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Robust Route and Channel Selection in Cognitive Radio Networks

Robust Route and Channel Selection in Cognitive Radio Networ...

2012 IEEE 14th International Conference on Communication Technology(2012年第十四届通信技术国际会议(ICCT 2012))

作者： Jianzhao Zhang Yongxiang Liu Fuqiang Yao Long Cao PLA University of Science and Technology Nanjing China Nanjing Telecommunication Technology Institute Nanjing China

ISBN: (纸本)9781467321006

In this paper,the joint route and channel selection problem with reliability guarantee in cognitive radio network (CRN) is *** the interference to licensed spectrum owners needs to be strictly controlled,cognitive radio enabled users (CUs) should vacate the using channel immediately on detecting licensed users and the end to end performance may be seriously ***,the route constructed for a session may impose great negative influence on other current or latish sessions in the *** account for these challenges,the route reliability is formulated based on the link valid probability and a metric named interference impact is proposed to value the influence of a route to the adjacent *** the objective of minimizing the interference impact while providing throughput and reliability guarantee,the joint route and channel selection problem is formulated and shown to be in the form of integer nonlinear programming (INLP).Based on the analysis of the problem-specific feature,an on-demand route discovery algorithm is proposed to find reliable candidate routes,and a heuristic cross-layer optimization algorithm is proposed to choose the near-optimal *** results demonstrate that the proposed algorithm can guarantee the current route requirement while improving whole network throughput.

关键词： cognitive radio networks path stability interference impact integer nonlinear programming

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Robust Route and Channel Selection in Cognitive Radio Networks

Robust Route and Channel Selection in Cognitive Radio Networ...

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2012 IEEE 14th International Conference on Communication Technology

作者： Jianzhao Zhang Fuqiang Yao Yongxiang Liu Long Cao Nanjing PLA University of Science and Technology

关键词： cognitive radio networks path stability interference impact integer nonlinear programming

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Multiple-buyer multiple-vendor multi-product multi-constraint supply chain problem with stochastic demand and variable lead-time: A harmony search algorithm

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APPLIED MATHEMATICS AND COMPUTATION 2011年第22期217卷 9234-9253页

作者： Taleizadeh, Ata Allah Niaki, Seyed Taghi Akhavan Barzinpour, Farnaz Sharif Univ Technol Dept Ind Engn Tehran *** Iran Iran Univ Sci & Technol Dept Ind Engn Tehran Iran

In this paper, a multi-buyer multi-vendor supply chain problem is considered in which there are several products, each buyer has limited capacity to purchase products, and each vendor has warehouse limitation to store products. In this chain, the demand of each product is stochastic and follows a uniform distribution. The lead-time of receiving products from a vendor to a buyer is assumed to vary linearly with respect to the order quantity of the buyer and the production rate of the vendor. For each product, a fraction of the shortage is backordered and the rest are lost. The ordered product quantities are placed in multiple of pre-defined packets and there are service rate constraints for the buyers. The goal is to determine the reorder points, the safety stocks, and the numbers of shipments and packets in each shipment of the products such that the total cost of the supply chain is minimized. We show that the model of this problem is of an integer nonlinear programming type and in order to solve it a harmony search algorithm is employed. To validate the solution and to compare the performance of the proposed algorithm, a genetic algorithm is utilized as well. A numerical illustration and sensitivity analysis are given at the end to show the applicability of the proposed methodology in real-world supply chain problems. (C) 2011 Elsevier Inc. All rights reserved.

关键词： Supply chain management Multi-buyer Multi-vendor Partial back ordering Variable lead-time integer nonlinear programming Harmony search algorithm Genetic algorithsm

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A membership function approach to lot size re-order point inventory problems in fuzzy environments

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2011年第13期49卷 3855-3871页

作者： Chen, Shih-Pin Natl Chung Cheng Univ Dept Business Adm Chiayi 621 Taiwan

Inventory models play an important role in logistics and supply chain management for reducing cost and increasing customer satisfaction. This paper develops an approach to derive the fuzzy objective value and decision variables of the fuzzy lot size re-order point inventory problem with parameters being fuzzy numbers and the shortages are backordered with extra cost incurred. Different from the existing studies, the idea is based on Zadeh's extension principle. A pair of mixed integer nonlinear programs (MINLP) parameterised by the possibility level is formulated to calculate the lower and upper bounds of the minimal total cost per unit time at , through which the membership function of the minimal total cost per unit time is constructed. At the same time the membership functions of the optimal order quantity and the optimal re-order point are also provided. A numerical example studied by previous studies is solved successfully to demonstrate the validity of the proposed method. Compared with previous studies, the obtained results which precisely and completely conserve the fuzziness of the input information are more informative for finding the best inventory policy since they are expressed by membership functions rather than by crisp ones. Moreover, to provide representative crisp solutions for designing inventory systems, the Yager's ranking index method is adopted to defuzzify the obtained membership functions. The successful extension of inventory models to fuzzy environments permits inventory models to have wider applications in practice.

关键词： inventory fuzzy sets integer nonlinear programming membership function

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ON MAXIMAL S-FREE CONVEX SETS

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SIAM JOURNAL ON DISCRETE MATHEMATICS 2011年第1期25卷 379-393页

作者： Moran R, Diego A. Dey, Santanu S. Georgia Inst Technol H Milton Stewart Sch Ind & Syst Engn Atlanta GA 30332 USA

Let S subset of Z(n) satisfy the property that conv(S) boolean AND Z(n) - S. Then a convex set K is called an S-free convex set if int(K) boolean AND S = empty set A maximal S-free convex set is an S-free convex set that is not properly contained in any S-free convex set. We show that maximal S-free convex sets are polyhedra. This result generalizes a result of Basu et al. [SIAM J. Discrete Math., 24 (2010), pp. 158-168] for the case where S is the set of integer points in a rational polyhedron and a result of Lovasz [Mathematical programming: Recent Developments and Applications, M. Iri and K. Tanabe, eds., Kluwer, Dordrecht, 1989, pp. 177-210] and Basu et al. [Math. Oper. Res., 35 (2010), pp. 704-720] for the case where S is the set of integer points in some affine subspace of R-n.

