AI and OR in management of operations: history and trends

The last decade has seen a considerable growth in the use of Artificial Intelligence (AI) for operations management with the aim of finding solutions to problems that are increasing in complexity and scale. This paper begins by setting the context for the survey through a historical perspective of OR and AI. An extensive survey of applications of AI techniques for operations management, covering a total of over 1200 papers published from 1995 to 2004 is then presented. The survey utilizes Elsevier's ScienceDirect database as a source. Hence, the survey may not cover all the relevant journals but includes a sufficiently wide range of publications to make it representative of the research in the field. The papers are categorized into four areas of operations management: (a) design, (b) scheduling, (c) process planning and control and (d) quality, maintenance and fault diagnosis. Each of the four areas is categorized in terms of the AI techniques used: genetic algorithms, case-based reasoning, knowledge-based systems, fuzzy logic and hybrid techniques. The trends over the last decade are identified, discussed with respect to expected trends and directions for future work suggested

Pre-emptive resource-constrained multimode project scheduling using genetic algorithm: a dynamic forward approach

Purpose: The issue resource over-allocating is a big concern for project engineers in the process of scheduling project activities. Resource over-allocating drawback is frequently seen after scheduling of a project in practice which causes a schedule to be useless. Modifying an over-allocated schedule is very complicated and needs a lot of efforts and time. In this paper, a new and fast tracking method is proposed to schedule large scale projects which can help project engineers to schedule the project rapidly and with more confidence. Design/methodology/approach: In this article, a forward approach for maximizing net present value (NPV) in multi-mode resource constrained project scheduling problem while assuming discounted positive cash flows (MRCPSP-DCF) is proposed. The progress payment method is used and all resources are considered as pre-emptible. The proposed approach maximizes NPV using unscheduled resources through resource calendar in forward mode. For this purpose, a Genetic Algorithm is applied to solve. Findings: The findings show that the proposed method is an effective way to maximize NPV in MRCPSP-DCF problems while activity splitting is allowed. The proposed algorithm is very fast and can schedule experimental cases with 1000 variables and 100 resources in few seconds. The results are then compared with branch and bound method and simulated annealing algorithm and it is found the proposed genetic algorithm can provide results with better quality. Then algorithm is then applied for scheduling a hospital in practice. Originality/value: The method can be used alone or as a macro in Microsoft Office Project® Software to schedule MRCPSP-DCF problems or to modify resource over-allocated activities after scheduling a project. This can help project engineers to schedule project activities rapidly with more accuracy in practice.Peer Reviewe

An Optimisation-based Framework for Complex Business Process: Healthcare Application

The Irish healthcare system is currently facing major pressures due to rising demand, caused by population growth, ageing and high expectations of service quality. This pressure on the Irish healthcare system creates a need for support from research institutions in dealing with decision areas such as resource allocation and performance measurement. While approaches such as modelling, simulation, multi-criteria decision analysis, performance management, and optimisation can – when applied skilfully – improve healthcare performance, they represent just one part of the solution. Accordingly, to achieve significant and sustainable performance, this research aims to develop a practical, yet effective, optimisation-based framework for managing complex processes in the healthcare domain. Through an extensive review of the literature on the aforementioned solution techniques, limitations of using each technique on its own are identified in order to define a practical integrated approach toward developing the proposed framework. During the framework validation phase, real-time strategies have to be optimised to solve Emergency Department performance issues in a major hospital. Results show a potential of significant reduction in patients average length of stay (i.e. 48% of average patient throughput time) whilst reducing the over-reliance on overstretched nursing resources, that resulted in an increase of staff utilisation between 7% and 10%. Given the high uncertainty in healthcare service demand, using the integrated framework allows decision makers to find optimal staff schedules that improve emergency department performance. The proposed optimum staff schedule reduces the average waiting time of patients by 57% and also contributes to reduce number of patients left without treatment to 8% instead of 17%. The developed framework has been implemented by the hospital partner with a high level of success

