Papers by Inneke VAN NIEUWENHUYSE
PLOS ONE, 2019
Motivation Patients with hematological malignancies are susceptible to life-threatening infection... more Motivation Patients with hematological malignancies are susceptible to life-threatening infections after chemotherapy. The current study aimed to evaluate whether management of such patients in dedicated inpatient and emergency wards could provide superior infection prevention and outcome. Methods We have developed an approach allowing to retrieve infection-related information from unstructured electronic medical records of a tertiary center. Data on 2,330 adults receiving 13,529 chemotherapy treatments for hematological malignancies were identified and assessed. Infection and mortality hazard rates were calculated with multivariate models. Patients were randomly divided into 80:20 training and validation cohorts. To develop patient-tailored risk-prediction models, several machine-learning methods were compared using area under the curve (AUC). Results Of the tested algorithms, the probit model was found to most accurately predict the evaluated hazards and was implemented in an online calculator. The infection-prediction model identified risk factors for infection based on patient characteristics, treatment and history. Observation of patients with a high predicted infection risk in general wards appeared to increase their infection hazard (p = 0.009) compared to similar patients observed in hematology units. The mortality-risk model demonstrated that for infection events starting at home, admission through hematology services was associated with a lower mortality hazard compared to admission through the general emergency department (p = 0.007). Both models show that dedicated hematological facilities and emergency services improve patient
Simulation of emergency department operations: a comprehensive review of KPIs and operational improvements
Computers & Industrial Engineering
Construction of fast retrieval model of e-commerce supply chain information system based on Bayesian network
Information Systems and e-Business Management
Research on agricultural supply chain system with double chain architecture based on blockchain technology
Future Generation Computer Systems
Comparison of Kriging-based algorithms for simulation optimization with heterogeneous noise
European Journal of Operational Research, 2017
A queueing model for a two-stage stochastic manufacturing system with overlapping operations
International Journal of Flexible Manufacturing Systems, 2005
This paper presents analytical expressions for estimating average process batch flow times throug... more This paper presents analytical expressions for estimating average process batch flow times through a stochastic manufacturing system with overlapping operations. It is shown that the traditional queueing methodology cannot be directly applied to this setting, as the use of the overlapping operations principle causes the arrival process of sublots at the second stage to be a non-renewal process. An embedded
Buffer sizing in multi-product multi-reactor batch processes: Impact of allocation and campaign sizing policies
European Journal of Operational Research, Jun 1, 2007
ABSTRACT This paper studies the impact of management policies, such as product allocation and cam... more ABSTRACT This paper studies the impact of management policies, such as product allocation and campaign sizing, on the required size of the finished goods inventories in a multi-product multi-reactor batch process. Demand, setup and batch processing times for these products are assumed to be stochastic, and the inventory buffer for every product type needs to be such that target customer service levels are met. To perform this analysis, we develop a queueing model that allows us to explicitly estimate service levels as a function of the buffer size, and the allocation/campaign sizing policies. This model can be used to evaluate the service level given an existing buffer configuration, as well as to determine the buffer sizes required across products to meet a pre-specified service level. It also allows us to formulate a number of insights into how product allocation decisions and campaign planning policies affect buffer sizing decisions in symmetric production systems.
The Vehicle Routing Problem: State of the Art Classification and Review
Computers & Industrial Engineering, 2015
In many warehouses, customer orders are batched to profit from a reduction in the order picking e... more In many warehouses, customer orders are batched to profit from a reduction in the order picking effort. This reduction has to be offset against an increase in sorting effort. This paper studies the impact of the order batching policy on average customer order throughput time, in warehouses where the picking and sorting functions are executed separately by either a single operator or multiple parallel operators. We present a throughput time estimation model based on Whitt's queuing network approach, assuming that the number of order lines per customer order follows a discrete probability distribution and that the warehouse uses a random storage strategy. We show that the model is adequate in approximating the optimal pick batch size, minimizing average customer order throughput time. Next, we use the model to explore the different factors influencing optimal batch size, the optimal allocation of workers to picking and sorting, and the impact of different order picking strategies such as sort-while-pick (SWP) versus pick-and-sort (PAS).
