Industrial sector growth in developing countries requires the provision of alternatives to guarantee sustainable development. Improving energy efficiency and fuel switching are two measures to reduce CO2 emissions in ...
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Industrial sector growth in developing countries requires the provision of alternatives to guarantee sustainable development. Improving energy efficiency and fuel switching are two measures to reduce CO2 emissions in the industrial sector, with natural gas and low-carbon electricity as the most feasible options in the short term. In this work, a linear programming optimization model has been developed to study the potential of energy efficiency improvement and fuel substitution for CO2 emissions reduction, at national level in the non-ferrous metals industry. The energy resource/end-use device allocation problem in secondary metal production and semi-fabrication has been modeled. Using this model, the particular case of Colombia, where low-carbon electricity is available, has been studied. By improving energy efficiency, energy use and CO2 emissions can be reduced significantly, 73% and 72%, respectively, at negative costs. Further CO2 emissions reductions, up to 88%, are possible with fuel switching to low-carbon electricity, increasing the costs for the energy system;however, cost reductions caused by energy efficiency improvement outweigh cost increments of fuel switching. Benefits achieved with fuel substitution using low-carbon electricity can be lost if hydropower is not available;in such a case, efficient natural gas-fired end-use devices are preferable. (C) 2012 Elsevier Ltd. All rights reserved.
Network discovery is a fundamental task in different scenarios of IEEE 802.15.4-based wireless personal area networks. Scenario examples are body sensor networks requiring health- and wellness-related patient monitori...
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Network discovery is a fundamental task in different scenarios of IEEE 802.15.4-based wireless personal area networks. Scenario examples are body sensor networks requiring health- and wellness-related patient monitoring or situations requiring opportunistic message propagation. In this paper, we investigate optimized discovery of IEEE 802.15.4 static and mobile networks operating in multiple frequency bands and with different beacon intervals. We present a linearprogramming model that allows finding two optimized strategies, named OPT and SWOPT, to deal with the asynchronous and multichannel discovery problem. We also propose a simplified discovery solution, named SUBOPT, featuring a low-complexity algorithm requiring less memory usage. A cross validation between analytical, simulation, and experimental evaluation methods is performed. Finally, a more detailed simulation-based evaluation is presented, when considering varying sets of parameters (i.e., number of channels, network density, beacon intervals, etc.) and using static and mobile scenarios. The performance studies confirm improvements achieved by our solutions in terms of first, average, and last discovery time as well as discovery ratio, when compared to IEEE 802.15.4 standard approach and the SWEEP approach known from the literature.
In this paper we present a novel distributed Inter-Cell Interference Coordination (ICIC) scheme for interference-limited heterogeneous cellular networks (HetNet). We reformulate our problem in such a way that it can b...
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In this paper we present a novel distributed Inter-Cell Interference Coordination (ICIC) scheme for interference-limited heterogeneous cellular networks (HetNet). We reformulate our problem in such a way that it can be decomposed into a number of small sub-problems, which can be solved independently through an iterative subgradient method. The proposed dual decomposition method can also address problems with binary-valued variables. The proposed algorithm is compared with some reference schemes in terms of cell-edge and total cell throughput.
This article investigates agricultural productivity growth over several decades, emphasizing to a great extent the agricultural economic development condition for the nine agricultural divisions of the United States, ...
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This article investigates agricultural productivity growth over several decades, emphasizing to a great extent the agricultural economic development condition for the nine agricultural divisions of the United States, and China's 27 provinces in terms of Malmquist productivity growth index. The paper sets up a technique to make use of two-stage linearprogramming method, based on sequential production technology, to estimate the most fitted and reliable distance functions in relevant agricultural sectors, and thus to compute the Malmquist productivity indexes. Especially, it proposes to decompose the productivity growth index into two major components, technical progress and efficiency improvement, and their sub-components, to study the sources of growth in productivity.
Circuit design often runs in parallel with the development of the manufacturing process that will be used to fabricate it. However, as the manufacturing process matures, its models may undergo substantial changes as t...
