Single machine scheduling with periodic machine availability

In this paper we address the problem of scheduling jobs on a single machine with cyclical machine availability periods. In this problem, the scheduling horizon is composed of periods where the machine is available followed by other periods where no operation can be performed. In the literature, the problem is denoted as scheduling with periodic maintenance, as it is usually assumed that these unavailability periods are employed to perform maintenance activities. Another situation is the one inspiring our research, i.e. the need of completing manufacturing operations within a shift. More specifically, we focus the single machine scheduling problem with makespan objective subject to periodic machine availability. There are several contributions proposing approximate procedures due to the NP-hardness shown for the problem. However, we are not aware of a computational evaluation among these procedures. Furthermore, the problem is similar to the classical bin packing problem, so it is of interest to explore the relation between both problems. In this paper, we address these two issues, and propose new approximate solution procedures for the problem.Ministerio de Ciencia e Innovación DPI2016-80750-

Optimal Scheduling of Nursing Shifts : A Case Study on Work Scheduling at Haukeland University Hospital

This thesis presents a nurse scheduling problem tailored to characteristics common of Norwegian hospitals. The problem involves allocating nurses to specific shifts to ensure coverage of demand, while respecting work regulations and accounting for balance of workload, general nurse preferences and fairness. We formulate models for the nurse scheduling problem in line with the scheduling principles at Haukeland University Hospital and solve them using mathematical programming techniques. The purpose lies in the attempt to present a more efficient approach to the problem, compared to the manual scheduling approach currently utilized at the hospital. The method involves formulating a mixed integer programming model, which is implemented computationally in an optimization software. Multiple decision models are produced to represent two different forms of schedules, one cyclical and one calendar based. The model for the cyclical schedule can be optimized directly using the solver of the software. The model for the calendar-based schedule is more complex and is therefore solved by designing a decomposition heuristic approach to find a good solution in a reasonable computational time. The conclusion is that the schedules derived from the decision models are viable, with emphasis on the considerable time savings compared to the current scheduling approach at Haukeland. Currently, the hospital uses a manual method which takes approximately four to six weeks to create a schedule, whereas the models proposed in this thesis are able to derive an optimal solution within two hours. The models manage to effectively account for many criteria, including work regulations, fairness, balance of workload and preferred practices. The work in this thesis has been conducted through close cooperation with a representative from the staffing department at Haukeland, and the solutions derived from the models are able to capture their considerations in practice to a large extent. Our work has contributed to giving staff at Haukeland insight on how optimization and computational tools can be used to deal with their complex work scheduling problem.nhhma

Sensitivity of multi-product two-stage economic lotsizing models and their dependency on change-over and product cost ratio's

This study considers the production and inventory management problem of a two-stage semi-process production system. In case both production stages are physically connected it is obvious that materials are forced to flow. The economic lotsize depends on the holding cost of the end-product and the combined change-over cost of both production stages. On the other hand this 'flow shop' is forced to produce at the speed of the slowest stage. The benefit of this approach is the low amount of Work In Process inventory. When on the other hand, the involved stages are physically disconnected, a stock of intermediates acts as a decoupling point. Typically for the semi-process industry are high change-over costs for the process oriented first stage, which results in large lotsize differences for the different production stages. Using the stock of intermediates as a decoupling point avoids the complexity of synchronising operations but is an additional reason to augment the intermediate stock position. The disadvantage of this model is the high amount of Work-In-Process inventory. This paper proposes the 'synchronised planning model' realising a global optimum instead of the combination of two locally optimised settings. The mathematical model proves (for a two-stage single-product setting) that the optimal two-stage production frequency corresponds with the single EOQ solution for the first stage. A sensitivity study reveals, within these two-stage lotsizing models, the economical cost dependency on product and change-over cost ratio‟s. The purpose of this paper is to understand under which conditions the „joined setup‟ or the „two-stage individual eoq model‟ remain close to the optimal model. Numerical examples prove that the conclusions about the optimal settings remain valid when extending the model to a two-stage multi-product setting. The research reveals that two-stage individually optimized EOQ lotsizing should only be used when the end-product stage has a high added value and small change-over costs, compared to the first stage. Physically connected operations should be used when the end-product stage has a small added value and low change-over costs, or high added value and large change-over costs compared to the first production stage. The paper concludes with suggesting a practical common cycle approach to tackle a two-stage multi-product production and inventory management problem. The common cycle approach brings the benefit of a repetitive and predictable production schedule

Joint Trajectory and Communication Design for UAV-Enabled Multiple Access

Unmanned aerial vehicles (UAVs) have attracted significant interest recently in wireless communication due to their high maneuverability, flexible deployment, and low cost. This paper studies a UAV-enabled wireless network where the UAV is employed as an aerial mobile base station (BS) to serve a group of users on the ground. To achieve fair performance among users, we maximize the minimum throughput over all ground users by jointly optimizing the multiuser communication scheduling and UAV trajectory over a finite horizon. The formulated problem is shown to be a mixed integer non-convex optimization problem that is difficult to solve in general. We thus propose an efficient iterative algorithm by applying the block coordinate descent and successive convex optimization techniques, which is guaranteed to converge to at least a locally optimal solution. To achieve fast convergence and stable throughput, we further propose a low-complexity initialization scheme for the UAV trajectory design based on the simple circular trajectory. Extensive simulation results are provided which show significant throughput gains of the proposed design as compared to other benchmark schemes.Comment: Submitted for possible publicatio

Improving workforce scheduling of aircraft line maintenance at Sabena Technics.

This paper presents our application of a visualization tool and optimization model based on mixed-integer linear programming to solve a workforce staffing and scheduling problem at Sabena Technics, a major aircraft maintenance company in Belgium. We used the software to generate many alternative, cost-efficient schedules and to analyze multiple scenarios. In several management meetings, takeholders evaluated the schedules and raised concerns. We subsequently changed the model to successfully address their concerns. The model has resulted in considerable savings and a more efficient use of human resources.Workforce staffing; Scheduling; Optimization; Visualization; Aircraft maintenance;

Time and Organizational Improvisation

This paper argues that the apparent contradiction in current conceptualizations of time in organizations (e.g., Chronos vs. Kairos) is only apparent, and that a synthesis between these opposing poles is both possible and desirable. We propose improvisation (where time to plan converges with time to act) as a vehicle for articulating a dialectical view of time-based organizational phenomena, while focusing on the three major time-related problems organizations have to solve: scheduling, synchronization, and allocation. The paper discusses how improvisation helps to synthesize even time and event time in scheduling processes, internal pacing and external pacing in synchronization processes, and linear and cyclical time in allocation processes. Methodological and practical obstacles to synthesis are also discussed.Improvisation, Planning, Time

Stylized Facts and Other Empirical Evidence on Firm Dynamics, Business Cycle and Growth

In this paper, we bring together in a systematised fashion the scattered empirical evidence relating firm dynamics and both short-run and long-run macroeconomic dynamics. There are numerous studies that focus on firm-level data while controlling for macroeconomic conditions, which cover a considerable range of variables, industries and countries. From these studies it has emerged what is by now a rather robust set of empirical regularities, or stylized facts, about entry, exit, growth and the size distribution of firms. On the contrary, the literature that focus explicitly on the interplay between firm dynamics and the business cycle is roughly confined to the US experience and to the cyclical properties of firm entry and exit, whereas systematic studies about the relationship between firm dynamics and economic growth are almost non-existent whatsoever.empirical evidence, firm dynamics, business cycle, economic growth