Bart Veltman

Bio: Bart Veltman is an academic researcher from University of Twente. The author has contributed to research in topics: Staffing & Workforce planning. The author has an hindex of 6, co-authored 8 publications receiving 249 citations.

ORchestra: an online reference database of OR/MS literature in health care.

Abstract: We introduce the categorized reference database ORchestra, which is available online at http://www.utwente.nl/choir/orchestra/.

Harmonious personnel scheduling

Abstract: The area of personnel scheduling is very broad. Here we focus on the ‘shift assignment problem’. Our aim is to discuss how ORTEC HARMONY handles this planning problem. In particular we go into the structure of the optimization engine in ORTEC HARMONY, which uses techniques from genetic algorithms, local optimization algorithms and variable neighborhood search. We will describe the result on an artificial test set.

A case study of cost-efficient staffing under annualized hours

Abstract: We propose a mathematical programming formulation that incorporates annualized hours and shows to be very flexible with regard to modeling various contract types. The objective of our model is to minimize salary cost, thereby covering workforce demand, and using annualized hours. Our model is able to address various business questions regarding tactical workforce planning problems, e.g., with regard to annualized hours, subcontracting, and vacation planning. In a case study for a Dutch hospital two of these business questions are addressed, and we demonstrate that applying annualized hours potentially saves up to 5.2% in personnel wages annually.

Shift rostering using decomposition: assign weekend shifts first

Abstract: This paper introduces a shift rostering problem that surprisingly has not been studied in the literature: the weekend shift rostering problem. It is motivated by our experience that employees' shift preferences predominantly focus on the weekends, since many social activities happen during weekends. The weekend rostering problem (WRP) addresses the rostering of weekend shifts, for which we design a problem-specific heuristic. We consider the WRP as the first phase of the shift rostering problem. To complete the shift roster, the second phase assigns the weekday shifts. This decomposition reflects how shift rosters are often created manually in practice, which makes the decomposition method proposed in this paper a more intuitive approach for business users compared to approaches without this decomposition. We believe that such approaches enable business users to effectively analyze and steer the outcomes of algorithms for shift rostering especially on criteria that are relevant to them such as those concerning weekends. We analyze and discuss effects of this two-phase approach both on the weekend shift roster and on the roster as a whole. We demonstrate that our first-phase weekend rostering heuristic is effective both on generated instances and real-life instances. For situations where the weekend shift roster is one of the key determinants of the quality of the complete roster, our two-phase approach is shown to be effective.

Variable neighbourhood search: methods and applications

Abstract: Variable neighbourhood search (VNS) is a metaheuristic, or a framework for building heuristics, based upon systematic changes of neighbourhoods both in descent phase, to find a local minimum, and in perturbation phase to emerge from the corresponding valley. It was first proposed in 1997 and has since then rapidly developed both in its methods and its applications. In the present paper, these two aspects are thoroughly reviewed and an extensive bibliography is provided. Moreover, one section is devoted to newcomers. It consists of steps for developing a heuristic for any particular problem. Those steps are common to the implementation of other metaheuristics.

Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS

Abstract: We provide a comprehensive overview of the typical decisions to be made in resource capacity planning and control in health care, and a structured review of relevant articles from the field of Operations Research and Management Sciences (OR/MS) for each planning decision. The contribution of this paper is twofold. First, to position the planning decisions, a taxonomy is presented. This taxonomy provides health care managers and OR/MS researchers with a method to identify, break down and classify planning and control decisions. Second, following the taxonomy, for six health care services, we provide an exhaustive specification of planning and control decisions in resource capacity planning and control. For each planning and control decision, we structurally review the key OR/MS articles and the OR/MS methods and techniques that are applied in the literature to support decision making.

Red deer algorithm (RDA): a new nature-inspired meta-heuristic

Abstract: Nature has been considered as an inspiration of several recent meta-heuristic algorithms. This paper firstly studies and mimics the behavior of Scottish red deer in order to develop a new nature-inspired algorithm. The main inspiration of this meta-heuristic algorithm is to originate from an unusual mating behavior of Scottish red deer in a breading season. Similar to other population-based meta-heuristics, the red deer algorithm (RDA) starts with an initial population called red deers (RDs). They are divided into two types: hinds and male RDs. Besides, a harem is a group of female RDs. The general steps of this evolutionary algorithm are considered by the competition of male RDs to get the harem with more hinds via roaring and fighting behaviors. By solving 12 benchmark functions and important engineering as well as multi-objective optimization problems, the superiority of the proposed RDA shows in comparison with other well-known and recent meta-heuristics.