This paper describes the UniCorT tool designed to solve university course timetabling problems specifically tailored for the 2019 International Timetabling Competition (ITC 2019). The proposed approach includes pre-processing, the use of a maximum satisfiability (MaxSAT) solver and a local search procedure. UniCorT is assessed with the benchmark instances from the ITC 2019. The impact of a handful

We consider scheduling problems for unit jobs with release times, where the number or size of the gaps in the schedule is taken into consideration, either in the objective function or as a constraint. Except for several papers on minimum-energy scheduling, there is no work in the scheduling literature that uses performance metrics depending on the gap structure of a schedule. One of our objectives

The scheduling of gantry cranes with respect to mutual interference has received considerable attention in recent years. We consider a subproblem which arises when each crane has a sequence of tasks to be assigned. The problem is concerned with resolving the interference between two cranes by determining which crane avoids the other in order to let it complete its next task first. We provide a fairly

Bender et al. (SPAA 2013) proposed a theoretical framework for testing in contexts where safety mistakes must be avoided. Testing in such a context is made by machines that need to be calibrated on a regular basis. Since calibrations have a non-negligible cost, it is important to study policies minimizing the total calibration cost while performing all the necessary tests. We focus on the single-machine

We consider a scheduling problem that abstracts a model of demand response management in a smart grid. We investigate the problem with a set of unrelated machines, and each job j (representing a client demand) is characterized by its release date, and its power request function expressing its request demand at specific times. Each machine has an energy power function, and the energy cost incurred at

Employee absences are inevitable in practice due to illness, heavy workloads or accidents. These unforeseen events result in the disruption of employee shift rosters, which are then typically repaired using re-rostering methods. Despite their widespread use, repair methods often require last-minute changes to rosters, negatively affecting employees’ personal lives. Robust rosters are thus crucial when

This paper addresses the job shop scheduling problem including time lag constraints. This is an extension of the job shop scheduling problem with many applications in real production environments, where extra (minimum and maximum) delays can be introduced between operations. It belongs to a category of problems known as NP-hard problems due to the large solution space. Biogeography-based optimization

We consider a variant of the NP-hard problem of assigning jobs to machines to minimize the completion time of the last job. Usually, precedence constraints are given by a partial order on the set of jobs, and each job requires all its predecessors to be completed before it can start. In this paper, we consider a different type of precedence relation that has not been discussed as extensively and is

Observations show that some HPC applications periodically alternate between (i) operations (computations, local data accesses) executed on the compute nodes, and (ii) I/O transfers of data and this behavior can be predicted before-hand. While the compute nodes are allocated separately to each application, the storage is shared, and thus, I/O access can be a bottleneck leading to contention. To tackle

This paper considers the problem of servicing a set of locations by a fleet of robots so as to minimize overall makespan. Although motivated by a specific real-world, multi-robot drilling and fastening application, the problem also arises in a range of other multi-robot domains where service start times are subject to precedence constraints and robots must be routed in space and time to avoid collisions

Scheduling of megaprojects is very challenging because of typical characteristics, such as expected long project durations, many activities with multiple modes, scarce resources, and investment decisions. Furthermore, each megaproject has additional specific characteristics to be considered. Since the number of nuclear dismantling projects is expected to increase considerably worldwide in the coming

In this paper, we investigate an open problem by Györgyi and Kis for a single-machine scheduling problem with a non-renewable resource (NR-SSP) and total weighted completion time criterion. The problem is NP-hard, even if every job has the same processing time, and each weight is equal to its required amount of the resource. Györgyi and Kis prove that a simple list scheduling algorithm for this special

Motivated by mail delivery scheduling problems arising in Royal Mail, we study a generalization of the fundamental makespan scheduling \(P||C_{\max }\) problem which we call the bounded job start scheduling problem. Given a set of jobs, each specified by an integer processing time \(p_j\), that have to be executed non-preemptively by a set of m parallel identical machines, the objective is to compute

We study a generalization of the well-known traveling salesman problem in a metric space, in which each city is associated with a release time. The salesman has to visit each city at or after its release time. There exists a naive 5/2-approximation algorithm where the salesman simply starts to route the network after all cities are released. Interestingly, this bound has never been improved for more

We study several two-machine shop scheduling problems, namely flow shop, job shop and open shop scheduling problems under linear constraints. In these problems, the processing times of two stages of jobs are also decision variables and satisfy a system of linear constraints. The goal of each problem is to determine the processing time of each job, and to schedule the jobs to the shop machine such that

