scholarly journals Operating Room Scheduling in Teaching Hospitals

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Somayeh Ghazalbash ◽  
Mohammad Mehdi Sepehri ◽  
Pejman Shadpour ◽  
Arezoo Atighehchian

Operating room scheduling is an important operational problem in most hospitals. In this paper, a novel mixed integer programming (MIP) model is presented for minimizing Cmax and operating room idle times in hospitals. Using this model, we can determine the allocation of resources including operating rooms, surgeons, and assistant surgeons to surgeries, moreover the sequence of surgeries within operating rooms and the start time of them. The main features of the model will include the chronologic curriculum plan for training residents and the real-life constraints to be observed in teaching hospitals. The proposed model is evaluated against some real-life problems, by comparing the schedule obtained from the model and the one currently developed by the hospital staff. Numerical results indicate the efficiency of the proposed model compared to the real-life hospital scheduling, and the gap evaluations for the instances show that the results are generally satisfactory.

Author(s):  
Mohamed K. Omar

This chapter studies production and transportation problem confronting a speciality chemical company that has two manufacturing facilities. Facility I produces intermediate products which are then transported to Facility II where the end products are to be manufactured to meet customers’ demand. The author formulated the problem as a mixed integer programming (MIP) model that integrates the production and transportation decisions between the two facilities. The developed MIP aims to minimize the production, inventory, manpower, and transportation costs. Real industrial data are used to test and validate the developed MIP model. Comparing the model’s results and the company’s actual performance indicate that, if the company implemented the proposed model, significant costs savings could be achieved.


Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1702
Author(s):  
Jiun-Yan Shiau ◽  
Ming-Kung Huang ◽  
Chu-Yi Huang

The problem of staff scheduling in the airline industry is extensively investigated in operational research studies because efficient staff employment can drastically reduce the operational costs of airline companies. Considering the flight schedule of an airline company, staff scheduling is the process of assigning all necessary staff members in such a way that the airline can operate all its flights and construct a roster line for each employee while minimizing the corresponding overall costs for the personnel. This research uses a rostering case study of the ground staff in the aviation industry as an example to illustrate the application of integrating monthly and daily schedules. The ground staff in the aviation industry case is a rostering problem that includes three different types of personnel scheduling results: fluctuation-centered, mobility-centered, and project-centered planning. This paper presents an integrated mixed integer programming (MIP) model for determining the manpower requirements and related personnel shift designs for the ground staff at the airline to minimize manpower costs. The aim of this study is to complete the planning of the monthly and daily schedules simultaneously. A case study based on real-life data shows that this model is useful for the manpower planning of ground services at the airline and that the integrated approach is superior to the traditional two-stage approach.


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M A Tlili ◽  
H Sayeh ◽  
W Aouicha ◽  
M Souki ◽  
E Taghouti ◽  
...  

Abstract Background Currently, ensuring surgical safety remain a worldwide challenge. The description of operating room professionals' attitudes toward patient safety in their work units helps to identify strengths and weaknesses in term of patient safety, allowing a clearer vision of the safety aspects that require special attention. This study aimed to describe healthcare professionals' attitudes on patient safety in the Tunisian operating rooms. Methods This is a cross-sectional descriptive study spread over a 6-month period (October-April 2018). It was conducted among healthcare professionals working in the operating rooms of the two teaching hospitals of Sousse (Tunisia). The measuring instrument used is the Operating Room Management Attitudes Questionnaire (ORMAQ), which consists of 60 items spread over 8 dimensions. The latter has been subjected to a transcultural validation process inspired from the Vallerand method. Data entry and analysis was done by the Statistical Package for Social Sciences (SPSS.20) software. Results A total of 303 professionals participated in the study (participation rate= 76.13%). The most developed dimension was teamwork and the least developed was “Procedural errors/ compliance”. Items' results show that 94.8% of professionals confirmed that seniors should encourage medical and paramedical staff to ask questions, 53.5% of professionals stated that personal problems can adversely affect their performance and 87.5% agreed that operating rooms' team members share responsibilities for prioritizing activities in high workload situations. In addition, 50.9% of participants reported that the managers don't listen to staff or care about their concerns. Conclusions Operating rooms professionals' attitudes toward patient safety in their work units reflect an alarming situation regarding the quality of healthcare provided to patients. These results should be taken into consideration to guide future intervention on quality management improvement. Key messages Considering human factors is essential to improve safety in operating rooms and has an important role in reducing the occurrence of adverse events in these settings. It is important to study the underlying attitudes that determine the human factors for a better understanding and resolution of patient safety problems.


