampled 580 employed women in California who participated in a nested population-based case-control study of birth outcomes. Adjusted multivariate regression analyses estimated associations between heavy lifting, frequent bending, high noise, extreme temperature, prolonged standing and organizational stressors (shift work, inflexible schedules, effort-reward ratio), and primary cesarean (vs vaginal) delivery, controlling for covariates. Women occupationally exposed had higher odds of cesarean. Those exposed to daily manual lifting more than 15 pounds [adjusted odds ratio = 2.54; 95% confidence interval (95% CI) 1.21 to 5.32] and at least four physical job stressors (adjusted odds ratio = 3.49; 95% CI 1.21 to 10.09) had significantly elevated odds of cesarean delivery. Exposed morbid women experienced greater risk; risk was lower among those with schedule flexibility. Associations were found between modifiable exposure to physical job stressors during pregnancy and cesarean delivery.

Integrated care for mental health social inclusion through job placement: Implementing IPS in Spain

OpenAIRE

Koatz, Débora; Hilarión, Pilar; Bonet, Pere; Suñol, Rosa

2016-01-01

Introduction: Individual Placement and Support (IPS) is an integrated social, labor and mental health intervention with an important component of evidence for its effectiveness in helping people with severe mental disorders. Its objective is to obtain and maintain competitive jobs, increase social inclusion and quality of life, and while consuming fewer resources. In Europe, IPS model (which began 14 year ago) is currently implemented in four countries which share background with Dartmouth Co...

How do employees prioritise when they schedule their own shifts?

Science.gov (United States)

Nabe-Nielsen, Kirsten; Lund, Henrik; Ajslev, Jeppe Z; Hansen, Åse Marie; Albertsen, Karen; Hvid, Helge; Garde, Anne Helene

2013-01-01

We investigated how employees prioritised when they scheduled their own shifts and whether priorities depended on age, gender, educational level, cohabitation and health status. We used cross-sectional questionnaire data from the follow-up survey of an intervention study investigating the effect of self-scheduling (n = 317). Intervention group participants were asked about their priorities when scheduling their own shifts succeeded by 17 items covering family/private life, economy, job content, health and sleep. At least half of the participants reported that they were giving high priority to their family life, having consecutive time off, leisure-time activities, rest between shifts, sleep, regularity of their everyday life, health and that the work schedule balanced. Thus, employees consider both their own and the workplace's needs when they have the opportunity to schedule their own shifts. Age, gender, cohabitation and health status were all significantly associated with at least one of these priorities. Intervention studies report limited health effects of self-scheduling. Therefore, we investigated to what extent employees prioritise their health and recuperation when scheduling their own shifts. We found that employees not only consider both their health and family but also the workplace's needs when they schedule their own shifts.

A new self-scheduling strategy for integrated operation of wind and pumped-storage power plants in power markets

International Nuclear Information System (INIS)

Varkani, Ali Karimi; Daraeepour, Ali; Monsef, Hassan

2011-01-01

Highlights: → A strategy for integrated operation of wind and pumped-storage plants is proposed. → Participation of both plants in energy and ancillary service markets is modeled. → The uncertainty of wind production is modeled by a novel probabilistic function. → The proposed strategy is tested on a real case in the Spanish electricity market. -- Abstract: Competitive structure of power markets causes various challenges for wind resources to participate in these markets. Indeed, production uncertainty is the main cause of their low income. Thus, they are usually supported by system operators, which is in contrast with the competitive paradigm of power markets. In this paper, a new strategy for increasing the profits of wind resources is proposed. In the suggested strategy, a Generation Company (GenCo), who owns both wind and pumped-storage plants, self-schedules the integrated operation of them regarding the uncertainty of wind power generation. For presenting an integrated self-schedule and obtaining a real added value of the strategy, participation of the GenCo in energy and ancillary service markets is modeled. The self-scheduling strategy is based on stochastic programming techniques. Outputs of the problem include generation offers in day-ahead energy market and ancillary service markets, including spinning and regulation reserve markets. A Neural Network (NN) based technique is used for modeling the uncertainty of wind power production. The proposed strategy is tested on a real wind farm in mainland, Spain. Moreover, added value of the strategy is presented in different conditions of the market.

Job-sharing in nuclear medicine: an 8-year experience (1998-2006).