In this paper, we work on the scheduling problem with active time model. We have a set of preemptive jobs with integral release times, deadlines and required processing lengths, while the preemption of jobs is only allowed at integral time points. We have a single machine that can process at most g distinct job units at any given time unit when the machine is switched on. The objective is to find a

The single machine coupled task scheduling problem includes a set of jobs, each with two separated tasks, and there is an exact delay between the tasks. We investigate the single machine coupled task scheduling problem with the objective of minimizing the makespan under identical processing time for the first task and identical delay period for all jobs, and the time-dependent processing time setting

Following a recent interest in sustainable scheduling under operational costs that vary over time, we study scheduling problems on a single machine under time-of-use electricity tariffs. We consider two main variants of the problem: cost minimization and profit maximization. In the cost minimization problem, the set of jobs to be processed is given, and the goal is to schedule all jobs within a planning

In this paper, we fill in a conspicuous gap in research on scheduling coupled tasks. We draw a full complexity picture for single-machine scheduling of coupled tasks with exact time delays in between with the objective of minimizing the total of job completion times.

The paper considers the three-machine open shop scheduling problem to minimize the makespan. In the model, each job consists of two operations, one of which is to be processed on the bottleneck machine, which is the same for all jobs. A new linear-time algorithm to find an optimal non-preemptive schedule is developed. The suggested algorithm considerably simplifies the only previously known method

This special issue of the Journal of Scheduling contains selected papers submitted in response to an open call for papers announced after the Second International Workshop on Dynamic Scheduling Problems (IWDSP 2018), held in June 2018, at the Faculty of Mathematics and Computer Science, Adam Mickiewicz University, Poznań, Poland. It was the second IWDSP workshop, following the IWDSP 2016 workshop held

Real-time scheduling strategies for safety-critical systems are primarily focused on ensuring correctness, both functional and temporal. In order to provide the desired predictability in such systems, it is often advisable that all timing requirements be guaranteed offline, before putting the system into operation. Formal approaches allow for all necessary and sufficiency conditions corresponding to

This paper considers a joint order acceptance and scheduling problem under a general scenario. A manufacturer receives multiple orders with a given revenue, processing time, release date, due date, deadline, and earliness and tardiness penalties. The manufacturer can be seen as a single-machine system. Due to limited capacity, the manufacturer cannot process every order and needs to determine the optimal

We study the total weighted tardiness problem with rejection on a single machine. We present new recursive algorithms and approximation results for the agreeably weighted case and a variety of related problems with and without deadlines.

We prove the NP-hardness of constructing a minmax regret solution for the two-machine flow shop problem under the interval uncertainty of the job processing times. The problem complexity status has been an open question for over the past 20 years. We establish the NP-hardness of this problem using a so-called alternative scheme for proving the NP-hardness of optimization problems. Also, we show that

In this paper we study a proportionate flow shop of batching machines with release dates and a fixed number $m \geq 2$ of machines. The scheduling problem has so far barely received any attention in the literature, but recently its importance has increased significantly, due to applications in the industrial scaling of modern bio-medicine production processes. We show that for any fixed number of machines

Solving university course timetabling problems is a large and complex task. Moreover, every new academic term, a new timetable is likely to be scheduled due to disruptions (e.g., changes in teacher-lecture allocation). Nevertheless, the university infrastructure, the overall curricular plans, and the number of students/teachers is still very similar in consecutive terms. For this reason, a timetable

In the field of time-dependent scheduling, a job’s processing time is specified by a function of its start time. While monotonic processing time functions are well-known in the literature, this paper introduces non-monotonic functions with a convex, piecewise-linear V-shape similar to the absolute value function. They are minimum at an ideal start time, which is the same for all given jobs. Then, the

In production planning and scheduling, data mining methods can be applied to transform the scheduling data into useful knowledge that can be used to improve planning/scheduling by enabling real-time decision-making. In this paper, a novel approach combining dispatching rules, a genetic algorithm, data mining, and simulation is proposed. The genetic algorithm (i) is used to solve scheduling problems

We present several new results for a single machine time-dependent scheduling problem of minimizing the total completion time of a set of linearly deteriorating jobs with unit basic processing times. First, we show new properties of cyclic transformations of V-shaped sequences for this problem. Next, applying the results, we prove a new necessary condition of schedule optimality for the considered

