Patient admission planning using Approximate Dynamic Programming

Tactical planning in hospitals involves elective patient admission planning and the allocation of hospital resource capacities. We propose a method to develop a tactical resource allocation and patient admission plan that takes stochastic elements into consideration, thereby providing robust plans. Our method is developed in an Approximate Dynamic Programming (ADP) framework and copes with multiple resources, multiple time periods and multiple patient groups with uncertain treatment paths and an uncertain number of arrivals in each time period. As such, the method enables integrated decision making for a network of hospital departments and resources. Computational results indicate that the ADP approach provides an accurate approximation of the value functions, and that it is suitable for large problem instances at hospitals, in which the ADP approach performs significantly better than two other heuristic approaches. Our ADP algorithm is generic, as various cost functions and basis functions can be used in various hospital setting

Making Strategic Supply Chain Capacity Planning more Dynamic to cope with Hyperconnected and Uncertain Environments

Public and private organizations cope with a lot of uncertainties when planning the future of their supply chains. Additionally, the network of stakeholders is now intensely interconnected and dynamic, revealing new collaboration opportunities at a tremendous pace. In such a context, organizations must rethink most of their supply chain planning decision support systems. This is the case regarding strategic supply chain capacity planning systems that should ensure that supply chains will have enough resources to profitably produce and deliver products on time, whatever hazards and disruptions. Unfortunately, most of the existing systems are unable to consider satisfactorily this new deal. To solve this issue, this paper develops a decision support system designed for making strategic supply chain capacity planning more dynamic to cope with hyperconnected and uncertain environments. To validate this decision support system, two industrial experiments have been conducted with two European pharmaceuticals and cosmetics companies

Decision support for optimal design of water distribution networks: A real options approach

12th International Conference on Computing and Control for the Water Industry, CCWI2013There is a growing concern about how the technical, managerial and financial capacity of drinking water systems can be sustained in the long run with future uncertainties. A water supply system is critical for the well- being of a community and it must provide water in sufficient quantity, of appropriate quality and without interruption. People have high expectations for the proper functioning of these systems but the future is uncertain and it is very difficult to conceive an infallible infrastructure. This work proposes a real options (ROs) approach that takes into account future uncertainty associated with water distribution networks. The ROs methodology extends traditional analysis to include flexible strategic implementation. This work describes a decision support methodology to design water networks that are adaptable over a long-term planning horizon. Representing design strategies as decision trees allows decision makers to easily adapt the system according to future circumstances. Results show that the ROs solution makes it possible to save on resources through an analysis based on an extended and uncertain planning horizonPrograma Operacional Factores de Competitividade – COMPETEFCT – Fundação para a Ciência e Tecnologi

Strategies for dynamic appointment making by container terminals

We consider a container terminal that has to make appointments with barges dynamically, in real-time, and partly automatic. The challenge for the terminal is to make appointments with only limited knowledge about future arriving barges, and in the view of uncertainty and disturbances, such as uncertain arrival and handling times, as well as cancellations and no-shows. We illustrate this problem using an innovative implementation project which is currently running in the Port of Rotterdam. This project aims to align barge rotations and terminal quay schedules by means of a multi-agent system. In this\ud paper, we take the perspective of a single terminal that will participate in this planning system, and focus on the decision making capabilities of its intelligent agent. We focus on the question how the terminal operator can optimize, on an operational level, the utilization of its quay resources, while making reliable appointments with barges, i.e., with a guaranteed departure time. We explore two approaches: (i) an analytical approach based on the value of having certain intervals within the schedule and (ii) an approach based on sources of exibility that are naturally available to the terminal. We use simulation to get insight in the benefits of these approaches. We conclude that a major increase in utilization degree could be achieved only by deploying the sources of exibility, without harming the waiting time of barges too much

Global supply chains of high value low volume products

Imperial Users onl