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 Journal of Information Technology and Application in Education       (Followers: 16) Journal of Information Technology Research       (Followers: 3) Journal of Informetrics       (Followers: 7) Journal of Infrared, Millimeter and Terahertz Waves       (Followers: 1) Journal of Intelligent Manufacturing       (Followers: 5) Journal of Intelligent Procedures in Electrical Technology Journal of Interaction Science Journal of Interactive Humanities       (Followers: 1) Journal of Interactive Marketing       (Followers: 6) Journal of Interactive Media in Education       (Followers: 5) Journal of K-Theory       (Followers: 1) Journal of Kufa for Mathematics and Computer Journal of Laboratory Automation Journal of Language Modelling Journal of Law, Information and Science       (Followers: 25) Journal of Location Based Services       (Followers: 3) Journal of Logic and Computation Journal of Manufacturing Systems       (Followers: 6) Journal of Material Cycles and Waste Management       (Followers: 2) Journal of mathematical and computational science       (Followers: 5) Journal of Mathematical Imaging and Vision       (Followers: 2) Journal of Mechatronics       (Followers: 1) Journal of Medical Systems       (Followers: 2) Journal of Metallurgy       (Followers: 4) Journal of Mobile, Embedded and Distributed Systems       (Followers: 3) Journal of Molecular Structure       (Followers: 3) Journal of Multimedia       (Followers: 2) Journal of Multivariate Analysis       (Followers: 7) Journal of Nanoparticle Research       (Followers: 2) Journal of Network and Computer Applications       (Followers: 4) Journal of Network and Systems Management Journal of Networks       (Followers: 4) Journal of Neural Engineering       (Followers: 6) Journal of Neural Transmission       (Followers: 2) Journal of Number Theory       (Followers: 1) Journal of Optical and Fiber Communications Reports       (Followers: 2) Journal of Optimization Theory and Applications       (Followers: 2) Journal of Organizational and End User Computing       (Followers: 2) Journal of Organizational Behavior       (Followers: 35) Journal of Organizational Computing and Electronic Commerce       (Followers: 2) Journal of Parallel and Distributed Computing       (Followers: 7) Journal of Policy Analysis and Management       (Followers: 12) Journal of Process Control       (Followers: 2) Journal of Proteome Science and Computational Biology Journal of Real-Time Image Processing       (Followers: 5) Journal of Revenue and Pricing Management       (Followers: 6) Journal of Scheduling       (Followers: 1) Journal of Science and Technology of the Arts       (Followers: 2) Journal of Scientific Computing       (Followers: 3) Journal of Second Language Writing       (Followers: 14) Journal of Sensor Technology       (Followers: 3) Journal of Sensors       (Followers: 9) Journal of Signal Processing Systems Journal of Software       (Followers: 2) Journal of Software : Evolution and Process       (Followers: 4) Journal of Software Engineering       (Followers: 6) Journal of Solar Energy Engineering       (Followers: 16) Journal of Spatial Information Science       (Followers: 1) Journal of Statistical Software       (Followers: 11) Journal of Symbolic Computation Journal of Systems and Software       (Followers: 7) Journal of Systems Architecture       (Followers: 3) Journal of Systems Integration       (Followers: 1) Journal of Systems Science and Complexity       (Followers: 6) Journal of Systems Science and Systems Engineering       (Followers: 2) Journal of the ACM       (Followers: 3) Journal of the Association for History and Computing       (Followers: 6) Journal of the Brazilian Computer Society Journal of the Text Encoding Initiative       (Followers: 1) Journal of Theoretical and Computational Chemistry       (Followers: 8) Journal of Transplantation       (Followers: 4) Journal of Transportation Systems Engineering and Information Technology       (Followers: 14) Journal of Turbulence       (Followers: 1) Journal of Urban Regeneration & Renewal       (Followers: 17) Journal of Visual Communication and Image Representation       (Followers: 7) Journal of VLSI Design Tools & Technology       (Followers: 2) Journal of Water and Land Development       (Followers: 1) Journal of Zhejiang University SCIENCE C Journal on Chain and Network Science       (Followers: 3) Journal on Data Semantics       (Followers: 2) Journal on Multimodal User Interfaces       (Followers: 4) Jurnal Ilmu Komputer dan Informasi Jurnal Informatika       (Followers: 2) Jurnal Informatika       (Followers: 3) Jurnal INKOM : Jurnal Informatika, Sistem Kendali dan Komputer       (Followers: 1) Jurnal Sistem Komputer Jurnal Teknologi       (Followers: 2) Karbala International Journal of Modern Science KI - Künstliche Intelligenz Knowledge and Information Systems       (Followers: 13) Knowledge Management Research & Practice       (Followers: 20) Kybernetes       (Followers: 1) Landscape and Ecological Engineering       (Followers: 3) Language & Communication       (Followers: 15) Language Resources and Evaluation       (Followers: 6) Latin American Journal of Computing Learning Technologies, IEEE Transactions on       (Followers: 10) Lecture Notes in Computer Science       (Followers: 1) Legal Theory       (Followers: 7) Leonardo       (Followers: 11)
 Journal of Scheduling   [SJR: 1.417]   [H-I: 38]   [1 followers]  Follow         Hybrid journal (It can contain Open Access articles)    ISSN (Print) 1099-1425 - ISSN (Online) 1094-6136    Published by Springer-Verlag  [2281 journals]
• Improved upper bounds for online malleable job scheduling
• Abstract: Abstract In this paper, we study online algorithms that schedule malleable jobs, i.e., jobs that can be parallelized on any subset of the available $$m$$ identical machines. We study a model that accounts for the tradeoff between multiprocessor speedup and overhead time, namely, if job $$j$$ has processing requirement $$p_j$$ and is assigned to run on $$k_j$$ machines, then $$j$$ ’s execution time becomes $$p_j/k_j + (k_j -1)c$$ , where $$c$$ is a constant parameter to the problem. For $$m=2$$ , we present an online algorithm OCS that has a strong competitive ratio of 3/2, matching a previously established lower bound. We also present an online algorithm ASYM2 that is asymptotically $$((4-\epsilon )/(3-\epsilon ))$$ -competitive when $$m=2$$ , where $$0 < \epsilon \le 2$$ is a parameter to the algorithm, improving upon an existing asymptotically (3/2)-competitive algorithm. Finally, we present an online algorithm OTO that is strongly $$2$$ -competitive when $$m = 3$$ , improving upon the previous best upper bound of $$9/4$$ .
PubDate: 2015-08-01