Stochastic surgery selection and sequencing under dynamic emergency break-ins

Anticipating the impact of urgent emergency arrivals on operating room schedules remains methodologically and computationally challenging. This paper investigates a model for surgery scheduling, in which both surgery durations and emergency patient arrivals are stochastic. When an emergency patient arrives he enters the first available room. Given the sets of surgeries available to each operating room for that day, as well as the distributions of the main stochastic variables, we aim to find the per-room surgery sequences that minimise a joint objective, which includes over- and under-utilisation, the amount of cancelled patients, as well as the risk that emergencies suffer an excessively long waiting time. We show that a detailed analysis of emergency break-ins and their disruption of the schedule leads to a lower total cost compared to less sophisticated models. We also map the trade-off between the threshold for excessive waiting time, and the set of other objectives. Finally, an efficient heuristic is proposed to accurately estimate the value of a solution with significantly less computational effort.Anticipating the impact of urgent emergency arrivals on operating room schedules remains methodologically and computationally challenging. This paper investigates a model for surgery scheduling, in which both surgery durations and emergency patient arrivals are stochastic. When an emergency patient arrives he enters the first available room. Given the sets of surgeries available to each operating room for that day, as well as the distributions of the main stochastic variables, we aim to find the per-room surgery sequences that minimise a joint objective, which includes over- and under-utilisation, the amount of cancelled patients, as well as the risk that emergencies suffer an excessively long waiting time. We show that a detailed analysis of emergency break-ins and their disruption of the schedule leads to a lower total cost compared to less sophisticated models. We also map the trade-off between the threshold for excessive waiting time, and the set of other objectives. Finally, an efficient heuristic is proposed to accurately estimate the value of a solution with significantly less computational effort.A

Operating Room Scheduling Optimization Based on a Fuzzy Uncertainty Approach and Metaheuristic Algorithms

Today, planning and scheduling problems are the most significant issues in the world and make a great impact on improving organizational productivity and serving systems such as medical and healthcare providers. Since operating room planning is a major problem in healthcare organizations, the optimization of medical staff and equipment plays an essential role. Thus, this study presents a multi-objective mathematical model with a new categorization (preoperative, intraoperative, and postoperative) to minimize operating room scheduling and the risk of using equipment. Time constraints in healthcare systems and medical equipment limited capacity are the most significant considered limitation in the present study. In this regard, since the duration of patient preparation and implementation of treatment processes occur in three states of optimistic, pessimistic, and normal, the introduced parameters are examined relying on a fuzzy uncertainty analysis of the problem. Hence, the model is measured in a real numerical solution sample in a medical center to evaluate and confirm the proposed mathematical model. Then, two meta-heuristic algorithms (NRGA and NSGAII) are implemented on the mathematical model to analyze the proposed model. Finally, the research results indicate that the NSGA-II is more efficient in the operating room scheduling problem

Decision support systems for task scheduling: applications in manufacturing and healthcare

