Abstract
Forest fires are a serious management challenge in many regions, complicating the appropriate allocation to suppression and prevention efforts. Using a System Dynamics (SD) model, this paper explores how interactions between physical and political systems in forest fire management impact the effectiveness of different allocations. A core issue is that apparently sound management can have unintended consequences. An instinctive management response to periods of worsening fire severity is to increase fire suppression capacity, an approach with immediate appeal as it directly treats the symptom of devastating fires and appeases the public. However, the SD analysis indicates that a policy emphasizing suppression can degrade the long-run effectiveness of forest fire management. By crowding out efforts to preventative fuel removal, it exacerbates fuel loads and leads to greater fires, which further balloon suppression budgets. The business management literature refers to this problem as the firefighting trap, wherein focus on fixing problems diverts attention from preventing them, and thus leads to inferior outcomes. The paper illustrates these phenomena through a case study of Portugal, showing that a balanced approach to suppression and prevention efforts can mitigate the self-reinforcing consequences of this trap, and better manage long-term fire damages. These insights can help policymakers and fire managers better appreciate the interconnected systems in which their authorities reside and the dynamics that may undermine seemingly rational management decisions.

Abstract

Abstract
This research provides mechanisms that facilitate to monitor and manage of Virtual Enterprise (VE) collaborative business processes in an efficient and effective way. First, it shows a self-contained process monitoring tool specification that contains the following main functionalities: events capturing from a workflow engine, business activity monitoring, process analytics and monitoring rules definition and evaluation. An interactive user interface layer in the form of dashboard is then highlighted within the scope of this research with the objective to monitor the VE operational processes. The dashboard will be the integration platform for a set of components that allow the establishment and operation of VE successfully. This platform enables a seamless integration of business processes and provides an endto-end ICT solution among the VE member organizations. The work presented in this paper is developed within the scope of the European Commission NMP priority of the Seventh RTD Framework Programme for the ADVENTURE (ADaptive Virtual ENterprise ManufacTURing Environment) project. © Springer International Publishing Switzerland 2013.

Abstract
This paper is addressed to the generalization of simple plant location problem where customer's preferences are taken into account. Some basic polyhedral studies and a new family of facet-defining inequalities are given. The effectiveness of the proposed approach is illustrated by the computational experience.

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
More than ever, the economic globalization is creating the need to increase business competitiveness. Lean manufacturing is a management philosophy oriented to the elimination of activities that do not create any type of value and are thus considered a waste. One of the main differences from other management philosophies is the shop-floor focus and the operators' involvement. Therefore, the training of all organization levels is crucial for the success of lean manufacturing. Universities should also participate actively in this process by developing students' lean management skills and promoting a better and faster integration of students into their future organizations. This paper proposes a single realistic manufacturing platform, involving production and assembly operations, to learn by playing many of the lean tools such as VSM, 5S, SMED, poke-yoke, line balance, TPM, Mizusumashi, plant layout, and JIT/kanban. This simulation game was built in tight cooperation with experienced lean companies under the international program "Lean Learning Academy,"1 and its main aim is to make bachelor and master courses in applied sciences more attractive by integrating classic lectures with a simulated production environment that could result in more motivated students and higher study yields. The simulation game results show that our approach is efficient in providing a realistic platform for the effective learning of lean principles, tools, and mindset, which can be easily included in course classes of less than two hours. © 2013 IEEE.