• Two-machine interval shop scheduling with time lags
• Abstract: Abstract We introduce and analyze the interval shop scheduling problem, where the objective is to maximize the weighted number of jobs that can be processed in a two-stage flow shop, job shop, or open shop, where each job has a fixed start and end time and requires a given transportation time, i.e., a time lag, for moving from one stage to the other. This problem is a natural extension of the parallel-machine scheduling problem with fixed start and end times, which is relatively well understood. We prove that the two-machine interval flow shop problem is $$\mathcal{NP }$$ -hard in the strong sense for general time lags, even in the case of equal processing times and equal weights. The problem is solvable in polynomial time if all time lags are equal. The two-machine interval job shop problem is solvable in $$O(n^3)$$ time if the time lags are equal and relatively small. For the two-machine interval open shop problem, this is true as well.
PubDate: 2015-08-01

• New perspectives in scheduling theory
• PubDate: 2015-08-01

• Generating class schedules within a complex modular environment with
application to secondary schools
• Abstract: Abstract Westside High School (WHS) of Omaha, Nebraska utilizes a sophisticated scheduling environment called “modular scheduling.” Modular scheduling empowers teachers with the ability to design the structure of their classes by adjusting the frequency, duration, and location of each of their lessons. This paper presents a novel heuristic methodology, implemented as a computer program called the sequential modular algorithmic routines for timetabling (SMART) Scheduler, which creates cohesive modular class schedules using effective techniques such as ejection trees and student sectioning. In experimentation, the SMART Scheduler is able to schedule over 2,800 distinct lessons in less than 4 s using data provided by WHS. This paper describes algorithms within the SMART Scheduler as well as computational results of its implementation.
PubDate: 2015-08-01

