Abstract
Medical training is an intricate and long process, which is compulsory to medical practice and often lasts up to twelve years for some specialties. Health stakeholders recognise that an adequate planning is crucial for health systems to deliver necessary care services. However, proper planning needs to account for complexity related with the setting of medical school vacancies and of residency programs, which are highly influenced by multiple stakeholders with diverse perspectives and views, as well as by the specificities of medical training. Aiming at building comprehensive models with a potential to assist health decision-makers, this article develops a multi-methodological framework to assist the planning of medical training under such a complex environment. It combines the structuring of the objectives and specificities of the medical training problem with a Soft Systems Methodology through the CATWOE (Customer, Actor, Transformation, Weltanschauung, Owner, Environment) approach, and the formulation of a Mixed Integer Linear Programming model that considers all relevant aspects. Considering the specificities of countries based on a National Health Service structure, a multi -objective planning model emerges, informing on how many vacancies should be opened/closed per year in medical schools and in each specialty. This model aims at (i) minimizing imbalances between medical demand and supply; (ii) minimizing costs; and (iii) maximizing equity across medical specialties. A case study in Portugal is explored so as to illustrate the applicability of the proposed multi-methodology, showing the relevance of proper structuring for planning models having the potential to inform health decision-makers and planners in practice.

Abstract
Physician emigration can either function as an escape valve to help the health labour market clear from a supply surplus, or aggravate the problem further in case of a shortage. Either way, policy-makers should be particularly aware and devise policies to minimize the occurrence of an imbalance in the physician workforce, which may require physician retention policies if barriers to entry and other market rigidities can not be removed. To this purpose we have developed an agent-based computational economics model to analyse physician emigration, and have used it to study the impact of potential short- and long-term retention policies. As a real case study we have calibrated it with data from Portugal, which features a very particular health system with many rigidities. Results show that all policies are capable of increasing the workforce size, but not all reduce emigration. Also, the effect of return migration is non-negligible, and may substantially offset the impact on the workforce size. Furthermore, the welfare impact of the policies varies considerably. Whether policies to retain physicians should be enacted or whether policy makers should let physicians go will depend on the type of imbalance present in the health system.

Abstract
Together with the significant improvement in health and longevity came a number of health and economic concerns related to the demand for healthcare services and resources: changes in the patterns of health and illness, increasing amount and complexity of healthcare services demanded, rising health expenditures and uncertainty about whether there will be enough human, physical and financial resources to deliver the healthcare services needed. This paper aims to draw attention to the importance of planning the demand for healthcare in the aforementioned context, to create awareness of the need for a comprehensive study on the demand for healthcare services and resources and to propose an integrated approach for planning them, to inform managers and policy-makers on what can be the main challenges on assuring healthcare delivery in the future.

Abstract
Most vehicle routing approaches disregard the need to refuel fleets. However, planners search for opportunities to refuel at lower prices even if, counter-intuitively, distant fuel stations need to be visited. We propose a novel mathematical formulation and develop branch-and-cut and matheuristic algorithms to efficiently tackle this problem. Results indicate that, to minimize costs, detour distances may increase up to 6 percentage points when fuel stations with lower prices are farther away from the depot. For practice, these insights imply that current policies disregarding station location and/or fuel prices along with "myopic" planning horizons may lead to sub-optimal decisions.

Abstract
The phenomenon of missed nursing care is endemic across all sectors. Nurse leaders have drawn attention to the implications of missed care for patient outcomes, with calls to develop clear political, methodological, and theoretical approaches. As part of this call, we describe three structural theories that inform frameworks of missed care: systems theory, economic theory, and neoliberal politics. The final section provides commentary on the strengths and limitations of these three theories, in the light of structuration theory and calls to balance this research agenda by reinstating nurse agency and examining the interactions between nurses as agents and the health systems as structures. The paper argues that a better understanding of variations in structure-agency interaction across the healthcare system might lead to more effective interventions at strategic leverage points.

Abstract
Distribution warehouses are a critical part of supply chains, representing a nonnegligible share of the operating costs. This is especially true for unautomated, labor-intensive warehouses, partially due to time-consuming activities such as picking up items or traveling. Inventory categorization techniques, as well as zone storage assignment policies, may help in improving operations, but may also be short-sighted. This work presents a three-step methodology that uses probabilistic simulation, optimization, and event-based simulation (SOS) to analyze and experiment with layout and storage assignment policies to improve the picking performance. In the first stage, picking performance is estimated under different storage assignment policies and zone configurations using a probabilistic model. In the second stage, a mixed integer optimization model defines the overall warehouse layout by selecting the configuration and storage assignment policy for each zone. Finally, the optimized layout solution is tested under demand uncertainty in the third, final simulation phase, through a discrete-event simulation model. The SOS methodology was validated with three months of operational data from a large retailer's warehouse, successfully illustrating how it may be successfully used for improving the performance of a distribution warehouse.