Abstract
Public transport networks were, in the past, mainly designed to maximize the efficiency of commuting trips. However, with such perspective there are considerable risks to marginalize some specific population groups (e.g. disabled, elderly, children, pregnant, people in poverty). For enhancing social inclusion and improving the accessibility of more vulnerable citizens, such networks are often redesigned and adjusted. Nevertheless, even with such adjustments, it is sometimes difficult to provide efficient services that fully address the real needs and capabilities of travelers, partially because of the failure in following the fast technological and demanding changes of modern societies. Taking in mind these challenges, we have developed a conceptual model to support knowledge sharing and decision-making in urban mobility, and to improve the way travel information is addressed. The multi-user integrated platform proposed in this work is supported by the idea that information from different channels must be centralized, organized, managed and properly distributed. This idea is grounded in two main principles: (i) past and real-time information from a wide range of sources is combined for knowledge extraction, and such knowledge is going to be used not only to allow travelers to better plan their trips, but also to help transport providers to develop services adapted to the needs and preferences of their customers; and (ii) information is provided in a personalized way taking into account socio-economical differences between groups of travelers. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
The multi-facility layout problem involves the physical organization of departments inside several facilities, to allow flexible and efficient operations. This work studies the facility layout problem in a new perspective, considering a group of facilities, and two different concerns: the location of departments within a group of facilities, and the location of departments inside each facility itself. The problem is formulated as a Quadratic Programming Problem with multiple objectives and unequal areas, allowing layout reconfigurations in each planning period. The objectives of the model are: the minimization of costs (material handling inside facilities and between facilities, and re-layout); the maximization of adjacency between departments; and the minimization of the "unsuitability" of department positions and locations. This unsuitability measure is a new objective proposed in this work, to combine the characteristics of existing locations with the requirements of departments. The model was tested with data from the literature as well as with a problem inspired in a first tier supplier in the automotive industry. Preliminary results show that this work can be viewed as an innovative and promising integrated approach for tackling real, complex facility layout problems.

Abstract
This study addresses the product-launch planning problem in the chemical-pharmaceutical industry under technical and market uncertainties, and considering resource limitations associated to the need of processing in the same plant products under development and products in commercialization. A novel approach is developed by combining a mixed integer linear programming (MILP) model and a Monte Carlo simulation (MCS) procedure, to deal with the integrated process design and production planning decisions during the New Product Development (NPD) phase. The Monte Carlo simulation framework was designed as a two-step sampling procedure based on Bernoulli and Normal distributions. Results show the unquestionable influence of the uncertainty parameters on the decision variables and objective function, thus highlighting the inherent risks associated to the deterministic models. Process designs and scale-ups that maximize expected profit were determined, providing a valuable knowledge frame to support the long-term decision-making process, and enabling earlier and better decisions during NPD.

Abstract
When public authorities face the need to improve a transportation system, they normally have to make a difficult choice among a set of technological and operational alternatives. To help the correct evaluation of each alternative and its impacts, costs and benefits, it would be useful to have a decision support tool based on approaches such as Multi-Criteria Decision Analysis (MCDA) and/or Cost-Benefit Analysis (CBA). Among the many impacts caused by a public transportation system, typically those on the land use are not adequately considered in the decision-making processes, mainly because they are hard to monetize, they are often considered as value transfer instead of value creation, and they are too complex to be assessed by traditional transport modelling tools. To overcome these weaknesses, the objectives of this research are to identify and measure the impacts of transit systems on land use and accessibility, and to consider those impacts in decision-making processes, along with more traditional financial and transport related impacts. For this purpose, a decision support tool, combining a land use and transport model with a MCDA model, was developed and assessed in a small case study. In future work, sensitivity and risk analysis will be incorporated, to more accurately and realistically reflect uncertainties and exogenous conditions that may significantly affect the costs and the benefits of a project. Finally, this decision support tool will be fully assessed in a study of the Green Line extension project in Boston, USA. (C) 2017 The Authors. Published by Elsevier B.V.

Abstract
The container loading problem (CLP) is a real-world driven, combinatorial optimisation problem that addresses the maximisation of space usage in cargo transport units. The research conducted on this problem failed to fulfill the real needs of the transportation industry, owing to the inadequate representation of practical-relevant constraints. The dynamic stability of cargo is one of the most important practical constraints. It has been addressed in the literature in an over-simplified way which does not translate to real-world stability. This paper proposes a physics simulation tool based on a physics engine, which can be used to translate real-world stability into the CLP. To validate the tool, a set of benchmark tests is proposed and the results obtained with the physics simulation tool are compared to the state-of-the-art simulation engineering software Abaqus Unified FEA. Analytical calculations have been also conducted, and it was also possible to conclude that the tool proposed is a valid alternative. Copyright © 2017 Inderscience Enterprises Ltd.

Abstract
Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Product lifecycle management research tends to focus on situations that are responsive to formal analysis and modelling. However, in several domains such as knowledge intensive collaborative environments, it's not possible to model processes using formal notations. Knowledge based and collaborative process management involves a combination of structured and non-structured processes. Structured processes management can be reduced to a set of fully-defined rules leading to high efficiency but also low flexibility, whereas the management of non-structured processes is not prone to a full formalization. A combination of both structured and unstructured management approaches is required in order to achieve a successful trade-off between efficiency, flexibility and controllability. We call a process as semi-structured when it contains both structured and non-structured sub-processes leading to a flexible and efficient hybrid approach. Large enterprise information systems, impose structured and predictable workflows, while knowledge based collaborative processes are unpredictable to some extent, involving high amount of human-decision. Moreover, large enterprise information systems are not able to manage the daily ad hoc communication inherent to the knowledge-based process itself. This paper introduces a set of concepts, methods and tools of an innovative Hybrid Process Management approach validated by a real world business case in the automotive industry.