• Flowshop scheduling with interstage job transportation
• Abstract: Abstract There are a variety of joint job production and transportation scheduling problems that arise in modern manufacturing systems. In this paper, we study two such problems that arise in a flowshop environment where there are two processing stages and a single transporter that is available to deliver the finished jobs from the first stage to the second. In the first problem, there is a single machine in each of the two flowshop stages and jobs have different sizes when loaded onto the transporter. In the second problem, there are two parallel machines in the first stage and a single machine in the second stage, and the transporter can carry only one job in each shipment. The objective of both problems is to minimize the makespan, i.e., the completion time of the last job in the second stage. The two problems are both strongly NP-hard. For each problem, we propose a fast heuristic and show that the heuristic has a tight worst-case bound of 2.
PubDate: 2015-08-01

• Two-agent scheduling with agent specific batches on an unbounded serial
batching machine
• Abstract: Abstract We study a scheduling problem, in which jobs of two agents are performed in agent specific batches on the same serial unbounded batching machine. On this machine, jobs of the same batch complete simultaneously, and the batch processing time is equal to the total processing time of its jobs plus a setup time. Each agent aims at minimizing a function which depends only on the completion times of its jobs. The problem is to find a schedule that minimizes the objective function of one agent, subject to the objective function of the other agent does not exceed a given threshold. The problem appears in optimizing product consolidation operations of a cross-docking distribution center. Polynomial and pseudo-polynomial dynamic programming algorithms are derived for settings with various combinations of the objective functions.
PubDate: 2015-08-01

• Scheduling parallel batch jobs in grids with evolutionary metaheuristics
• Abstract: Abstract In this paper we propose an efficient offline job scheduling algorithm working in a grid environment that is based on a relatively new evolutionary metaheuristic called generalized extremal optimization (GEO). We compare our experimental results with those obtained using a very popular evolutionary metaheuristic, the genetic algorithm (GA). The scheduling algorithm implies two-stage scheduling. In the first stage, the algorithm allocates jobs to suitable machines of a grid; GEO/GA is used for this purpose. In the second stage, jobs are independently scheduled on each machine; this is performed with a variant of a list scheduling algorithm. Both GEO and GA belong to the class of evolutionary algorithms, but GEO is much simpler and requires the tuning of only one parameter, whereas GA requires the tuning of several parameters. The results of the experimental study show that GEO, despite its simplicity, outperforms the GA in a whole range of scheduling instances and is much easier to use.
PubDate: 2015-08-01

• Scheduling semi-malleable jobs to minimize mean flow time
• Abstract: Abstract This paper deals with the problem of scheduling $$n_\mathrm{A}$$ malleable and $$n_\mathrm{B}$$ non-malleable jobs to be executed together on two parallel identical machines to minimize mean flow time. We propose a set of dominant schedules for this problem, and a dynamic programming algorithm that finds an optimal schedule in this dominant set in time $$O(n_\mathrm{A}^2n_\mathrm{B})$$ .
PubDate: 2015-08-01

• Integer programming for the generalized high school timetabling problem
• Abstract: Abstract Recently, the XHSTT format for high school timetabling was introduced. It provides a uniform way of modeling problem instances and corresponding solutions. The format supports a wide variety of constraints, and currently 38 real-life instances from 11 different countries are available. Thereby, the XHSTT format serves as a common ground for researchers within this area. This paper describes the first exact method capable of handling an arbitrary instance of the XHSTT format. The method is based on a mixed-integer linear programming (MIP) model, which is solved in two steps with a commercial general-purpose MIP solver. Computational results show that our approach is able to find previously unknown optimal solutions for 2 instances of XHSTT and proves optimality of 4 known solutions. For the instances not solved to optimality, new non-trivial lower bounds were found in 11 cases, and new best known solutions were found in 9 cases. Furthermore, the approach is compared with the finalists of Round 2 of the International Timetabling Competition 2011 and is shown to be competitive with one of the finalists.
PubDate: 2015-08-01