Esta Tesis se centra en el problema de la programación de tareas. Aunque pueden encontrarse diferentes definiciones de la programación de tareas en la literatura, aquí se define como la asignación de un número de tareas – acciones individuales que deben realizarse para completar un determinado proceso-, a un conjunto de recursos, en momentos de tiempo específicos. Pueden encontrarse ejemplos de programación de tareas en muchos contextos, como por ejemplo, el orden en el que deben fabricarse las diferentes partes de un coche, la asignación de quirófanos y cirujanos a intervenciones quirúrgicas en un hospital, o el orden en el que deben ser servidos los clientes de un restaurante. La programación de tareas supone un elemento clave en muchas compañías, en el campo de los servicios y en el de la fabricación, ya que es esencial para la coordinación del trabajo entre los diferentes actores involucrados, tales como departamentos, recursos (físicos y humanos) o entidades externas. En la mayoría de los casos, la programación de tareas conlleva trabajar con grandes cantidades de datos relacionados con el proceso y gestionar correctamente el conjunto de restricciones que controlan el proceso. Como consecuencia de esto, la programación de tareas suele hacerse con ayuda de herramientas informáticas que ofrecen algún tipo de soporte para el decisor. A este respecto, el auge de las Tecnologías de la Información (TI) en las últimas décadas ha ayudado enormemente al desarrollo de sistemas computarizados que ofrecen soporte a la toma de decisiones – Sistemas de Soporte a la Decisión (SSD) – en muchos ámbitos, incluyendo la programación de tareas. Además, ha habido un notable aumento en la capacidad computacional que ha hecho posible afrontar problemas de programación de tareas que se consideraban irresolubles hace algunos años. A pesar de estos avances, se ha detectado un gap entre teoría y práctica al llevar estas nuevas condiciones a la práctica, que puede ser demostrado por el limitado número de sistemas que se han implementado y aceptado por los usuarios satisfactoriamente. La hipótesis de trabajo de esta Tesis es que, para reducir este gap entre teoría y práctica, estos sistemas deberían considerar un conjunto de aspectos que se han estudiado en la literatura pero que no se han tenido en cuenta en el proceso de implementación, tales como el rol del decisor en el sistema, el contexto organizacional donde se toman las decisiones para la programación o la consideración de la programación como un proceso dinámico. Normalmente, cada vez que una empresa necesita implementar un SSD para la programación de tareas (SSDPT), es posible elegir entre dos opciones: adquirir una solución off-the-shelf, o diseñar y desarrollar una herramienta personalizada. Cuando se elige la primera opción, normalmente la solución no se adapta perfectamente a las actividades de la empresa, y considerando que la programación de tareas es muy dependiente del contexto, esta opción puede resultar en una situación muy documentada en la literatura en la que se consigue una implementación muy limitada en la que hay diferentes sistemas de información trabajando en paralelo para tener en cuenta las diferentes especificidades de la empresa. Por otro lado, si se opta por la segunda opción, esta suele derivar en largos tiempos de implementación con resultados pobres, ya que el equipo de desarrollo podría no tener en cuenta los errores y aciertos de otras implementaciones, tales como las funcionalidades que un sistema debería tener o los perfiles que se debería dar a los diferentes usuarios. Como resumen podríamos decir que el diseño y la implementación de SSDPT tienen un conjunto de problemas que constituyes una de las principales causas del gap existente entre la teoría de la programación de tareas y su implementación en la práctica. Para mejorar la actividad de diseño y desarrollo de SSDPT, el objetivo de esta tesis es proponer un framework común para el desarrollo de SSDPT. Para asegurar su validez y analizar su rango de aplicación, se analiza su factibilidad en dos sectores de aplicación, fabricación y salud, y se llevan a cabo dos casos de estudio en estos sectores. Para conseguir el objetivo general de la Tesis, se consideran un conjunto de objetivos específicos: 1. Proponer un framework para el diseño y desarrollo de SSDPT. • El framework tiene en cuenta todos los problemas detectados en la literatura que tienen que ver con los fallo a la hora de implementar este tipo de sistemas. Este framework se detalla mediante un conjunto de perspectivas. 2. Analizar las implementaciones existentes de SSDPT para analizar la alineación del framework propuesto con las implementaciones existentes de este tipo de sistemas en los dos campos de aplicación. • Se lleva a cabo una revisión sistemática de la literatura en SSDPT en fabricación. Las contribuciones revisadas se clasifican de acuerdo a las funcionalidades que presentan. Se analizan y discuten una serie de resultados y conclusiones de los mismos. Además se realiza una revisión de SSDPT comerciales para la programación de quirófanos. Estas contribuciones también se clasifican según sus funcionalidades y se presentan y discuten una serie de resultados y conclusiones. 