Shift rostering using decomposition: assign weekend shifts first

This paper introduces a shift rostering problem that surprisingly has not been studied in 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 using an existing algorithm. We 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 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 shows to be effective when incorporated in a commercially implemented algorithm

ナース・スケジューリングにおける部分問題実行可能解空間のネットワーク表現

要旨あり最適化技術に基づく統計的推論原著論

An Optimization Technique to Prepare Nurse Schedule for a Monthly TIME Horizon

Nurse scheduling problem is one of the most difficult scheduling problems to solve since its solution space is large and it expects to comply many constraints. There is no standard model or a method of solution for nurse scheduling. The main objective of this study is to search for a scientific method to prepare a monthly working schedule for a group of nursing officers employed in a hospital. We propose an optimization method to prepare an optimal schedule. Initially, we develop an optimization model by formulating the objective and the constraints of the problem. The optimization model that we are interestedin is a 0-1 Integer Linear Programming problem. We apply the Branch-and-Bound technique to solve the problem using the optimization software package LINGO. Finally, the solution to the optimization problem is formulated to a regular nurse schedule. The methodology is illustrated by preparing a monthly schedule for a private hospital in Sri Lanka

Nurse Rostering: A Tabu Search Technique With Embedded Nurse Preferences

The decision making in assigning all nursing staffs to shift duties in a hospital unit must be done appropriately because it is a crucial task due to various requirements and constraints that need to be fulfilled. The shift assignment or also known as roster has a great impact on the nurses’ operational circumstances which are strongly related to the intensity of quality of health care. The head nurse usually spends a substantial amount of time developing manual rosters, especially when there are many staff requests. Yet, sometimes she could not ensure that all constraints are met. Therefore, this research identified the relevant constraints being imposed in solving the nurse rostering problem (NRP) and examined the efficient method to generate the nurse roster based on constraints involved. Subsequently, as part of this research, we develop a Tabu Search (TS) model to solve a particular NRP. There are two aspects of enhancement in the proposed TS model. The first aspect is in the initialization phase of the TS model, where we introduced a semi-random initialization method to produce an initial solution. The advantage of using this initialization method is that it avoids the violation of hard constraints at any time in the TS process. The second aspect is in the neighbourhood generation phase, where several neighbours need to be generated as part of the TS approach. In this phase, we introduced two different neighbourhood generation methods, which are specific to the NRP. The proposed TS model is evaluated for its efficiency, where 30 samples of rosters generated were taken for analysis. The feasible solutions (i.e. the roster) were evaluated based on their minimum penalty values. The penalty values were given based on different violations of hard and soft constraints. The TS model is able to produce efficient rosters which do not violate any hard constraints and at the same time, fulfill the soft constraints as much as possible. The performance of the model is certainly better than the manually generated model and also comparable to the existing similar nurse rostering model

New Approach Combining Branch and Price with Metaheuristics to Solve Nurse Scheduling Problem

This paper presents a new approach combining Branch and Price (B&P) with metaheuristics to derive various high-quality schedules as solutions to a nurse scheduling problem (nurse rostering problem). There are two main features of our approach. The first is the combination of B&P and metaheuristics, and the second is the implementation of an efficient B&P algorithm. Through applying our approach to widely used benchmark instances, the effectiveness of our approach is determined

Adaptation of Shift Sequence Based Method for High Number in Shifts Rostering Problem for Health Care Workers

Purpose—is to investigate a shift sequence-based approach efficiency then problem consisting of a high number of shifts. Research objectives:• Solve health care workers rostering problem using a shift sequence based method.• Measure its efficiency then number of shifts increases. Design/methodology/approach—Usually rostering problems are highly constrained.Constraints are classified to soft and hard constraints. Soft and hard constraints of the problem are additionally classified to: sequence constraints, schedule constraints and roster constraints. Sequence constraints are considered when constructing shift sequences. Schedule constraints are considered when constructing a schedule. Roster constraints are applied, then constructing overall solution, i.e. combining all schedules.Shift sequence based approach consists of two stages:• Shift sequences construction,• The construction of schedules.In the shift sequences construction stage, the shift sequences are constructed for each set of health care workers of different skill, considering sequence constraints. Shifts sequences are ranked by their penalties for easier retrieval in later stage.In schedules construction stage, schedules for each health care worker are constructed iteratively, using the shift sequences produced in stage 1. Shift sequence based method is an adaptive iterative method where health care workers who received the highest schedule penalties in the last iteration are scheduled first at the current iteration. During the roster construction, and after a schedule has been generated for the current health care worker, an improvement method based on an efficient greedy local search is carried out on the partial roster. It simply swaps any pair of shifts between two health care workers in the (partial) roster, as long as the swaps satisfy hard constraints and decrease the roster penalty.Findings—Using shift sequence method for solving health care workers rostering problem is inefficient, because of large amount of shifts sequences (feasible shifts sequences are approximately 260 thousands).In order to speed up roster construction process shifts are grouped to four groups: morning shifts, day shifts, night shifts and duty shifts. There are only 64 feasible shifts sequences, in this case.After roster construction shift groups are replaced with the one of shift belonging to that group of shifts.When all shifts are added to roster, computation of workload for each schedule is performed. If computed workload is equal to the one defined in working contract, then this schedule is complete, else begin shifts revision process. During revision process those schedules are considered which do not meet work contract requirements.If computed workload is larger than the one defined in working contract, each shift is replaced with the shift, if it’s possible, with lesser duration time. If computed workload is lesser than the one defined in working contract, each shift is replaced with the shift, if it’s possible, with larger duration time.This process continues while schedule does not meet workload requirement defined in working contract or no further improvement can be made.Research limitations/implications—Problem dimension: 27 health care workers, 15 shifts, over 20 soft constraints, rostering period—one calendar month.Practical implications – modifications made to shift sequence based approach allows to construct a roster for one of the major Lithuania’s hospitals personnel in shorter time.Originality/Value—modification of shift sequence based approach is proposed

Fairness aspects in personnel scheduling

In industries like health care, public transport or call centers a shift-based system ensures permanent availability of employees for covering needed services. The resource allocation problem – assigning employees to shifts – is known as personnel scheduling in literature and often aims at minimizing staffing costs. Working in shifts, though, impacts employees’ private lives which adds to the problem of increasing staff shortage in recent years. Therefore, more and more effort is spent on incorporating fairness into scheduling approaches in order to increase employees’ satisfaction. This paper presents a literature review of approaches for personnel scheduling considering fairness aspects. Since fairness is not a quantitative objective, but can be evaluated from different point of views, a large number of fairness measurements exists in the literature. Furthermore, perspective (group vs individual fairness) or time horizon (short-term vs long-term fairness) are often considered very differently. To conclude, we show that a uniform definition and approach for considering fairness in personnel scheduling is challenging and point out gaps for future research