IEEE Pulse ◽  
2015 ◽  
Vol 6 (4) ◽  
pp. 10-13 ◽  
Author(s):  
Roy Phitayakorn ◽  
Wilton Levine ◽  
Emil Petrusa ◽  
Bethany Daily ◽  
Ersne Eromo ◽  
...  

Healthcare ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 152
Author(s):  
Yang-Kuei Lin ◽  
Min-Yang Li

Many healthcare institutions are interested in reducing costs and in maintaining a good quality of care. The operating room department is typically one of the most costly units in a hospital. Hospital managers are always interested in finding effective ways of using operating rooms to minimize operating costs. In this research, we study the operating room scheduling problem. We consider the use of a weekly surgery schedule with an open scheduling strategy that takes into account the availabilities of surgeons and operating rooms. The objective is to minimize the total operating cost while maximizing the utilization of the operating rooms but also minimizing overtime use. A revised mathematical model is proposed that can provide optimal solutions for a surgery size up to 110 surgical cases. Next, two modified heuristics, based on the earliest due date (EDD) and longest processing time (LPT) rules, are proposed to quickly find feasible solutions to the studied problem. Finally, an artificial bee colony (ABC) algorithm that incorporates the initial solutions, a recovery scheme, local search schemes, and an elitism strategy is proposed. The computational results show that, for a surgery size between 40 and 100 surgical cases, the ABC algorithm found optimal solutions to all of the tested problems. For surgery sizes larger than 110 surgical cases, the ABC algorithm performed significantly better than the two proposed heuristics. The computational results indicate that the proposed ABC is promising and capable of solving large problems.


2004 ◽  
Vol 13 (04) ◽  
pp. 931-944
Author(s):  
P. RADHA KRISHNA ◽  
J. SAILAJA RANI

Data mining is widely used to solve real-world problems in engineering, science and business. Usually the results from data mining obtained through the traditional approaches are not interpretable in the real life scenario. This paper suggests an approach for logical interpretations of the clustered data. Our approach involves using fuzzy ART technique for clustering the data and then applying the soft regression technique for interpreting the results of the clustering. The proposed model provides better analysis of data for describing overlapping clusters. We used our model to analyze patterns in the advances data of a public sector bank. Analyses and experiments show the effectiveness of the proposed method.