Science.gov (United States)

Als, Claudine; Brautigam, Peter

2006-01-01

Job-sharing is generally defined as a situation in which a single professional position is held in common by two separate individuals, who alternatively, on a timely basis, deal with the workload and the responsibilities. The aim of the present paper is to discuss prerequisites and characteristics of job-sharing by medical doctors and implications in a department of nuclear medicine. Job-sharing facilitates the combination of family life with professional occupation and prevents burnout. The time schedule applied by job-sharers is relevant: will both partners work for half-days, half-weeks, or rather alternatively during one to two consecutive weeks? This crucial choice, depending on personal as well as on professional circumstances, certainly influences the workflow of the department.

Flow shop scheduling with heterogeneous workers

OpenAIRE

Benavides, Alexander J.; Ritt, Marcus; Miralles Insa, Cristóbal Javier

2014-01-01

We propose an extension to the flow shop scheduling problem named Heterogeneous Flow Shop Scheduling Problem (Het-FSSP), where two simultaneous issues have to be resolved: finding the best worker assignment to the workstations, and solving the corresponding scheduling problem. This problem is motivated by Sheltered Work centers for Disabled, whose main objective is the labor integration of persons with disabilities, an important aim not only for these centers but for any company d...

Working multiple jobs over a day or a week: Short-term effects on sleep duration.

Science.gov (United States)

Marucci-Wellman, Helen R; Lombardi, David A; Willetts, Joanna L

Approximately 10% of the employed population in the United States works in multiple jobs. They are more likely to work long hours and in nonstandard work schedules, factors known to impact sleep duration and quality, and increase the risk of injury. In this study we used multivariate regression models to compare the duration of sleep in a 24-hour period between workers working in multiple jobs (MJHs) with single job holders (SJHs) controlling for other work schedule and demographic factors. We used data from the Bureau of Labor Statistics US American Time Use Survey (ATUS) pooled over a 9-year period (2003-2011). We found that MJHs had significantly reduced sleep duration compared with SJHs due to a number of independent factors, such as working longer hours and more often late at night. Male MJHs, working in their primary job or more than one job on the diary day, also had significantly shorter sleep durations (up to 40 minutes less on a weekend day) than male SJHs, even after controlling for all other factors. Therefore, duration of work hours, time of day working and duration of travel for work may not be the only factors to consider when understanding if male MJHs are able to fit in enough recuperative rest from their busy schedule. Work at night had the greatest impact on sleep duration for females, reducing sleep time by almost an hour compared with females who did not work at night. We also hypothesize that the high frequency or fragmentation of non-leisure activities (e.g. work and travel for work) throughout the day and between jobs may have an additional impact on the duration and quality of sleep for MJHs.

Integrating GRID tools to build a computing resource broker: activities of DataGrid WP1

International Nuclear Information System (INIS)

Anglano, C.; Barale, S.; Gaido, L.; Guarise, A.; Lusso, S.; Werbrouck, A.

2001-01-01

Resources on a computational Grid are geographically distributed, heterogeneous in nature, owned by different individuals or organizations with their own scheduling policies, have different access cost models with dynamically varying loads and availability conditions. This makes traditional approaches to workload management, load balancing and scheduling inappropriate. The first work package (WP1) of the EU-funded DataGrid project is addressing the issue of optimizing the distribution of jobs onto Grid resources based on a knowledge of the status and characteristics of these resources that is necessarily out-of-date (collected in a finite amount of time at a very loosely coupled site). The authors describe the DataGrid approach in integrating existing software components (from Condor, Globus, etc.) to build a Grid Resource Broker, and the early efforts to define a workable scheduling strategy

Scheduling Additional Train Unit Services on Rail Transit Lines

OpenAIRE

Zhibin Jiang; Yuyan Tan; Özgür Yalçınkaya

2014-01-01

This paper deals with the problem of scheduling additional train unit (TU) services in a double parallel rail transit line, and a mixed integer programming (MIP) model is formulated for integration strategies of new trains connected by TUs with the objective of obtaining higher frequencies in some special sections and special time periods due to mass passenger volumes. We took timetable scheduling and TUs scheduling as an integrated optimization model with two objectives: minimizing travel ti...

Enhanced round robin CPU scheduling with burst time based time quantum

Science.gov (United States)

Indusree, J. R.; Prabadevi, B.

2017-11-01

Process scheduling is a very important functionality of Operating system. The main-known process-scheduling algorithms are First Come First Serve (FCFS) algorithm, Round Robin (RR) algorithm, Priority scheduling algorithm and Shortest Job First (SJF) algorithm. Compared to its peers, Round Robin (RR) algorithm has the advantage that it gives fair share of CPU to the processes which are already in the ready-queue. The effectiveness of the RR algorithm greatly depends on chosen time quantum value. Through this research paper, we are proposing an enhanced algorithm called Enhanced Round Robin with Burst-time based Time Quantum (ERRBTQ) process scheduling algorithm which calculates time quantum as per the burst-time of processes already in ready queue. The experimental results and analysis of ERRBTQ algorithm clearly indicates the improved performance when compared with conventional RR and its variants.

