Abstract
The author's wishes to make the following correction: all the IAE values presented in the paper are multiplied by a factor of 100. The authors would like to apologise for any inconvenience caused. © 2015 Elsevier B.V.

Abstract
Sensors based on long-period fiber gratings (LPFGs) over coated with metal oxide were fabricated and characterized for refractive index (RI) sensing. Oxidation of Ni, Ti, Al, and Cr was monitored in real time by following the features of the LPFG attenuation band. Themetals were deposited simultaneously on top of Si substrates for further chemical and morphological analysis. Wavelength sensitivities (nm/RIU) of about 10 437 at 1.432, 1150 at 1.400, 20 125 at 1.448, and 875 at 1.420 were achieved for LPFGs coated, with 68 nm of Ni, 60 nm of TiO2, 50 nm of Al2O3, and 62 nm of Cr2O3, respectively. For surrounding RI higher than the cladding RI, the wavelength sensitivities are 1937, 6801, 5762, and 3051 nm/RIU at 1.457 for the Ni, Ti, Al, and Cr oxides, respectively. Working as intensity sensing devices sensitivities up to 167 dB/RIU were measured. Metal oxide coated LPFGs leads to wavelength sensitivity enhancement comparing to bare LPFGs and may be used in systems with RI higher than the fiber cladding, a region where bare LPFGs are insensitive.

Abstract
This study proposes an optimization model to improve the robustness of an existing bus schedule. Robustness represents the ability of schedules to absorb deviations from the timetable and to prevent their propagation through the daily operations. The model developed proposes an optimal assignment of arrival times and distribution of slacks among Time Control Points of a bus line, in order to minimize delays and anticipations from schedule. This required the use of data collected through GPS devices installed in buses, informing the location of buses during their daily operation. The robustness of bus schedules was evaluated through the quantification of delays and anticipations of real observations of bus shifts by comparison with the timetable. The performance measures used to evaluate robustness are the average delay (or anticipation) of buses by comparison with the timetable, and the probability that a passenger that arrives on time according to the timetable will miss the bus or have to wait more than a specified threshold at a Time Control Point. We also compared the improvement of the schedule proposed by the optimization model with the original schedule. The results obtained in a real-world case study, corresponding to a bus line operating in Porto, showed that the model could return an improved schedule for all performance measures considered when compared with the original schedule.

Abstract
Usually the Industrial Automatic Guide Vehicles (AGVs) have two kind of lasers. One for navigation on the top and others for obstacle detection (security lasers). Recently, security lasers extended its output data with obstacle distance (contours) and reflectivity, that allows the development of a novel localization system based on a security laser. This paper addresses a localization system that avoids a dedicated laser scanner reducing the implementations cost and robot size. Also, performs a tracking system with precision and robustness that can operate AVGs in an industrial environment. Artificial beacons detection algorithm combined with a Kalman filter and outliers rejection method increase the robustness and precision of the developed system. A comparison between the presented approach and a commercial localization system for industry is presented. Finally, the proposed algorithms were tested in an industrial application under realistic working conditions.

Abstract
This paper describes a biased random-key genetic algorithm (BRKGA) for the minimization of the open stacks problem (MOSP). The MOSP arises in a production system scenario, and consists of determining a sequence of cutting patterns that minimize the maximum number of open stacks during the cutting process. The proposed approach combines a BRKGA and a local search procedure for generating the sequence of cutting patterns. A novel fitness function for evaluating the quality of the solutions is also developed. Computational tests are presented using available instances taken from the literature. The high quality of the solutions obtained validate the proposed approach.

Abstract
The manufacturer's pallet loading problem (MPLP) has been widely studied during the past 50 years. It consists of placing a maximum number of identical rectangular boxes onto a single rectangular pallet. In this paper, we have reviewed the methods that have been proposed for the solution of this problem. Furthermore, the various problem instances and data sets are analyzed that have been used in computational experiments for the evaluation of these methods. The most challenging and yet unsolved methods are identified. By doing so, areas of future research concerning the MPLP can be highlighted.