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A detailed MILP model and an ad hoc decomposition algorithm for the operational optimization of gas transport networks

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COMPUTERS & CHEMICAL ENGINEERING 2025年 195卷

作者： Ghilardi, Lavinia Marina Paola Casella, Francesco Barbati, Daniele Palazzo, Roberto Martelli, Emanuele Politecn Milan Dept Energy Via Lambruschini 4 I-20154 Milan Italy Politecn Milan Dipartimento Elettron Informaz & Bioingn Via Ponzio 34 I-20133 Milan Italy Snam I-20097 San Donato Milanese MI Italy

Nowadays, the management of natural gas networks primarily relies on the expertise gained by operators over the years. Nevertheless, the need to reduce energy consumption and the progressive installation of electric compressors call for the adoption of systematic optimization tools. This study proposes a Mixed Integer Linear Programming (MILP) model for optimizing the operation of complex real-world gas networks to minimize the environmental impact of the compression work in presence of both gas-turbine driven and electric compressors. The operational problem includes the gas transport dynamic equations, detailed modeling of compressor stations and control valves, while handling complex branch and looped networks with possible reverse flow. To address large-scale problems, a graph reduction procedure and a novel bilevel decomposition algorithm are developed. This methodology, validated with real data, enables the optimization of the nationwide Italian network, comprising 51 compressors and 9727 km of pipes.

关键词： Operational optimization Gas transport Natural gas pipeline MILP decomposition algorithm

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A decomposition algorithm for distributionally robust chance-constrained programs with polyhedral ambiguity set

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OPTIMIZATION LETTERS 2025年 1-23页

作者： Pathy, Soumya Ranjan Rahimian, Hamed Clemson Univ Dept Ind Engn Clemson SC 29634 USA

In this paper, we study a distributionally robust optimization approach to chance-constrained stochastic programs to hedge against uncertainty in the distributions of the random parameters. We consider a general polyhedral ambiguity set under finite support. We develop a decomposition-based solution approach to solve the model and use mixing inequalities to develop custom feasibility cuts. In addition, probability cuts are also developed to handle the distributionally robust chance constraint. Finally, we present a numerical study to illustrate the effectiveness of the proposed decomposition-based algorithm and showcase the results for Wasserstein ambiguity set, total variation distance ambiguity set, and moment-based ambiguity set as special cases of the polyhedral ambiguity set.

关键词： Distributionally robust optimization Polyhedral ambiguity set Chance-constrained programming decomposition algorithm Cutting planes

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A decomposition algorithm FOR OPTIMAL STATIC LOAD BALANCING IN TREE HIERARCHY NETWORK CONFIGURATIONS

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 1994年第5期5卷 540-548页

作者： LI, J KAMEDA, H Institute of Information Sciences and Electronics University of Tsukuba Tsukuba Ibaraki Japan

We study the static load balancing problem in a distributed computer system with the tree hierarchy configuration. It is formulated as a nonlinear optimization problem. After studying the conditions that the solution to the optimization problem of the tree hierarchy network satisfies, we demonstrate that the special structure of the optimization problem leads to an interesting decomposition technique. A new effective decomposition algorithm to solve the optimization problem is presented. The proposed algorithm is compared with two other well known algorithms: the Flow Deviation (FD) algorithm and the Dafermos-Sparrow (D-S) algorithm. It is shown that the amounts of the storage required for the proposed algorithm and the FD algorithm are O(n) for load balancing of an n-node system. However, the amount of the storage required for the D-S algorithm is O(n log(n)). By using numerical experiments, we show that both the proposed algorithm and the D-S algorithm have much faster convergence in terms of central processing unit (CPU) time than the FD algorithm.

关键词： algorithm PERFORMANCE COMPUTER NETWORKS decomposition algorithm OPTIMAL LOAD BALANCING STAR NETWORK CONFIGURATIONS TREE HIERARCHY NETWORK CONFIGURATIONS

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decomposition algorithm for depth image of human health posture based on brain health

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NEURAL COMPUTING & APPLICATIONS 2020年第10期32卷 6327-6342页

作者： Luo, Bowen Sun, Ying Li, Gongfa Chen, Disi Ju, Zhaojie Wuhan Univ Sci & Technol Key Lab Met Equipment & Control Technol Minist Educ Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Hubei Key Lab Mech Transmiss & Mfg Engn Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Res Ctr Biol Manipulator & Intelligent Measuremen Wuhan 430081 Peoples R China Wuhan Univ Sci & Technol Inst Precis Mfg Wuhan 430081 Peoples R China Univ Portsmouth Sch Comp Portsmouth PO1 3HE Hants England