• Uplink scheduling for joint wireless orthogonal frequency and time
division multiple access networks
• Abstract: Abstract In this paper, we present a deterministic resource allocation model for a hybrid uplink wireless orthogonal frequency and time division multiple access network. Since the input data of the model may be affected by uncertainty, we further consider a stochastic formulation of the problem which we transform into an equivalent deterministic binary second-order conic program (SOCP). Subsequently, we use this binary SOCP to derive an equivalent integer linear programming formulation. The proposed models are aimed at maximizing the total bandwidth channel capacity subject to user power and sub-carrier assignment constraints while simultaneously scheduling users in time. As such, the models are best suited for non-real-time applications where sub-channel multiuser diversity can be further exploited simultaneously in frequency and time domains. Finally, in view of the large execution times required by CPLEX to solve the proposed models, we propose a variable neighborhood search metaheuristic procedure. Our numerical results show tight bounds and near optimal solutions for most of the instances when compared to the optimal solution of the problem. Moreover, we obtain better feasible solutions than CPLEX in the stochastic case. Finally, these bounds are obtained at a very low computational cost.
PubDate: 2015-07-21

• Optimizing memory allocation for multistage scheduling including setup
times
• Abstract: Abstract Mapping linear workflow applications onto a set of homogeneous processors can be optimally solved in polynomial time for the throughput objective with fewer processors than stages. This result holds true even when setup times occur in the execution and homogeneous buffers are available for the storage of intermediate results. In this kind of application, several computation stages are interconnected as a linear application graph, and each stage holds a buffer of limited size where intermediate results are stored and a processor setup time occurs when passing from one stage to another. In this paper, we tackle the problem in which the buffer sizes are not given beforehand and must be fixed before the execution to maximize the throughput within each processor. The goal of this work is to minimize the cost induced by the setup times by allocating buffers that are proportinal in size to each other. We present a closed formula to compute the optimal buffer allocation in the case of nondecreasing setup costs in the linear application. For the case of unsorted setup times, we provide competitive heuristics that are validated via extensive simulation. Three nonscalable brute force algorithms are also provided to compare heuristic approaches to optimal ones for small applications and to evaluate the relevance of our approach.
PubDate: 2015-07-21

• A decision support approach to automatic timetabling in higher education
institutions
• Abstract: Abstract At a time when the need to reduce costs has become part of the day-to-day reality of all educational institutions, it is unthinkable to continue to manually perform those tasks (i.e., the creation of timetables) that can be automated and optimized. The automatic creation of timetables for educational institutions is one of the most studied problems by the scientific community. However, almost all studies have been based on very simplified models of reality that have no practical application. A realistic model of the problem, robust algorithms that are able to find valid solutions in highly restricted environments, and optimization methods that are able to quickly provide quality results are key factors to consider when attempting to solve this (real) problem faced by educational institutions. This paper presents a summary of the work performed by Bullet Solutions over the last few years, from the first stage of understanding and modelling the problem to the final analysis of the results obtained using the developed software under real conditions.
PubDate: 2015-07-07

• Optimal control of a two-server flow-shop network
• Abstract: Abstract In this paper we suggest a new, intuitive, and simple method for scheduling jobs in a two-server flow-shop network (FSN) with the minimum makespan objective. Multiple types of jobs with corresponding constant service times arrive at the network at various times over a finite time interval. An analog fluid network is proposed and its optimal fluid control policy determined. We make use of this optimal control policy to suggest a new method for scheduling jobs in the original discrete FSN and prove its asymptotic optimality. The method is particularly attractive because it falls into the class of easy-to-implement and computationally inexpensive on-line algorithms. Numerical simulations are used to evaluate the performance of the suggested method and show that it performs optimally in almost all simulated instances. Some additional properties of the network are discussed and illustrated.
PubDate: 2015-07-02

• Optimal control strategies for single-machine family scheduling with
sequence-dependent batch setup and controllable processing times
• Abstract: Abstract The problem of scheduling jobs on an unreliable single machine is considered in this paper. The scheduling problem is characterized by the following features: jobs are grouped into classes of equivalent jobs; the generalized due date model is adopted for each class of jobs; it is possible to reduce the processing time of a job, at the price of the payment of an extra cost; a costly setup is required when switching between jobs of different classes. The scheduling problem is solved from a perspective which is different from the traditional determination of an optimal sequence of jobs; in fact, the objective of the paper is to determine optimal control strategies (functions of the system state) which allow generating the optimal decisions during the evolution of the system, taking into account the actual system state. In this way, optimal decisions can be promptly taken also in the presence of perturbations which affect the single machine (such as breakdowns and slowdowns). To this aim, a specific optimal control problem is stated and solved in the paper.
PubDate: 2015-07-02