Quay crane scheduling is a key aspect of container terminal operation, which can be regarded as a decision-making process with uncertainty. Each task involves stochastic loading and unloading operation times owing to the existence of uncertainty. In this study, we investigate the unidirectional quay crane scheduling problem for a stochastic processing time, which requires that all the quay cranes move

This paper proposes a discrete time Markov decision process approach to compute the optimal on-line speed scaling policy to minimize the energy consumption of a single processor executing a finite or infinite set of jobs with real-time constraints. We provide several qualitative properties of the optimal policy: monotonicity with respect to the jobs parameters, comparison with on-line deterministic

In rotational workforce planning, a schedule is constructed from a sequence of work and rest periods. Each employee starts at a different part of the schedule, and after a certain amount of time, the schedule repeats. The length of the schedule increases with a higher number of employees. At the same time, various constraints on work sequences and days off have to be considered. For a large number

In dynamic pickup and delivery problems with time windows (PDPTWs), potentially urgent request information is released over time. This gradual data availability means the decision-making process must be continuously repeated. These decisions are therefore likely to deteriorate in quality as new information becomes available. It is still believed that the state of the art for this problem remains far

We consider two single-machine scheduling problems in which two competing projects share one common resource. Each project has multiple interim assessments, and its own jobs are ordered completely. A tardy job incurs a tardiness penalty cost which can be avoided by compressing some jobs, which requires an additional cost. The performance measure of each project is the total tardiness penalty cost plus

In this paper we study a single batch-processing machine scheduling model. In our model, a set of jobs having different release dates needs to be scheduled onto a single machine that can process a batch of jobs simultaneously at a time. Each batch incurs a fixed setup time and a fixed setup cost. The decision maker may reject some of the jobs by paying penalty cost so as to achieve a tight makespan

Demand for healthcare is increasing rapidly. To meet demand, we must improve the efficiency of our public health services. We present a mixed integer programming formulation that simultaneously tackles the integrated master surgical schedule and surgical case assignment problems under a modified block scheduling policy. That is, we allocate specialties, surgeons, and patients to surgical time blocks

This paper considers three serial-batching scheduling problems with two agents to minimize the makespan of agent A and maximum cost (or maximum lateness) of agent B simultaneously. In these two-agent scheduling problems, jobs of different agents cannot be processed in a common batch, and the cost function of an agent depends only on its jobs. For each problem, we present a polynomial-time algorithm

Rapid growth of demand for remote computational power, along with high energy costs and infrastructure limits, has led to treating power usage as a primary constraint in data centers. Especially, recent challenges related to development of exascale systems or autonomous edge systems require tools that will limit power usage and energy consumption. This paper presents a power capping method that allows

In this paper, we consider the homogeneous scheduling on speed-scalable processors, where the energy consumption is minimized. While most previous works have studied single-processor jobs, we focus on rigid parallel jobs, using more than one processor at the same time. Each job is specified by release date, deadline, processing volume and the number of required processors. Firstly, we develop constant-factor

In this paper, we propose a new dataset for the resource-constrained multi-project scheduling problem and evaluate the performance of multi-project extensions of the single-project schedule generation schemes. This manuscript contributes to the existing research in three ways. First, we provide an overview of existing benchmark datasets and classify the multi-project literature based on the type of

Staffing and rostering are two interdependent optimization problems related to personnel planning. Where staffing concerns an organization’s personnel composition, personnel rostering aims to assign that staff to shifts while respecting a set of constraints. Staffing decisions therefore impact on the extent to which personnel rostering objectives can be accomplished. Previous research has suggested

In scheduling problems with generalized due dates (gdd), the due dates are specified according to their position in the sequence, and the j -th due date is assigned to the job in the j -th position. We study a single-machine problem with generalized due dates, where the objective is maximizing the number of jobs completed exactly on time. We prove that the problem is NP-hard in the strong sense. To

The mixed no-idle flowshop scheduling problem arises in modern industries including integrated circuits, ceramic frit and steel production, among others, and where some machines are not allowed to remain idle between jobs. This paper describes an exact algorithm that uses Benders decomposition with a simple yet effective enhancement mechanism that entails the generation of additional cuts by using

In this paper, we study event-based mixed-integer programming (MIP) formulations for the resource-constrained project scheduling problem (RCPSP) that represent an alternative to the more common time-indexed model (DDT) (Pritsker et al. in Manag Sci 16(1):93–108, 1969 ; Christofides et al. in Eur J Oper Res 29(3):262–273, 1987 ) for the case when the scheduling horizon is large. In contrast to time-indexed

