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This work studies the scheduling of elective procedures, with stochastic durations, in surgery rooms. Given a set of rooms with limited availability and a set of procedures, it must be decided in which room and when each procedure will be performed. The problem's objectives are to maximize the use of the operating rooms and to minimize the delays i...
Citations
... Variants of this problem include the waste collection problem [42,43], arc routing problem [44], and multi-depot vehicle routing problem [45]. Simheuristics have also been employed to address facility layout problems [46,47], healthcare problems [48], and financial problems [49]. With regards to scheduling problems, simheuristics has been applied to address the permutation flow shop scheduling problem (FSSP) [20], and its variants such as blocking lot-streaming FSSP [50], distributed assembly FSSP [51], and parallel FSSP [52]. ...
The flexible shop scheduling problem (FJSSP) has been an extensively studied and applied manufacturing systems in recent years. However, research has mostly focused on addressing the FJSSP in its basic form by relaxing several practical constraints. In this work, we consider FJSSP with worker flexibility and uncertain processing times. A simheuristic approach addresses the multi-objective stochastic FJSSP with worker flexibility, minimizing the expected makespan and standard deviation of makespan. This approach integrates the Monte Carlo simulation (MCS) into the proposed multi-objective modified Backtracking Search Algorithm (MBSA) framework. MBSA employs an effective population initialization strategy, dynamic mutation and crossover operators, and a transfer criterion. MCS evaluates’promising’ solutions generated by MBSA to guide the search process. Extensive experiments are performed considering three FJSSP benchmark data sets. At first, the best parameters for the MBSA are identified using the Taguchi method. Then, for the deterministic variant of the problem, MBSA is compared with two other metaheuristics to demonstrate its effectiveness. Finally, the stochastic variant is investigated considering two factors: variation level and the probability distribution of the processing times. Computational results statistically show a significant effect of these factors on the objectives, demonstrating the importance of selecting an appropriate probability distribution in an uncertain environment.
For the hospital environment information technology (IT) is essential, as it determines the quality of hospitalization of patients, and creates patterns that help organize medical activity conceptually, therefore it determines the quality of medical care, and ultimately it determines the security of patients and hospital personnel, both from the point of view of monitoring in real-time gas concentration (oxygen, CO, CO2) in hospital rooms, air humidity, air temperature, and pressure. The system the authors designed and developed is an application of Telemedicine with the main purpose to streamline the patients' and medical personnel's security in case of fire or an over-limit concentration of harmful gases. Data gathered by sensors are processed by a microcontroller and it is sent every quarter of an hour to medical personnel smartphones in a user-friendly graphical display.
This paper proposes a literature review about the usage of simulation-based optimization tools in hospital environment and, more precisely, for operating rooms management. The usage of simulation, in its various forms, is gaining increasing attention in healthcare management because of its capability of describing the system in a high degree of detail as well as of modelling scenarios with different levels of available resources or uncertainty. In this respect, the contribution of this review study consists of classifying the literature about the topic, delineating the most debated themes and their internal relationships, and identifying the most prominent authors and papers. These results are achieved using a combination of bibliographic and bibliometric tools, commonly adopted in review studies, on a sample of 82 papers. On the basis of the findings, opportunities for future research activities are delineated.
This paper presents a systematic review of the literature relating to the usage of engineering tools and methods for increasing the efficiency of hospitals and their internal processes, with a particular attention to the management of operating rooms. By means of specific queries made on the Scopus database, a sample of 44 papers describing the usage of technical tools for process optimization in the healthcare context has been retrieved. Descriptive statistics are proposed to delineate the trend of the research in time and to identify the top journals by number of terms of publications. Then, a more in depth analysis has been made, for classifying the papers in terms of their primary focus, tool and performance parameters used for evaluating the efficiency of the system. From the set of analyses made, useful indications are derived for a practical usage of the tools identified, as well as interesting suggestions for future research activities.
This paper addresses the daily appointment scheduling (AS) of patients in a hospital-integrated facility where outpatients and inpatients are treated simultaneously and share critical resources. We propose a lean approach based on the pull-strategy “Constant Work in Process” (ConWIP) to develop robust and easy-to-implement AS rules. Our objective is to reduce patients’ waiting time and maximise the use rate of resources while considering the global surgical process and stochastic service times. The AS rules based on ConWIP are evaluated using a Discrete-Event-Simulation model. Numerical experiments based on a real-life case study are carried out to assess the proposed appointment rules’ performance and compare them to AS rules developed in the literature. The results highlight the robustness of our approach and demonstrate its usefulness in practice.
This paper provides a comprehensive survey of research on operating room planning and scheduling problems. Aiming to give a comprehensive classification on the studied problems, we review the literature from the perspectives of decision level, scheduling strategy, patient characteristics, problem setting, uncertainty, mathematical models, and solutions and methods. The papers are reviewed in diversified ways so as to obtain a detailed overview in this area, and the fields that need to be focused on are summarized. It shows that mathematical programming and heuristics are frequently applied in the complex linear and combinatorial optimization problems. Furthermore, future research trends and directions on operating room planning and scheduling are also identified. © 2018 Springer Science+Business Media, LLC, part of Springer Nature