G-RAND: A phase-type approximation for the nonstationary G(t)/G(t)/s(t)+G(t) queue
ABSTRACT We present a Markov model to analyze the queueing behavior of the nonstationary G(t)/G(t... more ABSTRACT We present a Markov model to analyze the queueing behavior of the nonstationary G(t)/G(t)/s(t)+G(t) queue. We assume an exhaustive service discipline (where servers complete their current service before leaving) and use acyclic phase-type distributions to approximate the general interarrival, service, and abandonment time distributions. The time-varying performance measures of interest are: (1) the expected number of customers in queue, (2) the variance of the number of customers in queue, (3) the expected number of abandonments, and (4) the virtual waiting time distribution of a customer arriving at an arbitrary moment in time. We refer to our model as G-RAND since it analyzes a general queue using the randomization method. A computational experiment shows that our model allows the accurate analysis of small- to medium-sized problem instances.
Lean operations management gekwantificeerd
This paper presents an integrated production inventory model that enables to capture the tradeoff... more This paper presents an integrated production inventory model that enables to capture the tradeoffs between average inventory, production capacity and customer service level in a semiprocess industry setting. The model includes different features that are specific for such a setting, such as differences in reactor yield and quality requirements across products, the need for cleaning reactors when switching between product
A branch-and-bound algorithm for shift scheduling with stochastic nonstationary demand
Computers & Operations Research, 2015
It is now widely accepted that both large and small lot sizes can cause long lead times and conse... more It is now widely accepted that both large and small lot sizes can cause long lead times and consequently bad customer service in terms of late deliveries. The impact of the lot size on the lead time consists of a convex relationship, implying an optimal lot size minimising average lead time. In order to educate people with this undoubtedly correct, but yet controversial issue, we developed an educational software tool which helps to clarify the important determinants and allows for self-tuition experimentation. Therefore, in the first section we explain why this phenomenon is so important and how it can be applied in practice. In the second section, we introduce a small example and explain the theoretical foundations of the model. The third section describes the graphical user interface.
The objective of this article is to derive the density function and cumulative distribution funct... more The objective of this article is to derive the density function and cumulative distribution function for random variables which may be written as the sum of independent (either identical or non-identical) zerotruncated Poisson random variables. The obtained expressions may be particularly useful for modelling purposes, especially in view of linking common purchase quantity models from the marketing literature to stochastic production-inventory models from the operations management literature.
An adapted queueing model for estimating replenishment lead times in make-to-stock batch process industries
In this paper, we consider the problem of estimating the average and variance of replenishment le... more In this paper, we consider the problem of estimating the average and variance of replenishment lead time in a multi-product multi-reactor batch process with a base-stock inventory policy. The methodology used for this purpose is queueing theory. Although the body of knowledge on queueing theory has primarily been adopted in discrete manufacturing processes, we show that it is also applicable in semi-process industries. However, adequate changes to the models must be made in order to capture the specificities of this type of industry (such as batch processing, product allocation and campaign sizing).
This paper focuses on modelling the impact of lot splitting on average process batch flow times, ... more This paper focuses on modelling the impact of lot splitting on average process batch flow times, in a two-stage stochastic flowshop. It is shown that the traditional queueing methodology for estimating flow times cannot be directly applied to a system with lot splitting, as the arrival process of sublots at the second stage is not a renewal process. Consequently, an embedded queueing model is developed in order to approximate the average flow time of the flags through the system; from the flow time of the flags, the flow time of process batches can then be derived. The model turns out to yield very satisfactory results, and provides a tool to quantify the reduction in flow time that can be obtained by overlapping operations at different processing stages. Moreover, it allows to model the trade-off between flow time improvement and gap time occurrence by using it within the scope of a cost model.
Staffing and scheduling under nonstationary demand for service: A literature review
Omega, 2015
ABSTRACT
Simulation optimization in inventory replenishment: A classification
IIE Transactions, 2015
Our research focuses on improving the output rate of a single product CONWIP system. The system h... more Our research focuses on improving the output rate of a single product CONWIP system. The system has zero intermediate buffer capacity but may use time buffers which result from minimum and maximum processing times on each workstation. The transport between the different workstations is accomplished by a single resource (a bridge crane), constituting the bottleneck of the system. Since no mathematical approach exists to model this problem, we use simulation. To determine the parameters for the simulation scenarios, we rely on CONWIP, queueing and Factory Physics® literature. We apply the model to an industrial case. The results reveal major improvements in the output rate. The decision framework used, appears to be valuable for other real-life performance improvement applications based on simulation. The results also generate generic insights in improving production performance in similar systems.
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Papers by Inneke VAN NIEUWENHUYSE