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

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 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

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

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 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

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

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

We consider two-machine flow shop scheduling problems with storage to minimize the makespan. Under a storage constraint, each job has its own size, and the total size of the job(s) being processed on the machine(s) and the job(s) waiting for the second operation cannot exceed the given capacity. It is known that the computational complexity is strongly NP-hard and in general an optimal schedule does

We consider the \(P_m || C_{\max }\) scheduling problem where the goal is to schedule n jobs on m identical parallel machines \((m < n)\) to minimize makespan. We revisit the famous Longest Processing Time (LPT) rule proposed by Graham in 1969. LPT requires to sort jobs in non-ascending order of processing times and then to assign one job at a time to the machine whose load is smallest so far. We provide