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检索条件"主题词=mixed integer Linear programming"

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Multi-factory optimization enables kit reconfiguration in semiconductor manufacturing

Multi-factory optimization enables kit reconfiguration in se...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： M.T. Zhang S. Niu M. Mai Qi Li Intel Shanghai Operations Research and Solutions Shanghai China Operations Research & Solutions Intel Pudong Shangai Shanghai China Information Service and Technology Group Intel Corporation Shanghai China Flash Manufacturing Systems Intel Pudong Shangai Shanghai China

To enable the huge saving of the kit-breakdown, we developed MaxIt v1.2 to generate an optimal capacity plan at the kit component level for the mid-range build plan in multi-factory environment. We describe the MILP (mixed integer linear programming) model and system architecture of MaxIt v1.2. We also conduct detailed sensitivity analysis on parameter setting and objective prioritizing. With the implementation in the Intel Shanghai and Manila sites, we have significantly improved data integrity and enabled a -US/spl ges/ cost savings.

关键词： Semiconductor device manufacture Testing Capacity planning mixed integer linear programming Assembly Costs Business process re-engineering Production Operations research Manufacturing systems

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An algebraic decision diagram (ADD) based technique to find leakage histograms of combinational designs

An algebraic decision diagram (ADD) based technique to find ...

引用

International Symposium on Low Power Electronics and Design (ISLPED)

作者： K. Gulati N. Jayakumar S.P. Khatri Department of Electrical Engineering Texas A and M University College Station TX USA

In this paper, we present an algebraic decision diagram (ADD) based approach to determine and implicitly represent the leakage value for all input vectors of a combinational circuit. In its exact form, our technique can compute the leakage value of each input vector. To broaden the applicability of our technique, we present an approximate version of our algorithm as well. The approximation is done by limiting the total number of discriminant nodes in any ADD. Previous sleep vector computation techniques can find either the maximum or minimum sleep vector. Our technique computes the leakages for all vectors, storing them implicitly in an ADD structure. We experimentally demonstrate that these approximate techniques produce results which have reasonable errors. We also show that limiting the number of discriminants to a value between 12 and 16 is practical, allowing for good accuracy and lowered memory utilization.

关键词： Histograms Circuits Sleep Permission Very large scale integration Binary decision diagrams Leakage current Vectors mixed integer linear programming

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Predictive energy management strategies for hybrid vehicles

Predictive energy management strategies for hybrid vehicles

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Mutasim Salman Man-Feng Chang Jyh-Shin Chen Electrical and Controls Integration Lab. Of GM Research and Development Center

In this paper, predictive energy management strategies that utilize the previewed traffic pattern and terrain information are developed. A generalized predictive optimal control framework is used to find the conditions under which the predictive strategies, will give superior fuel economy to that of the instantaneous strategies. mixed integer linear programming methodology, with no assumptions on the control structure, is used to find the predictive energy management strategies. It is shown, by using theoretical work and simulation, that certain conditions are needed to make the predictive strategies, that utilize the previewed driving pattern and terrain information, give superior fuel economy to the instantaneous ones.

关键词： Energy management Fuel economy Vehicle driving Optimal control Vehicle dynamics Predictive models mixed integer linear programming Internal combustion engines Wheels Electric motors

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An enhanced exact procedure for the CMST problem

An enhanced exact procedure for the CMST problem

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International Conference on Information Technology and Applications, ICITA

作者： Jinpeng Huai Jun Han School of Computer Science Beihang University China

ISBN: (纸本)0769523161

This paper studies the capacitated minimum spanning tree problem, which is one of the most fundamental and significant problems in the optimal design of communication networks. A solution method using combined neighborhood search and branch and bound technique is introduced and its performance is presented. The advantage of the algorithm is shown while the process of searching for the optimal solution is illustrated. Computational experiences demonstrate that the proposed strategy significantly improves the efficiency of the previous arc-orientated branch and bound algorithm.

关键词： Costs Tree graphs Computer science Communication networks Graph theory mixed integer linear programming Vehicles Routing Computer errors Information technology

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Per-node power minimal multicast trees which maximize time-to-first-failure in energy constrained static wireless networks: a 2-step heuristic approach

Per-node power minimal multicast trees which maximize time-t...

引用

MILCOM, Military Communications Conference

作者： A.K. Das P. Arabshahi Department of Electrical Engineering University of Washington Seattle WA USA Jet Propulsion Laboratory Pasadena CA USA

We consider the problem of jointly maximizing the time-to-first-failure (TTFF), defined as the time till the first node in the network runs out of battery energy, and minimizing the total power in energy constrained static wireless networks. It is shown in A.K. Das et al. (2004) that simply optimizing the TTFF criterion may not provide the ideally optimum solution. Besides maximizing the TTFF, the ideally optimum solution guarantees that the lifetimes of all nodes are at least as high as in other trees which provide the same TTFF. A composite objective function involving the TTFF and the sum of the transmitter powers is therefore proposed in A.K. Das et al. (2004), along with a discussion of an optimal solution methodology using mixed integer linear programming. In this paper, we discuss a 2-step heuristic-procedure for the joint optimization problem. The first step is a greedy iterative algorithm which provides an optimal solution, but with respect to the TTFF criterion only. The second step is a tree-improvement technique which is used to refine the TTFF-optimal tree such that the total transmitter power is minimized, without affecting the optimal TTFF. Recent work has shown that the power consumed in the receiver circuitry can be almost comparable to the transmit power, especially in short-range networks. Our algorithms are therefore designed to take into account both the transmitter side and receiver side power expenditures. Simulation results are presented to validate the performance of the algorithm

关键词： Intelligent networks Wireless networks Transmitters Batteries Broadcasting Unicast Multicast algorithms Propulsion mixed integer linear programming Iterative algorithms

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A GRASP with Adaptive Memory for a Period Vehicle Routing Problem

A GRASP with Adaptive Memory for a Period Vehicle Routing Pr...

