Combining Optimisation and Simulation Using Logic-Based Benders Decomposition

Operations research practitioners frequently want to model complicated functions that are are difficult to encode in their underlying optimisation framework. A common approach is to solve an approximate model, and to use a simulation to evaluate the true objective value of one or more solutions. We propose a new approach to integrating simulation into the optimisation model itself. The idea is to run the simulation at each incumbent solution to the master problem. The simulation data is then used to guide the trajectory of the optimisation model itself using logic-based Benders cuts. We test the approach on a class of stochastic resource allocation problems with monotonic performance measures. We derive strong, novel Benders cuts that are provably valid for all problems of the given form. We consider two concrete examples: a nursing home shift scheduling problem, and an airport check in counter allocation problem. While previous papers on these applications could only approximately solve realistic instances, we are able to solve them exactly within a reasonable amount of time. Moreover, while those papers account for the inherent variance of the problem by including estimates of the underlying random variables as model parameters, we are able to compute sample average approximations to optimality with up to 100 scenarios.Comment: 30 page

Mental healthcare utilization among head and neck cancer patients:A longitudinal cohort study

Objective: To investigate utilization of mental healthcare among head and neck cancer (HNC) patients from diagnosis to 2 years after treatment, in relation to psychological symptoms, mental disorders, need for mental healthcare, and sociodemographic, clinical and personal factors. Methods: Netherlands Quality of life and Biomedical Cohort study data as measured before treatment, at 3 and 6 months, and at 1 and 2 years after treatment was used (n = 610). Data on mental healthcare utilization (iMCQ), psychological symptoms (Hospital Anxiety and Depression Scale, Cancer Worry Scale), mental disorders (CIDI interview), need for mental healthcare (Supportive Care Needs Survey Short-Form 34, either as continuous outcome indicating the level of need or dichotomized into unmet need (yes/no)) and several sociodemographic, clinical and personal factors were collected. Factors associated with mental healthcare utilization were investigated using generalized estimating equations (p &lt; 0.05). Results: Of all HNC patients, 5%–9% used mental healthcare per timepoint. This was 4%–14% in patients with mild-severe psychological symptoms, 4%–17% in patients with severe psychological symptoms, 15%–35% in patients with a mental disorder and 5%–16% in patients with an unmet need for mental healthcare. Among all patients, higher symptoms of anxiety, a higher need for mental healthcare, lower age, higher disease stage, lower self-efficacy and higher social support seeking were significantly associated with mental healthcare utilization. Conclusion: Mental health care utilization among HNC patients is limited, and is related to psychological symptoms, need for mental healthcare, and sociodemographic, clinical and personal factors.</p

The OCareCloudS project: toward organizing care through trusted cloud services

The increasing elderly population and the shift from acute to chronic illness makes it difficult to care for people in hospitals and rest homes. Moreover, elderly people, if given a choice, want to stay at home as long as possible. In this article, the methodologies to develop a cloud-based semantic system, offering valuable information and knowledge-based services, are presented. The information and services are related to the different personal living hemispheres of the patient, namely the daily care-related needs, the social needs and the daily life assistance. Ontologies are used to facilitate the integration, analysis, aggregation and efficient use of all the available data in the cloud. By using an interdisciplinary research approach, where user researchers, (ontology) engineers, researchers and domain stakeholders are at the forefront, a platform can be developed of great added value for the patients that want to grow old in their own home and for their caregivers