Preparing the Gaudi framework and the DIRAC WMS for multicore job submission

International Nuclear Information System (INIS)

Rauschmayr, N; Streit, A

2014-01-01

HEP applications need to adapt to the continuously increasing number of cores on modern CPUs. This must be done at different levels: the software must support parallelization, and the scheduling has to differ between multicore and singlecore jobs. The LHCb software framework (GAUDI) provides a parallel prototype (GaudiMP), based on the multiprocessing approach. It allows a reduction of the overall memory footprint and a coordinated access to data via separated reader and writer processes. A comparison between the parallel prototype and multiple independent Gaudi jobs in respect of CPU time and memory consumption will be shown. Furthermore, speedup must be predicted in order to find the limit beyond which the parallel prototype (GaudiMP) does not bring further scaling. This number must be known as it indicates the point, where new technologies must be introduced into the software framework. In order to reach further improvements in the overall throughput, scheduling strategies for mixing parallel jobs can be applied. It allows overcoming limitations in the speedup of the parallel prototype. Those changes require modifications at the level of the Workload Management System (DIRAC).

Solving a supply chain scheduling problem with non-identical job sizes and release times by applying a novel effective heuristic algorithm

Science.gov (United States)

Pei, Jun; Liu, Xinbao; Pardalos, Panos M.; Fan, Wenjuan; Wang, Ling; Yang, Shanlin

2016-03-01

Motivated by applications in manufacturing industry, we consider a supply chain scheduling problem, where each job is characterised by non-identical sizes, different release times and unequal processing times. The objective is to minimise the makespan by making batching and sequencing decisions. The problem is formalised as a mixed integer programming model and proved to be strongly NP-hard. Some structural properties are presented for both the general case and a special case. Based on these properties, a lower bound is derived, and a novel two-phase heuristic (TP-H) is developed to solve the problem, which guarantees to obtain a worst case performance ratio of ?. Computational experiments with a set of different sizes of random instances are conducted to evaluate the proposed approach TP-H, which is superior to another two heuristics proposed in the literature. Furthermore, the experimental results indicate that TP-H can effectively and efficiently solve large-size problems in a reasonable time.

Application of remote debugging techniques in user-centric job monitoring

International Nuclear Information System (INIS)

Dos Santos, T; Mättig, P; Harenberg, T; Volkmer, F; Beermann, T; Kalinin, S; Ahrens, R; Wulff, N

2012-01-01

With the Job Execution Monitor, a user-centric job monitoring software developed at the University of Wuppertal and integrated into the job brokerage systems of the WLCG, job progress and grid worker node health can be supervised in real time. Imminent error conditions can thus be detected early by the submitter and countermeasures can be taken. Grid site admins can access aggregated data of all monitored jobs to infer the site status and to detect job misbehaviour. To remove the last 'blind spot' from this monitoring, a remote debugging technique based on the GNU C compiler suite was developed and integrated into the software; its design concept and architecture is described in this paper and its application discussed.

Power Minimization for Parallel Real-Time Systems with Malleable Jobs and Homogeneous Frequencies

OpenAIRE

Paolillo, Antonio; Goossens, Joël; Hettiarachchi, Pradeep M.; Fisher, Nathan

2014-01-01

In this work, we investigate the potential benefit of parallelization for both meeting real-time constraints and minimizing power consumption. We consider malleable Gang scheduling of implicit-deadline sporadic tasks upon multiprocessors. By extending schedulability criteria for malleable jobs to DVFS-enabled multiprocessor platforms, we are able to derive an offline polynomial-time optimal processor/frequency-selection algorithm. Simulations of our algorithm on randomly generated task system...

A review of scheduling problem and resolution methods in flexible flow shop

Directory of Open Access Journals (Sweden)

Tian-Soon Lee

2019-01-01

Full Text Available The Flexible flow shop (FFS is defined as a multi-stage flow shops with multiple parallel machines. FFS scheduling problem is a complex combinatorial problem which has been intensively studied in many real world industries. This review paper gives a comprehensive exploration review on the FFS scheduling problem and guides the reader by considering and understanding different environmental assumptions, system constraints and objective functions for future research works. The published papers are classified into two categories. First is the FFS system characteristics and constraints including the problem differences and limitation defined by different studies. Second, the scheduling performances evaluation are elaborated and categorized into time, job and multi related objectives. In addition, the resolution approaches that have been used to solve FFS scheduling problems are discussed. This paper gives a comprehensive guide for the reader with respect to future research work on the FFS scheduling problem.