• Identical coupled task scheduling: polynomial complexity of the cyclic
case
• Abstract: Abstract Coupled tasks are two-operation tasks, where the two operations are separated by a time interval of fixed duration. Coupled task scheduling problems refer then to the scheduling of a set of coupled tasks on a single machine. Applications of these problems, reported in the literature, arise in connection with radar systems, robotic cells, and in manufacturing. Most of the complexity issues for scheduling coupled tasks have been settled. However, the complexity status has been unknown for the identical coupled task problem, where multiple copies of a single coupled task are to be processed. The purpose of the article is to solve this open problem in the cyclic case, for which we prove the polynomial complexity.
PubDate: 2015-06-24

• A graph coloring approach to the deployment scheduling and unit assignment
problem
• Abstract: Abstract We address one of the external factors of personnel inventory behavior, deployments. The configuration of persistent unit deployments has the ability to affect everything from individual perceptions of service palatability to operational effectiveness. There is little evidence to suggest any analytical underpinnings to the U.S. Army deployment scheduling and unit assignment patterns. This paper shows that the deployment scheduling and unit assignment problem can be formulated as an interval graph such that modifications to traditional graph coloring algorithms provide an efficient mechanism for dealing with multiple objectives.
PubDate: 2015-06-10

• A reclaimer scheduling problem arising in coal stockyard management
• Abstract: We study a number of variants of an abstract scheduling problem inspired by the scheduling of reclaimers in the stockyard of a coal export terminal. We analyze the complexity of each of the variants, providing complexity proofs for some and polynomial algorithms for others. For one, especially interesting variant, we also develop a constant factor approximation algorithm.
PubDate: 2015-06-10

• Approximation algorithms for inventory constrained scheduling on a single
machine
• Abstract: Abstract We consider the problem of scheduling a set of jobs on a single machine subject to inventory constraints, i.e., conditions that jobs add or remove items to or from a centralized inventory, respectively. Jobs that remove items cannot be processed if the required number of items is not available. We focus on scheduling problems on a single machine where the objective is to minimize the total weighted completion time. In this paper, we design 2-approximation algorithms for special cases of the problem that run in polynomial time.
PubDate: 2015-06-03

• Decentralized subcontractor scheduling with divisible jobs
• Abstract: Abstract Subcontracting allows manufacturer agents to reduce completion times of their jobs and thus obtain savings. This paper addresses the coordination of decentralized scheduling systems with a single subcontractor and several agents having divisible jobs. Assuming complete information, we design parametric pricing schemes that strongly coordinate this decentralized system, i.e., the agents’ choices of subcontracting intervals always result in efficient schedules. The subcontractor’s revenue under the pricing schemes depends on a single parameter which can be chosen to make the revenue as close to the total savings as required. Also, we give a lower bound on the subcontractor’s revenue for any coordinating pricing scheme. Allowing private information about processing times, we prove that the pivotal mechanism is coordinating, i.e., agents are better off by reporting their true processing times, and by participating in the subcontracting. We show that the subcontractor’s maximum revenue with any coordinating mechanism under private information equals the lower bound of that with coordinating pricing schemes under complete information. Finally, we address the asymmetric case where agents obtain savings at different rates per unit reduction in completion times. We show that coordinating pricing schemes do not always exist in this case.
PubDate: 2015-06-02

• Batched bin packing revisited
• Abstract: Abstract We revisit the batched bin packing problem. In this model, items come in K consecutive batches, and the items of the earlier batches must be packed without any knowledge of later batches. We give the first approximation algorithm for the case $$K=2$$ , with tight asymptotic approximation ratio of 1.5833, while the known lower bound of the model is 1.378. With the application of this result, we are also able to provide an improved algorithm for the recently defined graph-bin packing problem in a special case, where we improve the upper bound from 3 to 2.5833.
PubDate: 2015-06-02

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