2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Tian Lan ◽  
Zhilin Li

<p><strong>Abstract.</strong> Schematic (network) maps are helpful for people to perform route planning and orientation tasks. The London Underground Map designed by Harry Beck is an excellent example of such maps. Generally, there are three approaches to generate schematic maps: manual, semi-automated (or computer-aided) and fully automated. In the past twenty years, many researchers have been devoted to the development of automated methods for generation of schematic maps. In these automated methods, various sets of constraints are used. Most of these constraints are for geometric properties of individual features (such as the lengths and orientations of lines); a few constraints are for relations between features (such as the minimum distance threshold between non-incident edges); but none are explicitly for the main structures of whole networks. It is believed that preservation of the main structure is the most important, because main structure is represented by global features which is first recognized by a pre-attentive process in human cognition – a global-to-local process (in which local features are then recognized by an attentive process). It is hypothesized here that an automated method with the preservation of main structures of networks should be able to generate schematic maps with improved clarity and aesthetics.</p><p>This paper describes the development of an automated method with the preservation of the main structures of line networks. In this method, automated schematization is treated as an optimization problem and is represented as a Mixed-Integer Programming (MIP) model, which consists of an objective function and a set of constraints. The preservation of main structures is modelled into constraints (i.e., making important lines straight and orientating them to specific directions) for the model. The MIP model is imported into a commercial optimization software called “IBM ILOG CPLEX Optimization Studio” (version 12.6.3) for the acquisition of optimal solutions (i.e., coordinates of vertices and edges on schematic maps). The whole process is shown in Figure 1.</p><p>Experimental evaluations have been conducted with a set of real-life data as shown in Figure 2a and 2d. Schematic maps are generated by this new method with the preservation of main structures and by an old method without the particular consideration for main structures, as shown in Figures 2b, 2c, 2e and 2f. A psychological test with a questionnaire has been conducted, which consists of questions regarding “clarity”, “recognition of major lines”, “visual simplicity” and “satisfaction”. It is found that, in all these four aspects, the map generated by new methods with preservation of main structures have higher scores than those by the old method. These improvements are proved to be significant after paired-t tests.</p><p>Therefore, it is concluded that the new automated method with the preservation of main structures can generate schematic maps with significant improvement in clarity and aesthetics. This study is helpful to improve automated methods for generation of schematic maps and other visual representations.</p>


2020 ◽  
Vol 13 (3) ◽  
pp. 451
Author(s):  
Jhunievieve Soriano ◽  
Eugene Rex Jalao ◽  
Iris Ann Martinez

Purpose: This research paper introduces an integrated employee scheduling problem that considers various real-life problems such as varying employee demand, different employee working conditions, and individual preferences regarding schedules.Design/methodology/approach: The proposed model, which is a combination of Analytic Hierarchy Process and Mixed Integer Linear Programming, is used to solve the problem with multi-dimensional objectivesFindings: Results show that the proposed model generates optimal and feasible solutions for weekly employee schedules.Originality/value: Many employee scheduling problems in literature are able to solve the employee scheduling problem to a large extent but still do not fully reflect current realistic organizational problems such as varying employee demand per hour inteval, different employee working conditions on disjoint shifts and breaks, and individual preferences regarding schedules all at the same time.


2019 ◽  
Vol 48 (1) ◽  
pp. 31-38
Author(s):  
Wen Xu ◽  
Yuyan Tan ◽  
Bishal Sharma ◽  
Ziyulong Wang

Due to several obvious advantages both in transport marketing and train operation planning, the cyclic timetable has already applied in many high-speed railway (HSR) countries. In order to adopt the cyclic timetable in China's HSR system, a Mixed Integer Programmer (MIP) model is proposed in this paper involving many general constraints, such as running time, dwell time, headway, and connection constraints. In addition, the real-world overtaking rule that concerning a train with higher priority will not be overtaken by a slower one is incorporated into the cyclic timetable optimization model. An approach based on fixed departure is proposed to get a cyclic timetable with minimum total journey time within a reasonable time. From numerical investigations using data from Guangzhou-Zhuhai HSR line in China, the proposed model and associated approach are tested and shown to be effective.


Author(s):  
İlker Küçükoğlu ◽  
Alkın Yurtkuran

Timetabling is one of the computationally difficult problems in scheduling and aims to find best time slots for a number of tasks which require limited resources. In this paper, we examine different solution approaches for the real-world examination timetabling problem (ETP) for university courses. The problem has unique hard and soft constraints, when compared to previous efforts, i.e. consecutive exams, sharing of rooms, room preferences, room capacity and number of empty slots. The aim of the problem is to achieve a timetable, which minimizes the total number of the examination slots without any conflicts. First, the real-world problem is formally defined and a mixed integer linear model is presented. Then, a constructive heuristic and a genetic algorithm based meta-heuristic are proposed in order to solve the ETP. Proposed approaches are tested on a problem set formed by using a real-life data. Results reveal that, proposed approaches are able to produce superior solutions in a limited time. Keywords: Timetabling, constructive heuristic, genetic algorithm;


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