Abstract

Abstract
This paper presents an approaches. that assists in producing highly compacted Nesting layouts with irregular pieces using free rotations. This approach consists in the selection and compaction of big pieces in a first phase, while in a second phase, places the remaining small pieces between the big pieces, compacting all of them. The effect of several parameters are analyzed, such as minimum length to be achieved in the first phase, attraction of the pieces to the edges of the container, attraction between each pair of pieces, among others. This approach can provide good compaction results, while improving computational cost in some cases, which cart allow to tackle real world problems more effectively mkt efficiently.

Abstract
In this paper, we address the irregular strip packing problem (or nesting problem) where irregular shapes have to be placed on strips representing a piece of material whose width is constant and length is virtually unlimited. We explore a constructive heuristic that relies on the use of graphical processing units to accelerate the computation of different geometrical operations. The heuristic relies on static selection processes, which assume that a sequence of pieces to be placed is defined a priori. Here, the emphasis is put on the analysis of the impact of these sequences on the global performance of the solution algorithm. Computational results on benchmark datasets are provided to support this analysis, and guide the selection of the most promising methods to generate these sequences.

Abstract
Entities that participate in the same supply chain or that can complement each other can benefit from reductions in their operational costs and increased operating efficiency when collaborating by sharing information and resources or engaging in joint planning. However, setting up successful collaborations is still an active research topic, particularly in the forest sector, due to the lack of a clearly defined road map for bringing collaboration into practice. This paper builds on a comprehensive literature review to propose a framework for developing inter-firm collaboration, particularly for agents of forest-based supply chains. The framework encompasses identification of collaboration opportunities with potential entities, design of the collaborative strategy, and tools for its implementation. The framework is used to discuss cases of collaboration found in the literature. The framework is also applied to developing a new collaborative process in the wood furniture industry.

Abstract
Wildfire management has been struggling in recent years with escalating devastation, expenditures, and complexity. Given the copious factors involved and the complexity of their interactions, uncertainty in the outcomes is a prominent feature of wildfire management strategies, at both policy and operational levels. Improvements in risk handling and in risk-based decision support tools have therefore a key role in addressing these challenges. In this paper, we review key systems created to support wildfire management decision-making at different levels and scales, and describe their evolution from an initial focus on landscape-level fire growth simulation and burn probability assessment, to the incorporation of exposure and economic loss potential (allowing the translation of ignition likelihood, fire environment terrain, fuels, and weather and suppression efficacy into potential fire effects), the integration with forest management and planning, and more recently, to developments in the assessment of values at risk, including real-time assessment. This evolution is linked to a progressive widening of the scope of usage of these systems, from an initial more limited application to risk assessment, to the subsequent inclusion of functionality enabling their Utilization in the context of risk management, and more recently, to their explicit casting in the broader societal context of risks and decisions, from a risk governance perspective. This joint evolution can be seen as the result of a simultaneous pull from methodological progresses in risk handling, and push from technological progress in wildfire management decision support tool, as well as more broadly in computational power. We identify the key benefits and challenges in the development and adoption of these systems, as well as future plausible research trends.

Abstract
Production planning and scheduling in the process industry in general and in the pulp and paper (P&P) sector in particular can be very challenging. Most practitioners, however, address those activities relying only on spreadsheets, which is time-consuming and sub-optimal. The literature has reported some decision support systems (DSSs) that are far from the state-of-the-art with regard to optimization models and methods, and several research works that do not address industrial issues. We contribute to reduce that gap by developing and describing a DSS that resulted from several iterations with a P&P company and from a thorough review of the literature on process systems engineering. The DSS incorporates relevant industrial features (which motivated the development of a specific model), exhibits important technical details (such as the connection to existing systems and user-friendly interfaces) and shows how optimization can be integrated in real world applications, enhanced by key pre- and post-optimization procedures.