We introduce a natural but seemingly yet unstudied variant of the problem of scheduling jobs on a single machine so as to minimize the number of tardy jobs. The novelty of our new variant lies in simultaneously considering several instances of the problem at once. In particular, we have n clients over a period of m days, where each client has a single job with its own processing time and deadline per

A popular approach to construct a schedule for a round-robin tournament is known as first-break, then-schedule. Thus, when given a home away pattern (HAP) for each team, which specifies for each round whether the team plays a home game or an away game, the remaining challenge is to find a round for each match that is compatible with both team’s patterns. When using such an approach, it matters how

Mnich and Wiese (Math Program 154:533–562, 2015) proved that the \(\mathcal {NP}\)-hard single-machine scheduling problem with rejection and the total weighted completion time plus total rejection cost as objective is fixed parameter tractable with respect to the number of different processing times and weights in the instance. This result is obtained by reducing the problem to an integer convex programming

Motivated by the recent trend in delivering projects with value or benefit to stakeholders and seeking to reduce the significant fraction of projects plagued by schedule and budget overruns, researchers are looking at lean project management (LPM) as a possible solution. This paper outlines a new approach to project scheduling in an LPM framework. We develop and solve a math program for balancing project

The International Timetabling Competition 2019 (ITC 2019) posed a university timetabling problem involving assigning classes to times and rooms for an entire semester while assigning students to required classes. We propose a new mixed integer programming (MIP) formulation of the problem. The MIP formulation takes advantage of different graph structures in conflict graphs to construct a strong formulation

We consider a single-machine scheduling problem with multiple unavailability periods such that the processing time of each job is inversely proportional to the kth power of its own resource consumption amount. The objective is to minimize the sum of the makespan and the total resource consumption cost. For every \(k>0\), we show that the problem with one unavailability period is NP-hard while it admits

A considerable number of sports competitions cope with limited availability of teams and sports infrastructure by organizing their timetable around a season that comprises many more time slots than games per team. However, in such timetables the rest period between teams’ consecutive games can vary considerably and the difference in the number of games played at any point in the season can become large

We consider batch scheduling on m machines to minimize the makespan. Each job has a given set of machines to be assigned. Each machine can process several jobs simultaneously as a batch, and the machines may have different batch capacities. We study two models: (i) scheduling on equal-speed batch machines under a nested processing set restriction, where the machines have the same processing speed,

This article presents a mixed-integer programming model for solving the university timetabling problem which considers the allocation of students to classes and the assignment of rooms and time periods to each class. The model was developed as part of our participation in the International Timetabling Competition 2019 and produced a ranking of second place at the competition. Modeling a timetabling

Public transportation networks are typically operated with a periodic timetable. The periodic event scheduling problem (PESP) is the standard mathematical modeling tool for periodic timetabling. PESP is a computationally very challenging problem: For example, solving the instances of the benchmarking library PESPlib to optimality seems out of reach. Since PESP can be solved in linear time on trees

In this paper, we study an important real-life scheduling problem that can be formulated as an unrelated parallel machine scheduling problem with sequence-dependent setup times, due dates, and machine eligibility constraints. The objective is to minimise total tardiness and makespan. We adapt and extend a mathematical model to find optimal solutions for small instances. Additionally, we propose several

Minimizing the setup costs caused by color changes is one of the main concerns for paint shop scheduling in the automotive industry. Yet, finding an optimized color sequence is a very challenging task, as a large number of exterior systems for car manufacturing need to be painted in a variety of different colors. Therefore, there is a strong need for efficient automated scheduling solutions in this

This paper addresses two classes of different, yet interrelated optimization problems. The first class of problems involves a mobile searcher that must locate a hidden target in an environment that consists of a set of unbounded, concurrent rays. The second class pertains to the design of interruptible algorithms by means of a schedule of contract algorithms. Both types of problems capture fundamental

We consider the Ordered Open End Bin Packing problem. Items of sizes in (0, 1] are presented one by one, to be assigned to bins in this order. An item can be assigned to any bin for which the current total size is strictly below 1. This means also that the bin can be overloaded by its last packed item. We improve lower and upper bounds on the asymptotic competitive ratio in the online case. Specifically

We present a Work Stealing scheduling algorithm that provably avoids most synchronization overheads by keeping processors’ deques entirely private by default and only exposing work when requested by thieves. This is the first paper that obtains bounds on the synchronization overheads that are (essentially) independent of the total amount of work, thus corresponding to a great improvement, in both algorithm

We consider in this work a bicriteria scheduling problem on two different parallel machines with a periodic preventive maintenance policy. The two objectives considered involve minimization of job rejection costs and weighted sum of completion times. They are handled through a lexicographic approach, due to a natural hierarchy among the two objectives in the applications considered. The main contributions

