Abstract
Starting in the 50s, healthcare workforce planning became a major concern for researchers and policy makers, since an imbalance of health professionals may create a serious insufficiency in the health system, and eventually lead to avoidable patient deaths. As such, methodologies and techniques have evolved significantly throughout the years, and simulation, in particular system dynamics, has been used broadly. However, tools such as stochastic agent-based simulation offer additional advantages for conducting forecasts, making it straightforward to incorporate microeconomic foundations and behavior rules into the agents. Surprisingly, we found no application of agent-based simulation to healthcare workforce planning above the hospital level. In this paper we develop a stochastic agent-based simulation model to forecast the supply of physicians and apply it to the Portuguese physician workforce. Moreover, we study the effect of variability in key input parameters using Monte Carlo simulation, concluding that small deviations in emigration or dropout rates may originate disparate forecasts. We also present different scenarios reflecting opposing policy directions and quantify their effect using the model. Finally, we perform an analysis of the impact of existing demographic projections on the demand for healthcare services. Results suggest that despite a declining population there may not be enough physicians to deliver all the care an ageing population may require. Such conclusion challenges anecdotal evidence of a surplus of physicians, supported mainly by the observation that Portugal has more physicians than the EU average.

Abstract
This paper proposes a logistic planner with supplementary 3D spatial representations to enhance and interact with traditional logistic systems on the context of mobile manipulators performing internal logistics operations. By defining a hierarchical structure, the logistic world model, as the central entity synchronized between multiple system components, the reliability and accuracy of the logistic system is strengthened. The proposed approach aims at implementing a robust and intuitive solution for the set-up of mobile manipulator based logistic systems. The logistic planner includes a web based interface for fast setup of the warehouse layout based on robot sensing, as well as the definition of missions for the fleet of robotic systems.

Abstract
A Dynamic Manufacturing Network (DMN) is the manufacturing industry application of the Virtual Enterprise (VE) business model based on real time information sharing and process integration. DMNs are normally formed and supported by a collaborative platform previously designed and built by a preexisting strategic partnership. The collaborative platform forms and tracks each DMN through all phases of its life cycle which leads to the accumulation and storage of large historical datasets on partner and customer characteristics and actions. This data holds the key to customer and manufacturer behavioral patterns and performances that can further be used in the decision making processes. In this study, we have focused on tackling this widely neglected research opportunity, by integrating manufacturer, order and customer data and characteristics into DMN formation and planning. The developed big data analytics approach consists of TOPSIS, fuzzy inference system and multi objective optimization techniques. Initially, by integrating the TOPSIS multi criteria decision making technique with a fuzzy inference system (FIS) we have computed indices for Manufacturer reliability and Order priority. Then we developed a multi-objective mixed integer linear programming (MILP) model to generate efficient solutions minimizing cost and assigning more reliable manufacturers to orders with higher priority.

Abstract
Logistic decisions involving the location of facilities in connection with vehicle routing appear in many contexts and applications. Given a set of potential distribution centers (DC) and a group of clients, the choice of which DC to open together with the design of a number of vehicle routes, satisfying clients' demand, may define Location-Routing Problems (LRP). This paper contributes with a new method, the 4-Phase Method (4-PhM), to deal with Capacitated LRP. Relevant advantages of 4-PhM are its generality, the possibilities of handling Multiple-Criteria and of facing large dimension problems. This last aptitude is a consequence of the sectorization phases, which permit a simplification of the solution space. Sectors are constructed by two Simulated Annealing based procedures, and they follow SectorEl, a sectorization approach inspired by electrostatics. In the last phase, the results obtained are evaluated using multicriteria analysis. Here, decision makers play an important role by reflecting preferences in a pairwise comparison matrix of the Analytic Hierarchy Process. Computational results, based on randomly generated instances, confirm the expectations about 4-PhM and its potentiality to deal with LRP.

Abstract
The role of urban freight vehicle trips in fulfilling the consumption needs of people in urban areas is often overshadowed by externality-causing parking practices (e.g., double-parking associated with traffic delays). Loading/unloading bays are generally viewed as an effective way to avoid freight vehicles double-parking, but are often misused by non-freight vehicles. We assess the potential of reducing freight vehicles double-parking mobility impacts by changing: (a) the spatial configuration (number, location, size) of loading/unloading bays and, (b) the non-freight vehicles parking rules compliance levels. Parking demand models were created with data from an establishment-based freight survey and a parking observation exercise. Two case studies were defined for 1 km(2) zones in the city of Lisbon, Portugal. Alternative bay systems were derived from an iterative implementation of the "maximize capacitated coverage" algorithm to a range of bays to be located. Parking operations in current and alternative bay systems were compared using a microsimulation. Bay systems' ability in reducing double-parking impacts was assessed via a set of indicators (e.g., average speed). Freight traffic causes a disproportionate amount of externalities and the current bay configuration leads to greater mobility impacts than some of the proposed systems. Enforcement was a crucial element in reducing parking operations impact on traffic flow in one of the case-studies. Road network characteristics were demonstrated to play a role in the adequate strategy of arranging the spatial configuration of bays.

Abstract
Knowledge management is still a problem for many organizations and at two different levels: tacit knowledge, which typically resides in the head of each individual and gets lost for the organizations when a person goes to work with a different company; and explicit knowledge, which presents growing costs for its dissemination in the organization. In the chapter, the author proposes a model to address those problems, taking for base the SECI (socialization, externalization, combination, and internalization) model, originally developed for knowledge management, together with an e-learning platform and a set of activities as tools to implement a working solution. Such models have the ability to solve organizational knowledge problems, implementing a knowledge management process, allowing the transformation of tacit knowledge into explicit knowledge. © 2018, IGI Global.