Abstract
This work discusses on the simulation of a ship crew reaction in controlling damage in a single watertight compartment, taking into account ship's hydrostatics and equipment limitation. Three different simulators were built which exchange data using High Level Architecture concepts, implemented with an open source RTI called CERTI and a MatlabHLA Tollbox.

Abstract
This paper is concerned with the use of simulation as a decision support tool in maintenance systems, specifically in MFS (Maintenance Float Systems). For this purpose and due to its high complexity, in this paper the authors explore and present a way to develop a flexible MFS model, for any number of machines in the workstation, spare machines and maintenance crews, using Arena simulation language. Also in this paper, some of the most common performance measures are identified, calculated and analysed. Nevertheless this paper would concentrate on the two most important performance measures in maintenance systems: system availability and maintenance total cost. As far as these two indicators are concerned, it was then quite clear that they assumed different behaviour patterns, especially when using extreme values for periodic overhauls rates. In this respect, system availability proved to be a more sensitive parameter.

Abstract

Abstract
The adoption of mobile payment systems is known to face multiple concerns regarding security, usability and value proposition. In this work, we start from the assumption that initial acceptance will always be weak because of the lack of an established usage frame. Instead, we focus on understanding how we can leverage upon the real contact with the technology to create a solid path for gradual acceptance through the development of new practices and the increasing perception of value. In this study, we report on our findings with a real-world prototype of a NFC-based payment system. We identify a set of design lessons that may help to improve the initial phases of NFC-based payment deployments and provide a path for the adoption that focuses on positive initial user experiences and early adoption scenarios. © Springer International Publishing 2013.

Abstract
In this paper, a new efficient algorithm named combined local search heuristics which comprise two local search heuristics, Variable Neighborhood Descent (VND) and Random Neighbor Selection (RNS), is designed and proposed to solve two-dimensional guillotine bin packing problems. The objective of these problems is to pack smaller pieces of rectangular items into large rectangular bins without overlapping such that the total number of used bins is minimized. A constructive heuristic (CH) is conceived to construct a solution by packing items into bins with the use of a defined item packing sequence. VND and RNS, which consist of three deterministic neighborhood structures and three random neighbor selection operators, respectively, are used for improving a solution given by the CH. Benchmark instances were adopted to verify the effectiveness of the designed algorithm via computational experiments. Computational results show that, in terms of the quality of solutions, the proposed approach is better than other heuristics and metaheuristics. In terms of computational times, the proposed algorithm cannot be compared to other algorithms and the computational experiments cannot offer enough evidence of showing any good running-time behavior of the proposed algorithm because of different models of computers used. However, from a practical point of view, easy implementation and reasonable and affordable computational times confirm the usefulness of the proposed algorithm.

Abstract
Since the automotive industry is one of the most competitive markets, key players should be capable of evolving their management strategy from a reactive to proactive approach. This way, it is critical for this type of companies to explore a new performance management approach where an effective interaction between the strategic and operational layers should be achieved. In line with this vision, a framework is presented that helps stakeholders make decisions based on the ability to anticipate future performance behaviours. Using leading indicators as reference, the key idea is to structure and model the existing knowledge within a mathematical tool, in order to project the manufacturing system's behaviour into the future. In order to show the reliability and importance of this framework, this paper presents a research performed at an automotive plant. The aim is to model the factors affecting energy consumption and thus estimate the future behaviour in terms of sustainability issues.