Showing papers by "Mario Vanhoucke published in 2010"

Branching strategies in a branch-and-price approach for a multiple objective nurse scheduling problem

Abstract: The efficient management of nursing personnel is of critical importance in a hospital's environment comprising a vast share of the hospital's operational costs. The nurse scheduling process affects highly the nurses' working conditions, which are strongly related to the provided quality of care. In this paper, we consider the rostering over a mid-term period that involves the construction of duty timetables for a set of heterogeneous nurses. In scheduling nursing personnel, the head nurse is typically confronted with various (conflicting) goals complying with different priority levels which represent the hospital's policies and the nurses' preferences. In constructing a nurse roster, nurses need to be assigned to shifts in order to maximize the quality of the constructed timetable satisfying the case-specific time related constraints imposed on the individual nurse schedules. Personnel rostering in healthcare institutions is a highly constrained and difficult problem to solve and is known to be NP-hard. In this paper, we present an exact branch-and-price algorithm for solving the nurse scheduling problem incorporating multiple objectives and discuss different branching and pruning strategies. Detailed computational results are presented comparing the proposed branching strategies and indicating the beneficial effect of various principles encouraging computational efficiency.

Using activity sensitivity and network topology information to monitor project time performance.

Abstract: The interest in activity sensitivity from both the academics and the practitioners lies in the need to focus a project manager's attention on those activities that influence the performance of the project. When management has a certain feeling of the relative sensitivity of the various parts (activities) on the project objective, a better management's focus and a more accurate response during project tracking should positively contribute to the overall performance of the project. In the current research manuscript, a simulation study is performed to measure the ability of four basic sensitivity metrics to dynamically improve the time performance during project execution. We measure the use of sensitivity information to guide the corrective action decision making process to improve a project's time performance, while varying the degree of management's attention. A large amount of simulation runs are performed on a large set of fictitious project networks generated under a controlled design.

A scatter search heuristic for maximising the net present value of a resource-constrained project with fixed activity cash flows

Abstract: In this paper, we present a meta-heuristic algorithm for the resource-constrained project scheduling problem with discounted cash flows. We assume fixed payments associated with the execution of project activities and develop a heuristic optimisation procedure to maximise the net present value of a project subject to the precedence and renewable resource constraints. We investigate the use of a bi-directional generation scheme and a recursive forward/backward improvement method from literature and embed them in a meta-heuristic scatter search framework. We generate a large dataset of project instances under a controlled design and report detailed computational results. The solutions and project instances can be downloaded from a website in order to facilitate comparison with future research attempts.

Introducing Optimization Techniques to Students: An Exam Case Distribution Model

Abstract: In this paper, an integer programming IP model is presented to assign MBA and undergraduate students to groups to solve an exam case in an operations research O.R. course. It is assumed that the students have a basic understanding of mathematical programming and are now ready to build their first real-life model in class. Thanks to the direct link with the student's situation and the immediate repercussion on the exam assignment, students can quickly understand the problem and are willing to help to define the problem in class. The example illustrates many O.R.-related issues, such as the balance between problem complexity and solution quality, and the need for dynamic rather than static models. Thanks to its simplicity and practicality, this exercise is an ideal tool to make the often complex domain of O.R. more accessible.

Measuring time: An earned value performance management study”

Abstract: In this paper, I briefly describe the various topics of a new book that I have written as a summary of a large research study performed during the past 5 years The research described in the book deals with the project performance and control phase of the project life cycle, and the corresponding feedback loop from control to planning and scheduling to take corrective actions when necessary (this is known as project tracking or project monitoring) More precisely, the focus is on a reactive scheduling early warning system by means of Earned Value Management (EVM) and Schedule Risk Analysis (SRA) For an overview of EVM, see eg Anbari (2003) or Fleming and Koppelman (2005) For an introduction to SRA, see Hulett (1996) Although EVM has been set up to follow up both time and cost, the majority of the research has been focused on the cost aspect In the book, I focus on the time dimension which has received relatively less attention in the last decennia The aim of the research is to measure the project performance sensitivity and the forecast accuracy (both in terms of time and cost, but with a focus on the time dimension) of the existing and newly developed metrics based on the principles of EVM and SRA The research question boils down to the determination of when and in which cases SRA and EVM could lead to improved project tracking and corrective actions decision making

Introducing Learning Effects in Resource-constrained Project Scheduling

Abstract: Learning effects assume that the efficiency of a resource increases with the duration of a task. Although these effects are commonly used in machine scheduling environments, they are rarely used in a project scheduling setting. In this paper, we study and model learning effects in a project scheduling environment and apply the model to the discrete time/resource trade-o_ scheduling problem (DTRTP), where each activity has a _fixed work content for which a set of execution modes (duration/resource requirement pairs) can be defined. Computational results emphasize the significant impact of learning effects on the project schedule, measure the margin of error made by ignoring learning and show that timely incorporation of learning effects can lead to significant makespan improvements.

A hybrid job shop procedure for a Belgian manufacturing company producing industrial wheels and castors in rubber

Abstract: In this paper, a new procedure to solve a job shop scheduling problem at a Belgian manufacturer producing industrial wheels and castors in rubber is presented. The procedure is an extension of a hybrid shifting bottleneck procedure with a tabu search algorithm while incorporating various company specific constraints. The various extensions to cope with the company specific constraints have a strong similarity with the complex job shop problem formulation of Mason et al. (2002). The new procedure is used as a simulation engine to test the relevance of various scenarios in order to improve the current planning approach of the company. A detailed computational experiment highlights the main contribution of the novel procedure for the company.

A comparison of priority rules for the job shop scheduling problem under different flow time- and tardiness-related objective functions

Abstract: In this paper, a comparison and validation of various priority rules for the job shop scheduling problem under different objective functions is made. In a first computational experiment, 30 priority rules from literature are used to schedule job shop problems under two flow time-related and three tardiness-related objectives. Based on this comparative study, the priority rules are extended to 13 combined scheduling rules in order to improve the performance of the currently bestknown rules from literature. Moreover, the best performing priority rules on each of these five objective functions are combined into hybrid priority rules in order to be able to optimize various objectives at the same time. In a second part of the computational experiment, the robustness on the relative ranking of the performance quality is checked for the various priority rules when applied on larger problem instances, on the extension of multiple machines possibilities per job as well as on the introduction of sequence-dependent setup times. Moreover, the influence of dynamic arrivals of jobs has also been investigated to check the robustness on the relative ranking of the performance quality between static and dynamic job arrivals. The results of the computational experiments are presented and critical remarks and future research avenues are suggested.

A hybrid single and dual population search procedure for the job shop scheduling problem

Abstract: This paper presents a genetic algorithm and a scatter search procedure to solve the well-known job shop scheduling problem. In contrast to the single population search performed by the genetic algorithm, the scatter search algorithm splits the population of solutions in a diverse and high-quality set to exchange information between individuals in a controlled way. Extensions from a single to a dual population by taking problem specific characteristics into account can be seen as a stimulator to add diversity in the search process, which has a positive influence on the important balance between intensification and diversification. Computational experiments verify the benefit of this diversity on the effectiveness of the meta-heuristic search process. Various algorithmic parameters from literature are embedded in both procedures and a detailed comparison is made. A set of standard instances is used to compare the different approaches and the best obtained results are benchmarked against heuristic solutions found in literature.