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International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce

作者： L.B. Goncalves L.S. Ochi S.L. Martins Departamento de Ciência da Computação Universidade Federal Fluminense Niteroi Rio de Janeiro Brazil

We present some proposals to approximately solve a period vehicle routing problem used to model the extraction of oil from a set of onshore oil wells in Brazil. This problem differs from the well-known period vehicle routing problem in several aspects. One major difference between them, responsible for increasing the complexity of the problem, is that, in the proposed problem, the number of visits required by a customer during the period is not previously determined. We developed some pure GRASP heuristics and some other heuristics that include the use of memory in GRASP. Experimental results illustrate the effectiveness of GRASP with adaptive memory over pure GRASP heuristics

关键词： Vehicles Routing Petroleum Costs Production Proposals Finishing mixed integer linear programming Mathematical model Performance analysis

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Optimization models for fixed channel assignment in wireless mesh networks with multiple radios

Optimization models for fixed channel assignment in wireless...

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IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks (SECON)

作者： A.K. Das H.M.K. Alazemi R. Vijayakumar S. Roy Department of Electrical Engineering and the Department of Aeronautics and Astronautics University of Washington Seattle WA USA Department of Computer Engineering Kuwait University Kuwait Department of Electrical Engineering University of Washington Seattle WA USA

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A Lagrangian heuristic for bid evaluation in e-procurement auctions

A Lagrangian heuristic for bid evaluation in e-procurement a...

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IEEE International Conference on Automation Science and Engineering (CASE)

作者： S. Kameshwaran Y. Narahari ISGMP Bat: A INRIA Lorraine Metz France Department of Computer Science and Automation Indian Institute of Science Bangalore India

e-Procurement is an Internet based business process for sourcing direct or indirect materials. This paper considers a procurement scenario of a buyer procuring large quantities of a single good. The suppliers submit nonconvex piecewise linear supply curves as their bids. Such bids enable the suppliers to effectively express their economies of scale and transportation constraints. The buyer imposes a business rule of limiting the winning suppliers within a preferred range. The bid evaluation problem faced by the buyer is to select the winning suppliers and their trading quantities, such that the cost of procurement is minimized while satisfying the supply, demand, and business constraints. The bid evaluation problem is NP-hard even for a simple special case. In this paper, the problem is formulated as a mixed integer linear programming problem and we propose a Lagrangian relaxation based heuristic to find a near optimal solution. The computational experiments performed on representative data sets show that the proposed heuristic produces a feasible solution with negligible optimality gap.

关键词： Lagrangian functions Procurement Piecewise linear techniques Business Internet Costs Automation Economies of scale Transportation mixed integer linear programming

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Minimizing Market Operation Costs Using A Security-Constrained Unit Commitment Approach

Minimizing Market Operation Costs Using A Security-Constrain...

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IEEE/PES Transmission and Distribution Conference and Exhibition: Asia and Pacific

作者： Qin Zhou R. Frowd A. Papalexopoulos D. Lamb E. Ledesma ECCO International Inc. UAE California ISO USA

This paper presents the methodology and the results of the must offer waiver process as applied in the California electricity market. The goal of this cost saving process is to minimize the market operation costs by deploying an optimal unit commitment approach. This procedure replaces the "first come, first served" must offer waiver process that is currently in place. It uses a security constrained unit commitment application to commit enough units to meet the reliability requirement and minimize the total start up and minimum load costs over the specified time period. A post must offer waiver procedure utilizing the security constrained unit commitment is also established to calculate and allocate the incremental costs associated with the local reliability requirement. The key components of the new must offer waiver procedure, the methodology and computer algorithm of security constrained unit commitment, and the methodology of the incremental cost calculation and allocation are addressed in this paper. The paper finally presents computational results based on actual data to illustrate the benefits of the new approach

关键词： Cost function ISO Electricity supply industry Data security Computer security mixed integer linear programming Real time systems Constraint optimization Reliability engineering Load forecasting

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Fast MPLS Network Optimisation using Machine Learning

Fast MPLS Network Optimisation using Machine Learning

引用

IEEE Region 10 International Conference TENCON

作者： Michael J. Dale Herman L. Ferra Robert A. Palmer Telstra Research Laboratories Melbourne VIC Australia

This paper presents the application of a machine learning technique (neural networks) to the problem of optimising the traffic flows (label switched path placement) within telecommunications networks using multi-protocol label switching (MPLS). It is shown here that the machine learning technique achieves very fast computation of accurate solutions to the problem of placing label switched paths in order to maximise the performance of the network. Results are presented which compare the accuracy of the neural network solutions with the optimal solutions produced by the standard mixed integer linear programming technique, and the time taken to produce the solutions. As well, network simulation results are presented which show the improvement in network performance, in terms of packet loss, that can be achieved when using such a technique.

关键词： Multiprotocol label switching Machine learning Telecommunication traffic Neural networks Telecommunication switching mixed integer linear programming Laboratories Australia Computer networks Telecommunication computing

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