Modeling and improving the logistic distribution network of a hospital

This paper discusses using simulation and optimization to improve the hospital‐internal distribution network, for example, how to schedule and deliver the goods, which items should go on which cart, how to manage the variable consumption in the units, etc. We use a real case to build a simulation model to test various processes and incorporate an optimization algorithm to find the best distribution routes. The results highlight concrete improvements that could be made. These are the use of the same cart for different types of supplies to reduce the number of routes, the reduction of the distribution frequency for certain care units, and the use of optimized routes to reduce the transportation time.     

Human factors and qualitative pedagogical evaluation of a mobile augmented reality system for science education used by learners with physical disabilities

Technology-enhanced learning, employing novel forms of content representation and education service delivery by enhancing the visual perception of the real environment of the user, is favoured by proponents of educational inclusion for learners with physical disabilities. Such an augmented reality computer-mediated learning system has been developed as part of an EU funded research project, namely the CONNECT project. The CONNECT project brings together schools and science centres, and produces novel information and communication technologies based on augmented reality (AR) and web-based streaming and communication, in order to support learning in a variety of settings. The CONNECT AR interactive learning environment can assist users to better contextualize and reinforce their learning in school and in other settings where people learn (i.e. science centres and home). The CONNECT concept and associated technologies encourage users to visit science centres and perform experiments that are not possible in school. They can also build on these experiences back at school and at home with visual augmentations that they are communicated through web-based streaming technology. This paper particularly focuses on a user-centred evaluation approach of human factors and pedagogical aspects of the CONNECT system, as applied to a special needs user group. The main focus of the paper is on highlighting the human factors issues and challenges, in terms of wearability and technology acceptance, while elaborating on some qualitative aspects of the pedagogical effectiveness of the instructional medium that AR technology offers for this group of learners.

Analysing the factors that influence the Pareto frontier of a bi‐objective supply chain design problem

In this paper a bi‐objective multi‐product model for the design of a production/distribution supply chain logistic network with four echelons is considered. The proposed optimization model minimizes the total cost of the network (including the fixed cost to open facilities and the transportation costs between them) and the total CO₂ emissions. Five factors (network size, product complexity, cost variability, CO₂ emissions generation and over‐capacity) are considered for the experimental framework. The problem is solved using the ε‐constraint method and the resulting Pareto frontiers (PF) are characterized using five new metrics specifically developed for analysing how those factors affect the resulting optimal configurations. The results show that over‐capacity and product complexity are the two most influential factors regarding the characteristics of the PF, and that their effects are in the same direction: more complexity and capacity mean a wider set of optima alternatives, some close to the ideal point, and in general with a smaller number of links used.     

Rapid design closure of microwave components by means of feature‐based optimization and adjoint sensitivities

In this article, fast design closure of microwave components using feature‐based optimization (FBO) and adjoint sensitivities is discussed. FBO is one of the most recent optimization techniques that exploits a particular structure of the system response to “flatten” the functional landscape handled during the optimization process, which leads to reducing its computational complexity. When combined with gradient‐based search involving adjoint sensitivities, the design cost becomes even lower, allowing us to find the optimum design using just a few electromagnetic (EM) simulations of the structure at hand. Here, operation and performance of the algorithm is demonstrated using a waveguide filter and a miniaturized microstrip rat‐race coupler (RRC). Comparative studies indicate considerable savings that can be achieved even compared with adjoint‐based gradient search. In case of RRC, numerical results are supported by experimental validation.     

Usability and acceptance of truck dashboards designed by drivers: Two participatory design approaches compared to a user-centered design

Previous literature reported that Participatory Design (PD) results in satisfying products and presents other subjective benefits. PD implies an active involvement of users during all steps of the design process, including during concepts specification (contrary to user-centered design, UCD). This study compared the usability and acceptance of truck dashboards resulting either from a PD or from a UCD design processes. Moreover, design concepts from two PD approaches were compared: a collective versus an individual design session. Results showed that concepts resulting from user-centered design and individual design sessions were perceived as more useable and accepted than the concept resulting from the participatory workshop. These findings question PD benefits and encourage to further explore the different PD approaches in the industrial development of truck dashboards.     

Performance-based optimum seismic design of steel structures by a modified firefly algorithm and a new neural network

Structural optimization for performance-based seismic design (PBSD) in earthquake engineering aims at finding optimum design variables corresponding to a minimum objective function with constraints on performance requirements. In this study, an efficient methodology, consisting of two computational strategies, is presented for performance-based optimum seismic design (PBOSD) of steel moment frames. In the first strategy, a modified firefly algorithm (MFA) is proposed to efficiently find PBOSD at the performance levels. Because that for computing the structural responses at the performance levels a nonlinear static pushover analysis must be conducted, the overall computational time of optimization process is extremely large. In the second strategy, to reduce the computational burden, a new neural network model termed as wavelet cascade-forward back-propagation (WCFBP) is proposed to effectively predict the results of nonlinear pushover analysis during the optimization process. To illustrate the effectiveness of the proposed methodology, 3, 6 and 12 storey planar steel moment resisting frames are optimized for various performance levels. The results demonstrate the effectiveness of the proposed soft computing-based methodology for PBOSD of steel structures spending low computational cost.