A heuristic algorithm for nurse scheduling with balanced preference satisfaction

This paper tackles the nurse scheduling problem with balanced preference satisfaction which consists of generating an assignment of shifts to nurses over a given time horizon and ensuring that the satisfaction of nurses personal preferences for shifts is as even as possible in order to ensure fairness. We propose a heuristic algorithm based on successive resolutions of the bottleneck assignment problem. The algorithm has two phases. In the first phase, the algorithm constructs an initial solution by solving successive bottleneck assignment problems. In the second phase, two improvement procedures based on reassignment steps are applied. Computational tests are carried out using instances from the standard benchmark dataset NSPLib. Our experiments indicate that the proposed method is effective and efficient, reducing discrepancies (hence improving fairness) between the individual rosters

A heuristic algorithm for nurse scheduling with balanced preference satisfaction

This paper tackles the nurse scheduling problem with balanced preference satisfaction which consists of generating an assignment of shifts to nurses over a given time horizon and ensuring that the satisfaction of nurses personal preferences for shifts is as even as possible in order to ensure fairness. We propose a heuristic algorithm based on successive resolutions of the bottleneck assignment problem. The algorithm has two phases. In the first phase, the algorithm constructs an initial solution by solving successive bottleneck assignment problems. In the second phase, two improvement procedures based on reassignment steps are applied. Computational tests are carried out using instances from the standard benchmark dataset NSPLib. Our experiments indicate that the proposed method is effective and efficient, reducing discrepancies (hence improving fairness) between the individual rosters

Model Penjadwalan Perawat di Rumah Sakit

Dalam penelitian ini dibahas model penjadwalan perawat di rumah sakit yang meminimumkan total deviasi (penyimpangan) hari kerja setiap perawat dengan mempertimbangkan kebutuhan jumlah perawat, shift malam, dan kebutuhan day off dari tiap-tiap perawat serta beberapa kendala teknis lain yang perlu diperhatikan oleh pihak manajemen rumah sakit. Model penjadwalan perawat ini diformulasikan dalam bentuk Integer Linear Programming dan diproses dengan menggunakan software LINGO 8.0

Welcome to OR&S! Where students, academics and professionals come together

In this manuscript, an overview is given of the activities done at the Operations Research and Scheduling (OR&S) research group of the faculty of Economics and Business Administration of Ghent University. Unlike the book published by [1] that gives a summary of all academic and professional activities done in the field of Project Management in collaboration with the OR&S group, the focus of the current manuscript lies on academic publications and the integration of these published results in teaching activities. An overview is given of the publications from the very beginning till today, and some of the topics that have led to publications are discussed in somewhat more detail. Moreover, it is shown how the research results have been used in the classroom to actively involve students in our research activities

Homecare staff scheduling with three-step algorithm

This paper introduces a three-step algorithm, an efficient framework for solving a homecare staff scheduling problem (HSSP) service schedule, a multi-objective problem requiring a combination of the VRP and the staff scheduling problem. The proposed scheduling technique takes account of the design of optimal daily service routes and the dispatch of caregivers to visit patients under time and capacity constraints. The framework consists of three major stages: Step 1) Route scheduling creates effective routes for homecare caregivers to service patients at different task locations with the shortest path. Step 2) Resource selection seeks to match qualified staff to each route with the minimum cost and preferences under possible time, qualification requirement constraints, and modes of transportation. Step 3) Local improvement enhances the output solution generated by the resource selection by swapping tasks based on the cost function. Our empirical study reveals that the proposed scheduling technique can explore the improved service plan for an adapted case study with the minimum service cost and highest efficiency for arranging service tasks compared to the manual procedure

Implementasi Teknik Column Generation pada Penyelesaian Masalah Penjadwalan Perawat