Looking for a New Sport That Pays Well? Consider the Game of Federal Job Search.

Science.gov (United States)

Troutman, Kathryn Kraemer

This paper compares searching for a Federal Job to taking up a new sport. Becoming good at a sport takes lessons and coaching, study of the rules, practice, investment in equipment and special clothes, time to play, scheduling, and ongoing interest with friend who enjoy the same sport. An Expert Player/Jobseeker in the Federal Job Search System…

A Comparison of Training Experience, Training Satisfaction, and Job Search Experiences between Integrated Vascular Surgery Residency and Traditional Vascular Surgery Fellowship Graduates.

Science.gov (United States)

Colvard, Benjamin; Shames, Murray; Schanzer, Andres; Rectenwald, John; Chaer, Rabih; Lee, Jason T

2015-10-01

The first 2 integrated vascular residents in the United States graduated in 2012, and in 2013, 11 more entered the job market. The purpose of this study was to compare the job search experiences of the first cohort of integrated 0 + 5 graduates to their counterparts completing traditional 5 + 2 fellowship programs. An anonymous, Web-based, 15-question survey was sent to all 11 graduating integrated residents in 2013 and to the 25 corresponding 5 + 2 graduating fellows within the same institution. Questions focused on the following domains: training experience, job search timelines and outcomes, and overall satisfaction with each training paradigm. Survey response was nearly 81% for the 0 + 5 graduates and 64% for the 5 + 2 graduates. Overall, there was no significant difference between residents and fellows in the operative experience obtained as measured by the number of open and endovascular cases logged. Dedicated research time during the entire training period was similar between residents and fellows. Nearly all graduates were extremely satisfied with their training and had positive experiences during their job searches with respect to starting salaries, numbers of offers, and desired practice type. More 0 + 5 residents chose academic and mixed practices over private practices compared with 5 + 2 fellowship graduates. Although longer term data are needed to understand the impact of the addition of 0 + 5 graduating residents to the vascular surgery work force, preliminary survey results suggest that both training paradigms (0 + 5 and 5 + 2) provide positive training experiences that result in excellent job search experiences. Based on the current and future need for vascular surgeons in the work force, the continued growth and expansion of integrated 0 + 5 vascular surgery residency positions as an alternative to traditional fellowship training is thus far justified. Copyright © 2015 Elsevier Inc. All rights reserved.

Computer-aided resource planning and scheduling for radiological services

Science.gov (United States)

Garcia, Hong-Mei C.; Yun, David Y.; Ge, Yiqun; Khan, Javed I.

1996-05-01

There exists tremendous opportunity in hospital-wide resource optimization based on system integration. This paper defines the resource planning and scheduling requirements integral to PACS, RIS and HIS integration. An multi-site case study is conducted to define the requirements. A well-tested planning and scheduling methodology, called Constrained Resource Planning model, has been applied to the chosen problem of radiological service optimization. This investigation focuses on resource optimization issues for minimizing the turnaround time to increase clinical efficiency and customer satisfaction, particularly in cases where the scheduling of multiple exams are required for a patient. How best to combine the information system efficiency and human intelligence in improving radiological services is described. Finally, an architecture for interfacing a computer-aided resource planning and scheduling tool with the existing PACS, HIS and RIS implementation is presented.

Job Satisfaction: Insights from Home Support Care Workers in Three Canadian Jurisdictions.

Science.gov (United States)

Panagiotoglou, Dimitra; Fancey, Pamela; Keefe, Janice; Martin-Matthews, Anne

2017-03-01

This mixed-methods study identified the personal and workplace characteristics that drive the job satisfaction of home support workers (HSWs) providing assistance to elderly clients. Data were based on a standardized measure of job satisfaction, along with in-depth qualitative interviews with 176 home support workers from three Canadian provincial jurisdictions (British Columbia, n = 108; Ontario, n = 28; Nova Scotia, n = 40). We anticipated that variability in demographic profiles between the three groups of workers and different job descriptions would be associated with differences in perceived job satisfaction. This was not the case. Results from the qualitative analysis highlight key areas that contributed to job satisfaction. These are job (scheduling, travel, and safety), economic (income security), and organizational (communication, support, and respect) factors. Given these findings, we recommend improvements to workplace communication, increased travel time allowance between clients, and wage parity with equivalent positions in long-term care facilities.

Flow-shop scheduling problem under uncertainties: Review and trends