At this stage, brain health can be directly expressed in the human hand posture estimation. Therefore, model estimation of healthy human hand posture can also be used as a criterion for brain health. The recognition algorithm of healthy human hand gesture based on global feature extraction of depth map sequence is not enough to analyze the motion correlation of healthy human hand posture, which leads to the need to improve the accuracy of human body hand gesture description and the change of movement speed of robustness. After analyzing the characteristics of healthy human hand movement in detail, this paper proposes a hand posture decomposition algorithm based on depth map sequence. The goal is to find information that plays a key role in hand gesture recognition in the depth map sequence. The algorithm can remove redundant information and improve the robustness of the recognition algorithm.

关键词： Brain health decomposition algorithm Feature extraction Depth map sequence

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decomposition algorithm for performance evaluation of AGV systems

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PRODUCTION AND OPERATIONS MANAGEMENT 1999年第2期8卷 193-205页

作者： Nakano, M Ohno, K Toyota Cent Res & Dev Labs Inc Software Sci Lab Nagakute Aichi 4801192 Japan Nagoya Inst Technol Showa Ku Nagoya Aichi 466 Japan

This paper proposes a realistic queueing model of automated guided vehicle (acv) systems in just-in-time production systems. The model takes into consideration return paths, Erlang distributed service times, and pull-type dispatching rule, assuming finite buffer capacities. Since it has no product-form solution and natural decomposability due to complex nontree fork-cum-join architecture and dynamic dispatching rules, we propose a machine-based decomposition algorithm for the performance evaluation of the model. Each decomposed module consists of the processing machine and its dispatching station. Three how probabilities, derived from flow conservation analysis, relate the modules, which are updated iteratively until the parameters converge. The numerical results from a real-life AGV system application show that the algorithm is reasonably accurate.

关键词： queueing system decomposition algorithm AGV systems layout design

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decomposition algorithm for Power Delay Product Optimization in Wallace Multiplier

Decomposition Algorithm for Power Delay Product Optimization...

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International Conference on Control, Automation, Communication and Energy Conservation

作者： Ramanthan, P. Vanathi, P. T. Chaubey, Amaresh Raja, N. Senthil PSG Coll Technol Dept Elect & Commun Engn Coimbatore Tamil Nadu India

ISBN: (纸本)9788184244403

Low-power design of VLSI circuits has been identified as a critical technological need in recent years due to the high demand for portable consumer electronics products or even in line operated devices in order to avoid larger heat sinks. Adders and multipliers are the most important arithmetic units in a general microprocessor and the major source of power dissipation. Various architecture styles exist to implement these units, each having their own merits and demerits. The general objective of our work is to investigate the area and power-delay performances of 8 bit and 16 bit multiplier combining both Wallace tree[7] and decomposition[I] algorithm. This decomposition logic improves speed and reduces power consumption by reducing the spurious transitions on internal nodes. We have analyzed area and power-delay performances using different type of adder structures using different logic families CMOS[5], HYBRID[3] AND CPL[5]. With the help of these designs, it would be possible to design highly power efficient processor with less area, especially digital signal Processors.

关键词： Adders decomposition algorithm logic families Wallace tree algorithm

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Segregated Targeting for Multiple Resource Networks Using decomposition algorithm

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AICHE JOURNAL 2010年第5期56卷 1235-1248页

作者： Bandyopadhyay, Santanu Sahu, Gopal Chandra Foo, Dominic Chwan Yee Tan, Raymond R. Indian Inst Technol Dept Energy Sci & Engn Bombay 400076 Maharashtra India Univ Nottingham Dept Chem & Environm Engn Selangor 43500 Malaysia De La Salle Univ Dept Chem Engn Manila 1004 Philippines

A generalized decomposition technique is presented for determining optimal resource usage in segregated targeting problems with single quality index (e.g., concentration, temperature, etc.) through pinch analysis. The latter problems are concerned with determining minimal resource requirements of process networks characterized by the existence of multiple zones, each consisting of a set of demands and using a unique external resource. However, all the zones share a common set of internal sources. The decomposition algorithm allows the problem to he decomposed into a sequence of subproblems, each of which can in turn be solved using any established graphical or algebraic targeting methodology to determine the minimum requirement of respective resource. This article presents a rigorous mathematical proof of the decomposition algorithm, and then demonstrates its potential applications with case studies on carbon-constrained energy sector planning, interplant water integration, and emergy-based multisector fuel allocation. (C) 2009 American Institute of Chemical Engineers AIChE J, 56: 1235-1248, 2010

