Nico Nico Dellaert

Multimodal freight transportation planning: A literature review

Multimodal transportation offers an advanced platform for more efficient, reliable, flexible, and sustainable freight transportation. Planning such a complicated system provides interesting areas in Operations Research. This paper presents a structured overview of the multimodal transportation literature from 2005 onward. We focus on the traditional strategic, tactical, and operational levels of planning, where we present the relevant models and their developed solution techniques. We conclude our review paper with an outlook to future research directions.

Vehicle routing with soft time windows and stochastic travel times: A column generation and branch-and-price solution approach

We study a vehicle routing problem with soft time windows and stochastic travel times. In this problem, we consider stochastic travel times to obtain routes which are both efficient and reliable. In our problem setting, soft time windows allow early and late servicing at customers by incurring some penalty costs. The objective is to minimize the sum of transportation costs and service costs. Transportation costs result from three elements which are the total distance traveled, the number of vehicles used and the total expected overtime of the drivers. Service costs are incurred for early and late arrivals; these correspond to time-window violations at the customers. We apply a column generation procedure to solve this problem. The master problem can be modeled as a classical set partitioning problem. The pricing subproblem, for each vehicle, corresponds to an elementary shortest path problem with resource constraints. To generate an integer solution, we embed our column generation procedure within a branch-and-price method. Computational results obtained by experimenting with well-known problem instances are reported.

Reducing emergency department waiting times by adjusting work shifts considering patient visits to multiple care providers

Reducing Emergency Department (ED) overcrowding in the hope of improving the EDs operational efficiency and health care delivery ranks high on every health care decision makers wish list. The current study concentrates on developing efficient work shift schedules that make the best use of current resource capacity with the objectives of reducing patient waiting time and leveling resource utilization as much as possible. The study introduces two iterative heuristic algorithms, which combine simulation and optimization models for scheduling the work shifts of the ED resources: physicians, nurses and technicians. The algorithms are distinctive because they account for patients being treated by multiple care providers, possibly over the course of several hours, often with interspersed waiting. In such instances, patient arrival time is not a good indicator of when the various care providers are needed. The algorithms were tested using a detailed simulation based on data from five general hospital EDs. A patients Length of Stay (LOS) is measured as the time a patient spends in the ED until being admitted to the hospital or discharged. The first algorithm achieved an average reduction of between 20 and 45% in the total patient waiting time, which led to a reduction of between 7 and 17% in the combined average patient LOS. By allowing a restructure of the ED resource capacities, the second algorithm achieved an average reduction of between 20 and 64% in the total patient waiting time, leading to an 11 to 29% reduction in the combined average patient LOS.

One-stop-shop treatment for basal cell carcinoma, part of a new disease management strategy

Background  The number of skin cancer patients, especially patients with basal cell carcinoma (BCC), is rapidly increasing. Resources available at dermato‐oncology units have not increased proportionally, which affects the throughput time of patients.

Assessing and controlling the impact of hospital capacity planning on the waiting time

In the literature, tactical plans of elective patients aim at increasing hospital efficiency through a better resource utilisation, although hospitals claim that patient satisfaction, usually measured by the waiting time, is also important. In this regard, the purpose of this paper is to show how patient satisfaction can be associated with any tactical plan, by developing a method to compute exact waiting time distributions. We also present a procedure to calculate the exact levels of resource utilisation. Therefore, with our procedures, hospital managers can determine the operational performance of their tactical plan. We then explore two strategies to improve tactical plans in terms of waiting time: slack planning and smooth allocation. A case study based on data from a Dutch cardiothoracic surgery centre shows that slack planning leads to a trade-off between waiting time and hospital efficiency. When slack planning is combined to smooth allocation, additional improvements of the waiting time can be reached.

Integrated capacity and inventory decisions

This paper deals with the simultaneous acquisition of capacity and material in a situation with uncertain demand, with non-zero lead-times for the supply of both material and capacity. Although there is a lot of literature on the time-phased acquisition of capacity and material, most of this literature focuses on one of the two decisions. By using a dynamic programming formulation, we describe the optimal balance between using safety stocks and contingent workforce for various lead-time situations. We compare the cost ingredients of the optimal strategy with the standard inventory approach that neglects capacity restrictions in the decision. The experimental study shows that co-ordination of both decisions in the optimal strategy leads to cost reductions of around 10%.We also derive characteristics of the optimal strategy that we expect to provide a thorough basis for operational decision making.