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Just-in-Time Scheduling : Models and Algorithms for Computer and Manufacturing Systems

As the field of Supply Chain Management has matured, maintaining the precise flow of goods to maintain schedules (hence, minimizing inventories) on a just-in-time basis still remains as a major challenge. This problem or challenge has resulted in a fair amount of quantitative research in the area, producing an array of models and algorithms to help ensure the precise flow of components and final products into inventories to meet just-in-time requirements.The scheduling models and algorithms presented and illustrated in the book will be done so in the context of extensive use of computer systems in a "real time context.

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Ambiguities in Decision-oriented Life Cycle Inventories: The Role of Mental Models and Values

Shows for the first time how mental models and values influence this attribution in the life cycle inventory step of LCA. One of the key findings is that the different management rules for a sustainable use of materials must be taken into account for the attribution of material and energy flows to a product. Otherwise, improvement options recommended by an LCA might turn out to even worsen the environmental situation if reassessed from a meta-perspective. As a consequence of this book, the claim of unambiguitiy (‘objectivity’) of the life cycle inventory must be abandoned. A group-model building process for LCA is developed that allows one to grasp the decision makers' mental models and values in the inventory analysis on a case- and situation-specific basis. Only by this, LCA results will become relevant in a decision-making process. Two case studies on the modelling of recycling and other end-of-life options of aluminium windows and beech wood railway sleepers in LCA complement the methodological part.

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Level Crossing Methods in Stochastic Models

Since its inception in 1974, the level crossing approach for analyzing a large class of stochastic models has become increasingly popular among researchers. This volume traces the evolution of level crossing theory for obtaining probability distributions of state variables and demonstrates solution methods in a variety of stochastic models including: queues, inventories, dams, renewal models, counter models, pharmacokinetics, and the natural sciences. Results for both steady-state and transient distributions are given, and numerous examples help the reader apply the method to solve problems faster, more easily, and more intuitively.

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