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

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 \(m \ge 2\) 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

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

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 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

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 our

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 \(\mathcal {NP}\)-complete even if all jobs have the unit weights. When

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 \(m\ge 1\) 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 by

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

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 \(\mathscr {NP}\)-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 the

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

We present two deterministic online algorithms for the problem of scheduling with a general machine cost function. In this problem, every machine has a cost that is given by a nonnegative cost function, and the objective function is the sum of makespan and the cost of the purchased machines. In previous work by Imreh, it was shown that no deterministic algorithm has competitive ratio below 2, and an

We address single-machine scheduling problems for which the actual processing times of jobs are subject to various effects, including a positional effect, a cumulative effect and their combination. We review the known results on the problems to minimize the makespan, the sum of the completion times and their combinations and identify the problems for which an optimal sequence cannot be found by simple

Periodic rescheduling is a commonly used method for scheduling short-term operations. Through computational experiments that vary plant parameters, such as the load and the capacity of a facility, we investigate the effects these parameters have on plant performance under periodic rescheduling. The results show that choosing a suitable rescheduling policy depends highly on some key plant parameters

In this paper, a variant of the vehicle routing problem with mixed backhauls (VRPMB) is presented, i.e. goods have to be delivered from a central depot to linehaul customers, and, at the same time, goods have to be picked up from backhaul customers and brought to the depot. Both types of customers can be visited in mixed sequences. The goods to be delivered or picked up are three-dimensional (cuboid)

We show by induction that the shortest processing time sequence is optimal for a number of three-stage ordered flow shops with either synchronous flow, blocking or no-idle machines, effectively proving the optimality of an index priority rule when the adjacent job pairwise interchange argument does not hold. We also show that when the middle machine is maximal, the synchronous flow, blocking and no-wait

We consider the single-machine scheduling problem with job-dependent machine deterioration. In the problem, we are given a single machine with an initial nonnegative maintenance level, and a set of jobs each with a non-preemptive processing time and a machine deterioration. Such a machine deterioration quantifies the decrement in the machine maintenance level after processing the job. To avoid a machine

We study the optimal design of round-robin tournaments with three symmetric players. We characterize the subgame-perfect equilibrium in these tournaments with either one or two prizes. Our results show that the players who wish to maximize their expected payoffs or their probabilities of winning have different preferences about the order of games under tournaments with one or two prizes. We analyze

This paper studies a new mixed batch scheduling problem that arises in vacuum heat treatment. A mixed batch machine can process at most a given number of jobs simultaneously. The processing time of a batch is the weighted sum of the maximum processing time and the total processing time of jobs in the batch. The objective is to minimize the makespan. We first prove that the problem on a single machine

We investigate the problem of keeping the maximum number of starting times of a baseline schedule if some machines happen to be out of order when the baseline schedule is to be implemented. If the machines are identical, we show that the problem is polynomially solved when no deadline is imposed on the reactive schedule and is strongly NP-hard otherwise. If the number of unrelated machines is fixed

This paper investigates an integrated production and assembly scheduling problem with the practical manufacturing features of serial batching and the effects of deteriorating and learning. The problem is divided into two stages. During the production stage, there are several semi-product manufacturers who first produce ordered product components in batches, and then these processed components are sent

In a direct shipping (or point-to-point) network, individual deliveries are round trips from one supplier to one customer and back to either the same or another supplier, i.e., a truck can visit only one customer at a time before it has to return to a supplier. We consider the multiple sources/multiple sinks case, where a given set of direct deliveries from a set of suppliers to a set of customers

We study the parameterized complexity of a set of flow-shop scheduling problems in which the objective is to maximize the weighted number of just-in-time jobs. Our analysis focuses on the case where the number of due dates is considerably smaller than the number of jobs and thus can be considered as a parameter. We prove that the two-machine problem is W[1]-hard with respect to this parameter, even

Fully polynomial time approximation schemes for scheduling deteriorating jobs with nonlinear processing times on a single machine are given via an application of the K-approximation sets and functions technique.

In today’s ports, the storage area is often the bottleneck in the serving of a vessel. It is therefore an important influencing factor in the minimization of the turnaround time of the vessels, which is the main objective in operational planning in container terminals. The operational planning of the yard cranes strongly impacts the yard’s efficiency. This planning task comprises the assignment of

We revisit the classical single-machine scheduling problem to minimize total tardiness with deadlines. The problem is binary NP-hard even without the deadline restrictions. It was reported early in Koulamas and Kyparisis (Eur J Oper Res 133:447–453, 2001) that the exact complexity (unary NP-hardness or pseudo-polynomial-time solvability) of the problem is still open. We show that this problem is unary

We study scheduling problems on a proportionate flowshop. Three objective functions are considered: minimum makespan, minimum total completion time, and minimum total load. We consider a learning process; thus, the processing time of a job processed later in sequence is reduced. The scheduler has the option of job rejection; i.e., only a subset of the jobs are processed and the rejected jobs are penalized

In recent years, large public hospitals have undergone a strong growth in healthcare services demand, not offset by resources increase. In this context, one of the most critical issues is the optimization of human resources. In this paper, we study the problem of finding the optimal assignment of tasks to physicians over a predefined time horizon in a large general surgery ward. Each task has to be

Tang et al. (Eur J Oper Res 263:401–411, 2017) have recently introduced a parallel-batching machine scheduling problem with linearly deteriorating jobs of two agents and presented a computational complexity classification of various special cases of this problem, including a number of NP-hardness proofs. We refine these results by demonstrating strong NP-hardness of several special cases, which are

Industries such as textiles, paints, chemicals, paper, drugs and pharmaceuticals operate as flow shops with sequence-dependent setup times (SDST). The sequence-dependent setup environment is characterised by the dependence of the setup time on the current job and also on the previous job processed on that machine. To further complicate the problem, in most real-life scenarios, decision-makers have