To enable the efficient division of labor in container yards, many large ports apply twin cranes, two identical automated stacking cranes each dedicated to one of the transfer zones on the seaside and landside. The use of a handshake area, a bay of containers that separates the dedicated areas of the two cranes, is a simple means to avoid crane interference. Inbound containers arriving in the transfer

This paper deals with the \(1|{p-\text {batch}, s_j\le b}|\sum C_j\) scheduling problem, where jobs are scheduled in batches on a single machine in order to minimize the total completion time. A size is given for each job, such that the total size of each batch cannot exceed a fixed capacity b. A graph-based model is proposed for computing a very effective lower bound based on linear programming; the

In light of the rapid growth of data centers around the world and their huge energy consumption, several researchers have focused on the task scheduling and resource allocation problem in order to minimize the energy consumed by the data center. Other initiatives focus on the implementation of green energy sources in order to minimize the consumption of fossil fuels and their emission of CO\(_{2}\)

This paper considers single-machine scheduling problems in which a given solution, i.e., an ordered set of jobs, has to be improved as much as possible by re-sequencing the jobs. The need for rescheduling may arise in different contexts, e.g., due to changes in the job data or because of the local objective in a stage of a supply chain that is not aligned with the given sequence. A common production

Single machine scheduling with sequence-dependent setup times is one of the classical problems of production planning with widespread applications in many industries. Solving this problem under the min-makespan objective is well known to be strongly NP-hard. We consider a special case of the problem arising from products having a modular design. This means that product characteristics, (mass-)customizable

The Test Laboratory Scheduling Problem (TLSP) is a real-world scheduling problem that extends the well-known Resource-Constrained Project Scheduling Problem (RCPSP) by several new constraints. Most importantly, the jobs have to be assembled out of several smaller tasks by the solver, before they can be scheduled. In this paper, we introduce different metaheuristic solution approaches for this problem

Researchers have studied the nurse rostering problem for multiple decades. Initially, the formulations were rather primitive including only a few necessary restrictions, but down the road, the formulations have become more complex. Nonetheless, a fraction of the research reaches implementation in practice, and many wards still schedule nurses manually. In this article, we introduce a flexible nurse

We propose an algorithm selection approach and an instance space analysis for the well-known curriculum-based course timetabling problem (CB-CTT), which is an important problem for its application in higher education. Several state of the art algorithms exist, including both exact and metaheuristic methods. Results of these algorithms on existing instances in the literature show that there is no single

We study a single-machine scheduling problem with two allowable job release and delivery times. This special case of a strongly NP-hard single-machine scheduling problem with an arbitrary number of job release and delivery times and with the objective to minimize the maximum job completion time remains NP-hard. Nevertheless, it is more transparent and accessible than the general version. Hence, it

In this paper, we provide three notes on scheduling unit-length jobs with precedence constraints to minimize the total completion time. First, we propose an exact algorithm for in-trees, of which the complexity depends mainly on the graph height, i.e., the length of the longest chain of the precedence graph. We show that this work improves the algorithm in the literature both theoretically and experimentally

We consider two supply chain scheduling problems in which s suppliers preprocess different parts of the jobs to be assembled by the manufacturer under the common sequence constraint, with the goal of minimizing the total weighted number of tardy parts and minimizing the total late work of the parts, respectively. Ren et al. (Information Processing Letter 113: 609-601, 2013) showed that both of the

We formulate a single machine online scheduling problem where jobs with distinct processing times, weights, and due dates arrive over time and must be processed one at a time without preemption in order to minimize the total weighted earliness and tardiness cost. We introduce a new scheduling policy, the list-based delayed shortest processing time (LDWSPT) policy, which is amenable to theoretical analysis

The multi-mode resource-constrained project scheduling problem (MRCPSP) is a very general scheduling model. The MRCPSP covers problems where activities can be executed in several ways or modes, and is affected by parameters such as their duration, temporary relationships with other activities, and renewable and non-renewable resource requirements. The objective of the MRCPSP is to select a combination

We study a scheduling problem involving both partitioning and scheduling decisions. A solution for our problem is defined by (i) partitioning the set of jobs into a set of accepted and a set of rejected jobs and (ii) scheduling the set of accepted jobs in a proportionate flow shop scheduling system. For a given solution, the jth largest due date is assigned to the job with the jth largest completion

The two-machine open shop problem was proved to be solvable in linear time by Teofilo Gonzalez and Sartaj Sahni in 1976. Several algorithms for solving that problem have been proposed since that time. We introduce another optimal algorithm for that classical problem with an interesting property: it allows to process jobs in almost arbitrary order, unlike the Gohzalez–Sahni algorithm where jobs have