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ISBN:
(纸本)9781424489350
Circuit design often runs in parallel with the development of the manufacturing process that will be used to fabricate it. However, as the manufacturing process matures, its models may undergo substantial changes as the design nears production. These changes may cause the design itself to fail its specifications, and in these cases it is necessary to perform an Engineering Change Order (ECO) to correct these problems. We present a new framework to perform incremental gate sizing for process changes late in the design cycle. This includes a method to measure and estimate ECO cost, transform these costs into a linear programming optimization problem, and solve the problem to find the ECO. This method performs well, compared to a leading commercial physical design tool, reducing ECO costs by 18% to 99% in changed area, and 1% to 96% in number of pins with unnecessary pin timing changes.
This article investigates agricultural productivity growth over several decades,emphasizing to a great extent the agricultural economic development condition for the nine agricultural divisions of the United States,an...
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This article investigates agricultural productivity growth over several decades,emphasizing to a great extent the agricultural economic development condition for the nine agricultural divisions of the United States,and China's 27 provinces in terms of Malmquist productivity growth *** paper sets up a technique to make use of two-stage linearprogramming method,based on sequential production technology,to estimate the most fitted and reliable distance functions in relevant agricultural sectors,and thus to compute the Malmquist productivity ***,it proposes to decompose the productivity growth index into two major components,technical progress and efficiency improvement,and their sub-components,to study the sources of growth in productivity.
We consider a partial ordered set (POSET) of assembling operations, with known execution durations, that must be accomplished. The assembling operations can be executed on an acyclic network with an identical set of r...
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We consider a partial ordered set (POSET) of assembling operations, with known execution durations, that must be accomplished. The assembling operations can be executed on an acyclic network with an identical set of robots on each conveyer (arc). The number of depots (nodes) is a known integer. Between each pair of depots we can locate only one conveyer. We seek an arrangement of the network and a plan that divides the task operations among the conveyers, minimizing the overall task completion time. We use linear programming optimization, subject to reasonably general rules for distributing the operation-fragments among the conveyers. (c) 2006 Elsevier B.V. All rights reserved.
Extracorporeal bioartificial liver devices (BAL) are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with suffi...
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Extracorporeal bioartificial liver devices (BAL) are perhaps among the most promising technologies for the treatment of liver failure, but significant technical challenges remain in order to develop systems with sufficient processing capacity and of manageable size. One key limitation is that during BAL operation, when the device is exposed to plasma from the patient, hepatocytes are prone to accumulate intracellular lipids and exhibit poor liver-specific functions. Based on hepatic intermediary metabolism, we have utilized mathematical programming techniques to optimize the biochemical environment of hepatocyte cultures towards the desired effect of increased albumin and urea synthesis. To investigate the feasible range of optimal hepatic function, we have obtained a Pareto optimal set of solutions corresponding to liver-specific functions of urea and albumin secretion in the metabolic framework using multiobjective optimization. The importance of amino acids in the supplementation and the criticality of the metabolic pathways have been investigated using logic-based programming techniques. Since the metabolite measurements are bound to be patient specific, and hence subject to variability, uncertainty has to be integrated with system analysis to improve the prediction of hepatic function. We have used the concept of two stage stochastic programming to obtain robust solutions by considering extracellular variability. The proposed analysis represents a new systematic approach to analyze behavior of hepatocyte cultures and optimize different operating parameters for an extracorporeal device based on real-time conditions. (c) 2005 Wiley Periodicals, Inc.
This study is concerned with the problem of constructing an optimal military deployment plan for sealift assets during a period of conflict. The deployment problem is formulated as a set-partitioning optimization prob...
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This study is concerned with the problem of constructing an optimal military deployment plan for sealift assets during a period of conflict. The deployment problem is formulated as a set-partitioning optimization problem with a minimax objective. An algorithm for solving this problem is presented and it is based on solving a sequence of related, but simpler, linearprogramming problems by the column generation technique. The results of the model are ship schedules to meet the cargo requirements of the deployment plan in a minimum amount of time. Various implementation strategies are discussed as well as the occurrence of integer solutions. In addition, computational experiments for several small to medium size examples are presented.
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