We consider the competitive multi-agent scheduling problem on a single machine, where each agent’s cost function is to minimize its total weighted late work. The aim is to find the Pareto-optimal frontier, i.e., the set of all Pareto-optimal points. When the number of agents is arbitrary, the decision problem is shown to be unary $$\mathcal {NP}$$ NP -complete even if all jobs have the unit weights

We study a single-machine lot-sizing problem, where n types of products need to be scheduled on the machine. Each product is associated with a constant demand rate, maximum production rate and inventory costs per time unit. Every time when the machine switches production between products, sequencing costs are incurred. These sequencing costs depend both on the product the machine just produced and

In this work, we study scheduling in star data gathering networks with background communications. The worker nodes of the network hold datasets that have to be transferred directly to the base station. The communication speed of each link changes with time, due to other applications using the network, independently of the speeds of other links. Our goal is to gather all data within the minimum time

University timetabling is a real-world problem frequently encountered in higher education institutions. It has been studied by many researchers who have proposed a wide variety of solutions. Measuring the variation of the performance of solution approaches across instance spaces is a critical factor for algorithm selection and algorithm configuration, but because of the diverse conditions that define

In this paper, we address the problem of designing an interruptible system in a setting which involves n problem instances. The system schedules executions of a contract algorithm (which offers a trade-off between allowable computation time and quality of the solution) in m identical parallel processors. When an interruption occurs, the system outputs the currently best solution to each of the n problem

This paper describes a unified global constraint to model scheduling problems with unary resources, i.e., each resource can process only a single activity at a time. In addition, the constraint enforces sequence-dependent transition times between activities. It often happens that activities are grouped into families with zero transition times within a family. Moreover, some of the activities might

We study the problem of distributing a file, initially located at a server, among a set of n nodes. The file is divided into $$m\ge 1$$ m ≥ 1 equally sized packets. After downloading a packet, nodes can upload it to other nodes, possibly to multiple nodes in parallel. Each node, however, may receive each packet from a single source node only. The upload and download rates between nodes are constrained

The paper examines the complexity of assigning multiple breaks to shifts in the context of large-scale tour scheduling. A mixed-integer programming (MIP) model is presented that includes shift and days-off scheduling along with break assignments for a multi-skilled workforce. To achieve tractability, a two-stage decomposition procedure is proposed that separates the tour scheduling problem (TShP) from

This work deals with a very generic class of scheduling problems with identical/uniform/unrelated parallel machine environment. It considers well-known attributes such as release dates, deadlines, or sequence-dependent setup times and accepts any objective function defined over job completion times. Non-regular objectives are also supported. We introduce a branch-cut-and-price algorithm for such problems

We give a definition of a class of mirror scheduling problems, review existing representatives of this class and demonstrate that an identical parallel machine scheduling problem with precedence constraints and an upper bound on the makespan to minimize (maximize) the total weighted early work and the same problem with modified due dates, reversed precedence constraints and the objective function of

This paper is a comprehensive review of the research conducted over the past four decades in the domain of time-dependent scheduling, where variable processing times of jobs depend on when the jobs start. The paper is divided into four parts. The first part recalls some definitions and notions, introduces terminology, and defines the main models of time-dependent job processing times and the notation

The decisions in the operating room scheduling process related to the case mix planning, the master surgery schedule and the nurse roster are based on the expected demand, predicted by historical data. Patients are only scheduled in the operational phase when the actual demand is known. However, the actual patient demand may differ from the expected demand. In this paper, we integrate the surgical

We study a scheduling environment that finds many real-world manufacturing applications, in which there is a close connection between a hybrid multiprocessor open shop and multiple parallel identical flow shops. In this environment, there is an extended two-stage open shop, where in one stage we have a set of parallel identical machines, while in the other we have a two-machine flow shop. Our objective

We consider the $$\mathscr {NP}$$ NP -hard twin robot scheduling problem, which was introduced by Erdoğan et al. (Naval Res Logist (NRL) 61(2):119–130, 2014). Here, two moving robots positioned at the opposite ends of a rail have to perform automated storage and retrieval jobs at given positions along the gantry rail with a non-crossing constraint. The objective is to minimize the makespan. We extend

In order to increase the productivity of sea port container storage yards, a triple-crossover-stacking-crane setting can be deployed. Although this setting yields promising results, there is increasing risk of cranes interfering. Coping with interference is a key factor for exploiting the potential of triple-crossover-stacking-cranes to increase overall productivity. In this paper, we tackle the problem