关键词： resource conservation process integration pinch analysis targeting multiple resources decomposition algorithm

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An SKU decomposition algorithm for the tactical planning in the FMCG industry

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COMPUTERS & CHEMICAL ENGINEERING 2014年 62卷 80-95页

作者： van Elzakker, M. A. H. Zondervan, E. Raikar, N. B. Hoogland, H. Grossmann, I. E. Eindhoven Univ Technol Dept Chem Engn & Chem NL-5600 MB Eindhoven Netherlands Unilever Res Labs Vlaardingen Netherlands Carnegie Mellon Univ Dept Chem Engn Pittsburgh PA 15213 USA

In this paper we propose an MILP model to address the optimization of the tactical planning for the Fast Moving Consumer Goods (FMCG) industry. This model is demonstrated for a case containing 10 Stock-Keeping Units (SKUs), but is intractable for realistically sized problems. Therefore, we propose a decomposition based on single-SKU submodels. To account for the interaction between SKUs, slack variables are introduced into the capacity constraints. In an iterative procedure the cost of violating the capacity is slowly increased, and eventually a feasible solution is obtained. Even for the relatively small 10-SKU case, the required CPU time could be reduced from 1144 s to 175 s using the algorithm. Moreover, the algorithm was used to optimize cases of up to 1000 SKUs, whereas the full model is intractable for cases of 25 or more SKUs. The solutions obtained with the algorithm are typically within a few percent of the global optimum. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Tactical planning Optimization MILP decomposition algorithm Fast Moving Consumer Goods Enterprise-Wide Optimizationa

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Sparse signal reconstruction using decomposition algorithm

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KNOWLEDGE-BASED SYSTEMS 2013年 54卷 172-179页

作者： Zhang, Li Zhou, Wei-Da Chen, Gui-Rong Lu, Ya-Ping Li, Fan-Zhang Soochow Univ Res Ctr Machine Learning & Data Anal Sch Comp Sci & Technol Suzhou 215006 Peoples R China Al Speech Ltd Suzhou 215123 Jiangsu Peoples R China Xidian Univ Inst Intelligent Informat Proc Xian 710071 Peoples R China

In compressed sensing, sparse signal reconstruction is a required stage. To find sparse solutions of reconstruction problems, many methods have been proposed. It is time-consuming for some methods when the regularization parameter takes a small value. This paper proposes a decomposition algorithm for sparse signal reconstruction, which is almost insensitive to the regularization parameter. In each iteration, a subproblem or a small quadratic programming problem is solved in our decomposition algorithm. If the extended solution in the current iteration satisfies optimality conditions, an optimal solution to the reconstruction problem is found. On the contrary, a new working set must be selected for constructing the next subproblem. The convergence of the decomposition algorithm is also shown in this paper. Experimental results show that the decomposition method is able to achieve a fast convergence when the regularization parameter takes small values. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Compressed sensing Sparse signal reconstruction Quadratic programming decomposition algorithm Quadratic programming

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An improved trilinear decomposition algorithm based on a Lagrange operator

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ANALYTICAL SCIENCES 2003年第7期19卷 1037-1043页

作者： Lu, JZ Wu, HL Jiang, JH Long, N Mo, CY Yu, RQ Hunan Univ Coll Chem & Chem Engn State Key Lab Chemo Biosensing & Chemometr Changsha 410082 Peoples R China

An improved trilinear decomposition algorithm based on a Lagrange operator (LO) is developed in this paper, which introduces a Lagrange operator and penalty terms in the loss function to improve the performance of the algorithm. Compared to the traditional parallel factor (PARAFAC) algorithm, the algorithm not only may converge much faster, but also overcome the sensibility to estimate the number of components. A set of simulated and measured excitation/emission fluorescence data were treated by both the proposed and traditional PARAFAC algorithm to compare their efficiencies. The analytical results obtained with real chemical system containing aspirin and its metabolic products show that the trilinear decomposition methodology is a promising tool to obtain spectral and composition information from mixtures without chemical separation.

关键词： .penalty loss function decomposition algorithm trilinear Lagrange Operator fluorescence data traditional PARAFAC algorithm

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