ABSTRAK Penelitian ini membahas masalah penyusunan jadwal perawat yang sesuai dengan keinginan perawat. Pada kenyataannya, kemungkinan pola penjadwalan perawat jumlahnya sangat banyak. Akibatnya, model optimisasi penjadwalan perawat akan melibatkan kolom yang sangat besar. Oleh karena itu, penelitian ini menerapkan teknik column generation untuk menyelesaikan masalah penjadwalan secara efisien. Teknik column generation bekerja dengan cara membangun master problem, membentuk Restricted Master Problem (RMP), menyelesaikan LP relaksasi dari RMP, dan membangun subproblem yang akan diselesaikan hanya jika diperlukan. Hasil implementasi teknik column generation pada masalah penjadwalan perawat di sebuah rumah sakit di Kabupaten Cirebon menunjukkan bahwa teknik column generation dapat menyelesaikan masalah penjadwalan perawat dan mampu memenuhi seluruh pemilihan slot-waktu yang diinginkan oleh perawat. Kata Kunci: Column generation, Integer Programming, Penjadwalan, Solusi Optimal, Program linier. ABSTRACT This research study about nurse scheduling problems which accordance the wishes of the nurse. In fact, the number of feasible nurse scheduling patterns is too large. Hence, there are the large number of columns in the optimization model. This research applies column generation techniques to solve the nurse scheduling problem effeciently. The technique works by constracting a master problem, forming Restricted Master Problem (RMP), solving LP relaxation of RMP, and constructing subproblems and then, solve them if necessarry. The results show that the column generation technique on the problem of scheduling nurses in a hospital in Cirebon Regency show that the column generation technique can solve the nurse scheduling problem of a hospital in Cirebon Regency and is able to fulfill all the time slot selections desired by nurses. Keywords: Column generation, Integer Programming, Scheduling, Optimal Solution, Linier Programming

MODEL PENJADWALAN PERAWAT DI RUMAH SAKIT

Dalam penelitian ini dibahas model penjadwalan perawat di rumah sakit yang meminimumkan total deviasi (penyimpangan) hari kerja setiap perawat dengan mempertimbangkan kebutuhan jumlah perawat, shift malam, dan kebutuhan day off dari tiap-tiap perawat serta beberapa kendala teknis lain yang perlu diperhatikan oleh pihak manajemen rumah sakit. Model penjadwalan perawat ini diformulasikan dalam bentuk Integer Linear Programming dan diproses dengan menggunakan software LINGO 8.0

A harmony search algorithm for nurse rostering problems

Harmony search algorithm (HSA) is a relatively new nature-inspired algorithm. It evolves solutions in the problem search space by mimicking the musical improvisation process in seeking agreeable harmony measured by aesthetic standards. The nurse rostering problem (NRP) is a well-known NP-hard scheduling problem that aims at allocating the required workload to the available staff nurses at healthcare organizations to meet the operational requirements and a range of preferences. This work investigates research issues of the parameter settings in HSA and application of HSA to effectively solve complex NRPs. Due to the well-known fact that most NRPs algorithms are highly problem (or even instance) dependent, the performance of our proposed HSA is evaluated on two sets of very different nurse rostering problems. The first set represents a real world dataset obtained from a large hospital in Malaysia. Experimental results show that our proposed HSA produces better quality rosters for all considered instances than a genetic algorithm (implemented herein). The second is a set of well-known benchmark NRPs which are widely used by researchers in the literature. The proposed HSA obtains good results (and new lower bound for a few instances) when compared to the current state of the art of meta-heuristic algorithms in recent literature

A heuristic algorithm based on multiassignment procedures for nurse scheduling

This paper tackles a Nurse Scheduling Problem which consists of generating work schedules for a set of nurses while considering their shift preferences and other requirements. The objective is to maximize the satisfaction of nurses? preferences and minimize the violation of soft constraints. This paper presents a new deterministic heuristic algorithm, called MAPA (multi-assignment problem-based algorithm), which is based on successive resolutions of the assignment problem. The algorithm has two phases: a constructive phase and an improvement phase. The constructive phase builds a full schedule by solving successive assignment problems, one for each day in the planning period. The improvement phase uses a couple of procedures that re-solve assignment problems to produce a better schedule. Given the deterministic nature of this algorithm, the same schedule is obtained each time that the algorithm is applied to the same problem instance. The performance of MAPA is benchmarked against published results for almost 250,000 instances from the NSPLib dataset. In most cases, particularly on large instances of the problem, the results produced by MAPA are better when compared to best-known solutions from the literature. The experiments reported here also show that the MAPA algorithm finds more feasible solutions compared with other algorithms in the literature, which suggest that this proposed approach is effective and robust