关键词： integer nonlinear programming cutting planes maximal lattice-free convex sets

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引用; SIAM Journal on Discrete Mathematics 2011年第1期25卷 379-393页; 作者： Diego A. Morán R. Santanu S. Dey; Let S⊆Zn<span style="display: inline-block; width: 0px; height:; Let $S \subseteq Z^{n}$; 来源：评论; 学校读者我要写书评

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A particle swarm optimization approach for constraint joint single buyer-single vendor inventory problem with changeable lead time and (r,Q) policy in supply chain

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2010年第9-12期51卷 1209-1223页

作者： Taleizadeh, Ata Allah Niaki, Seyed Taghi Akhavan Shafii, Nima Meibodi, Ramak Ghavamizadeh Jabbarzadeh, Armin Sharif Univ Technol Dept Ind Engn Tehran *** Iran Raja Univ Dept Ind Management Qazvin Iran Univ Porto Fac Engn P-4100 Oporto Portugal Shahid Beheshti Univ Dept Elect & Comp Engn Tehran Iran

In this paper, the chance-constraint joint single vendor-single buyer inventory problem is considered in which the demand is stochastic and the lead time is assumed to vary linearly with respect to the lot size. The shortage in combination of back order and lost sale is considered and the demand follows a uniform distribution. The order should be placed in multiple of packets, the service rate limitation on each product is considered a chance constraint, and there is a limited budget for the buyer to purchase the products. The goal is to determine the re-order point and the order quantity of each product such that the chain total cost is minimized. The model of this problem is shown to be an integer nonlinear programming type and in order to solve it, a particle swarm optimization (PSO) approach is used. To assess the efficiency of the proposed algorithm, the model is solved using both genetic algorithm and simulated annealing approaches as well. The results of the comparisons by a numerical example, in which a sensitivity analysis on the model parameters is also performed, show that the proposed PSO algorithm performs better than the other two methods in terms of the total supply chain costs.

关键词： Multi-product inventory Stochastic demand Changeable lead time Supply chain integer nonlinear programming Particle swarm optimization

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integer programming SUBJECT TO MONOMIAL CONSTRAINTS

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SIAM JOURNAL ON OPTIMIZATION 2010年第6期20卷 3297-3311页

作者： Buchheim, Christoph Michaels, Dennis Weismantel, Robert Tech Univ Dortmund Fac Math D-44227 Dortmund Germany ETH Inst Operat Res CH-8092 Zurich Switzerland

We investigate integer programs containing constraints of the type Pi i is an element of I(x)i(alpha i) - b. Due to the number-theoretic nature of these constraints, standard methods based on linear algebra cannot be applied directly. Instead, we present a reformulation resulting in integer programs with linear constraints and polynomial objective functions, using prime decompositions of the right-hand sides b. Moreover, we show that minimizing a linear objective function with nonnegative coefficients over bivariate constraints is possible in polynomial time.

关键词： integer nonlinear programming monomial constraints

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A DSS to manage platelet production supply chain for regional blood centers

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DECISION SUPPORT SYSTEMS 2010年第1期50卷 32-42页

作者： Ghandforoush, Parviz Sen, Tarun K. Virginia Polytech Inst & State Univ Falls Church VA 22043 USA Virginia Tech RB Pamplin Coll Business Falls Church VA 22043 USA

This paper presents a prototype decision support system for platelet production and blood mobile scheduling for a regional blood center. Unlike whole blood cells, platelets have a very short shelf life, which requires matching demand and supply closely. This is achieved by an efficient supply chain DSS that is optimized for delivery of platelets from production centers to transfusion centers, typically hospitals. One of the critical elements of the DSS is an embedded non-convex integer optimization model that assists the regional blood center manager to schedule the shuttle transportation of whole blood from collection sites to the regional processing center. The proposed non-convex integer model is transformed to a linear 0-1 problem using a two-step conversion process. The transformed model is successfully solved and the optimal solution is reached for the test data. An application of the integrated DSS using data from a regional blood center is described. The results suggest that the proposed DSS better meets the daily demand by producing a superior production plan and mobile assignment schedule. (C) 2010 Elsevier B.V. All rights reserved.

关键词： Platelet supply management DSS integer nonlinear programming Blood bank DSS

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Optimal routing for minimizing the maximal link congestion

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Electronic Notes in Discrete Mathematics 2010年第C期36卷 1145-1152页

作者： Hijazi Hassan, H. Klopfenstein, Olivier Orange Labs 92130 Issy-les-Mx 38 rue du gl Leclerc France

A lot of attention has been devoted to flow routing in networks by the past. Usually, each commodity to be routed is characterized by a single deterministic traffic value. However, many real-life application contexts require to consider stochastic flows. This is the case, for instance, in telecommunication networks. The current paper revisits usual network routing and dimensioning models, in considering that traffic amounts to be routed are random variables. This leads naturally to probabilistic constraints. Some mathematical properties of the stochastic models introduced are described. A special focus is made on the relations between these stochastic models and usual deterministic approaches. © 2010 Elsevier B.V.

关键词： Congestion probability integer nonlinear programming Multicommodity flow Network optimization

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