3. Levar a cabo el diseño e implementación de dos SSDPT de acuerdo con el framework propuesto para demostrar su validez. • Basándonos en el framework un SSDPT para fabricación y un SSDPT para la programación de quirófanos han sido propuestos: i. El SSDPT para fabricación se implementó para una empresa de fabricación situada en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema. ii. El SSDPT para programación de quirófanos se implementó en un hospital situado en Sevilla. Primero se describe el contexto en el que el sistema actúa y el problema considerado. Después se estudian los principales casos de uso del sistema y se relacionan con el framework propuesto. Más tarde, se proponen una serie de métodos de resolución eficientes para el problema analizado. Finalmente, se realiza una breve discusión sobre los principales resultados de implementación del sistema.This thesis focuses on the problem of task scheduling. Although slightly different definitions of task scheduling can be found in the literature, here it is defined as the allocation of a number of tasks - single actions that must be performed to complete a specific process-, to a set of resources, at specific moments in time. Examples of task scheduling can be found in many settings, as for example, the order in which the different parts of a car have to be manufactured in a set of machines, the allocation of operating rooms and surgeons to the surgical interventions in a hospital, or the order in which the customers of a restaurant should be served. Clearly, task scheduling is a core activity of many companies, both in manufacturing and in services, as it is essential for the coordination of the work between the different involved actors, such as departments, resources (human and physical) or external entities. In most settings, task scheduling involves treating large amounts of data related to the process and properly handling the set of constraints controlling this process. As a consequence, task scheduling is usually carried out with the help of computer tools that offer some type of support to the decision maker. In this regard, the rising of Information Technologies (ITs) in the last decades has helped enormously to develop computer systems providing support for decision making - i.e. Decision Support Systems (DSSs) - for many decisions, including task scheduling. At the same time, there has been a notable increase in computer capacity that has made possible facing task scheduling problems that were considered unsolvable some years ago. Despite these advances, an important gap between theory and practice has been found when translating these new conditions into practice, as it can be proven by the relatively short number of documented systems that have been correctly implemented and accepted by users. The working hypothesis in this Thesis is that, in order to reduce this gap between theory and practice, these tools should consider a number of aspects that have been studied in the literature but that have not been taken into account in practice during the implementation process, such as the role of the decision makers in these tools, the organisational context where scheduling decisions take place or the consideration of scheduling as a dynamic process. Typically, each time a company requires to implement of a DSS for task scheduling, in the following DSSTS, it faces two different options: either acquiring an off-the-shelf solution, or designing and developing an in-house tool. If the former option is chosen, the acquired solution may not fit perfectly into the activities of the company, and, since task scheduling is company-specific, this approach may result in a situation widely documented in the literature where there exist limited implementations that needs information systems working in parallel to deal with the specificities of the company. On the contrary, the second option usually derives in large implementation times with poor results, as the development team may not take into account errors or successes from former implementations, such as the functionalities that the system should include or the profiles required for the decision makers among others. As a summary, the design and implementation of DSSTS suffer a number of problems which constitute a root cause for the existing gap between the scheduling theory and its implementation into practice. In order to improve the activity of designing and developing DSSTS, the aim of this thesis is to propose a common framework for the development of DSSTS. In order to ensure the validity and range of application of this framework, its feasibility is analysed within two specific fields of applications, namely manufacturing and healthcare, and two implementation case studies are conducted within these fields. In order to fullfil this general objective, a number of specific objectives can be detailed: 1. To propose a framework for the design and development of DSSTS. • This framework address all the issues found in literature regarding the common failures when implementing this type of systems. A number of perspectives of the framework are given in order to properly detail it. 2. To analyse existing implementations of DSSTS in order to check the alignment of the framework proposed with the task scheduling systems implemented in the two sectors chosen for the evaluation of the framework. • A systematic literature review on manufacturing DSSTS is carried out. The reviewed contributions are classified according to their functionalities. A number of findings and conclusions about these findings are discussed. Additionally, a review on commercial operating room DSSTS is done. These contributions are also classified according to their functionality and a number of findings and conclusions about these findings are discussed. 3. To conduct the design and implementation of two DSSTS according to the proposed framework in order to demonstrate its applicability. • Based on the proposed framework, a manufacturing DSSTS and an operating room DSSTS are implemented: i. The manufacturing DSSTS is applied to a real manufacturing company in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the hybrid flowshop scheduling problem with missing operations. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out. ii. The operating room DSSTS is applied to a real hospital in Sevilla. First, we describe the context where the DSSTS is deployed and the problem addressed, i.e. the the operating room scheduling problem. Then, the main use cases of the DSSTS are discussed and related to the framework. Next, a set of efficient solution procedures for the problem under study are proposed. And finally, a brief discussion on the main results of the implementation of the DSSTS is carried out

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions