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A Genetic Algorithm Approach for Multi-criteria Project Selection for Analogy-Based Software Cost Estimation 1

1st International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Kumari, Sweta Pushkar, Shashank BIT Dept CSE Ranchi Bihar India

ISBN: (纸本)9788132222026;9788132222019

This paper presents genetic algorithms as multi-criteria project selection for improving the Analogy Based Estimation (ABE) process, which is suitable to reuse past project experience to create estimation of the new projects. An attempt has also been made to create a multi-criteria project selection problem with and without allowing for interactive effects between projects based on criteria which are determined by the decision makers. Two categories of projects are also presented for comparison purposes with other traditional optimization methods and the experimented results show the capability of the proposed Genetic Algorithm based method in multi-criteria project selection problem and it can be used as an efficient solution to the problem that will enhance the ABE process. Here, Mean Absolute Relative Error (MARE) is used to evaluate the performance of ABE process and it has been found that interactive effects between projects may change the results.

关键词： Software cost estimation Analogy based estimation Genetic algorithm Multi-criteria decision making nonlinear integer programming

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Energy-efficient Cooperative Sensing Scheduling for Heterogeneous Channel Access in Cognitive Radio

Energy-efficient Cooperative Sensing Scheduling for Heteroge...

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IEEE Conference on Computer Communications (INFOCOM)

作者： Sun, Xiangxia Chen, Li Tsang, Danny H. K. Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China

ISBN: (纸本)9781467310161

As a promising technology to implement Dynamic Spectrum Access (DSA), Cognitive Radio (CR) is envisioned to evolve to be Green. In this paper, the Cooperative Sensing Scheduling (CSS) problem for Cognitive Radio Network (CRN) is analyzed by taking both the performance and energy consumption of spectrum sensing into consideration. We model the CSS problem under a practical scenario where primary user (PU) channels are heterogeneous in terms of channel protection criteria, idling probabilities and channel capacities. With the objective to find an optimal and efficient secondary users (SUs) assignment scheme, we formulate the CSS problem into a nonlinear integer programming problem. The intricate two-dimensional trade-off among energy efficiency, sensing performance and spectrum opportunity exploration is presented and properly tackled. We explore the inherent property of this problem by adopting a two-step approach. In the first step, by fixing the number of SUs participating in sensing, the problem is converted to an M-concave problem and an efficient algorithm for optimal SU assignment is proposed. With this scheme, we then investigate the appropriate number of SUs participating in sensing in the second step. Based on these two steps, the final SU assignment scheme is proposed. The optimality of this assignment scheme is proved theoretically and verified numerically.

关键词： cognitive radio cooperative sensing scheduling nonlinear integer programming energy-efficient M-convex

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integer Conic Function Minimization Based on the Comparison Oracle 18th

Integer Conic Function Minimization Based on the Comparison ...

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18th International Conference on Mathematical Optimization Theory and Operations Research (MOTOR)

作者： Gribanov, Dmitriy V. Malyshev, Dmitriy S. Lobachevsky State Univ Nizhny Novgorod 23 Gagarina Ave Nizhnii Novgorod 603950 Russia Natl Res Univ Higher Sch Econ 25-12 Bolshaja Pecherskaja Ulitsa Nizhnii Novgorod 603155 Russia

ISBN: (纸本)9783030226299;9783030226282

Let f : R-n -> R be a conic function and x(0) is an element of R-n. In this note, we show that the shallow separation oracle for the set K = {x is an element of R-n : f (x) <= f (x(0))} can be polynomially reduced to the comparison oracle of the function f. Combining these results with known results of D. Dadush et al., we give an algorithm with (O (n))(n) log R calls to the comparison oracle for checking the non-emptiness of the set K boolean AND Z(n), where K is included to the Euclidean ball of a radius R. Additionally, we give a randomized algorithm with the expected oracle complexity (O (n))(n) log R for the problem to find an integral vector that minimizes values of f on an Euclidean ball of a radius R. It is known that the classes of convex, strictly quasiconvex functions, and quasiconvex polynomials are included into the class of conic functions. Since any system of conic functions can be represented by a single conic function, the last facts give us an opportunity to check the feasibility of any system of convex, strictly quasiconvex functions, and quasiconvex polynomials by an algorithm with (O(n))(n) log R calls to the comparison oracle of the functions. It is also possible to solve a constraint minimization problem with the considered classes of functions by a randomized algorithm with (O (n))(n) log R expected oracle calls.

关键词： nonlinear integer programming Conic function Convex function Quasiconvex function Comparison oracle Separation oracle Membership oracle Convex set Integral lattice

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Dynamic Resource Reservation via Broker Federation in Cloud Service: A Fine-grained Heuristic-Based Approach

Dynamic Resource Reservation via Broker Federation in Cloud ...

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IEEE Global Communications Conference (GLOBECOM)

作者： Liu, Kaiyang Peng, Jun Liu, Weirong Yao, Pingping Huang, Zhiwu Cent S Univ Sch Informat Sci & Engn Changsha 400075 Hunan Peoples R China

ISBN: (纸本)9781479935123

In cloud computing, Infrastructure-as-a-Service (IaaS) cloud providers can offer two types of purchasing plans for cloud users, including on-demand plan and reservation plan. Generally reservation price is cheaper than on-demand price, while reservation plan may cause highly underutilized capacity problem. How to joint optimize the service cost and the resource utilization for clouds is a critical issue. To address this issue, a novel steady broker federation is developed to coordinate service demands in this paper. And the optimal reservation problem can be formulated as a nonlinear integer programming model. Then a fine-grained heuristic algorithm is proposed to reduce its computational complexity and obtain quasi-optimal solutions. Numerical simulations driven by large-scale Parallel Workloads Archive demonstrate that the proposed approach can save considerable costs for cloud users and improves the resource utilization for IaaS cloud providers.

关键词： cloud computing nonlinear integer programming resource reservation virtualization

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Solving nonlinear integer programs with large-scale optimization software

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Annals of Operations Research 1986年第1-4期5卷 425-437页

作者： Mawengkang, H. Murtagh, B.A. University of New South Wales Sydney Australia

This paper describes recent experience in tackling large nonlinear integer programming problems using the MINOS large-scale optimization software. A technique is presented for extending the constrained search approach used in MINOS to exploring integer-feasible solutions once a continuous optimal solution is obtained. Computational experience with this approach is described for two classes of problems: quadratic assignment problems and pipeline network design problems. © 1986 J.C. Baltzer A.G., Scientific Publishing Company.

关键词： large-scale optimization nonlinear integer programming optimization applications optimization software

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CONVEX EXTENSION OF DISCRETE-CONVEX FUNCTIONS AND APPLICATIONS IN OPTIMAL DESIGN OF COMPLICATED LOGISTIC, MANUFACTURING AND PROCESSING ENVIRONMENTS

CONVEX EXTENSION OF DISCRETE-CONVEX FUNCTIONS AND APPLICATIO...

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13th International Conference on Harbor, Maritime and Multimodal Logistics Modeling and Simulation (HMS)

作者： Riismaa, Tiit Tallinn Univ Technol Inst Cybernet Akad Tee 21 EE-12618 Tallinn Estonia

ISBN: (纸本)9788890372469

A method of description and optimal design of the structure of complicated multi-level processing systems is presented. The set of feasible structures for such class of systems is defined. The representation of this set is constructed in terms of the graph theory. For the reduced statement two types of variable parameters are defined: for the level size and for the relations of adjacent levels. The choice of variable parameters guarantees the discrete-convexity of objective function. A class of iteration methods for solving the discrete-convex programming problem is derived. The method based on the extension of discrete-convex function to the convex function and on extension of discrete-convex programming problem to the convex programming problem. On each step of the iteration the calculation of the value of objective function is required only on some vertices of unit cube. The considered approach is illustrated by an academic example of modelling and optimal design of the multi-level manufacturing system.

关键词： discrete manufacturing and processing environment optimal multi-level partitioning discrete-convex function nonlinear integer programming

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Influence of Short-Turning Route on Transport Capacity of Urban Rail Transit 4

Influence of Short-Turning Route on Transport Capacity of Ur...

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4th IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Gong, Chao-Qi Xu, Qi Beijing Jiaotong Univ MOE Key Lab Urban Transportat Complex Syst Theory Beijing Peoples R China

ISBN: (纸本)9781728114101

Influence of short-turning route on transport capacity of urban rail transit systems have been intensively studied. Yet, even successful modelling approach such as those considering fixed facilities still do not fully take into account the real-life passenger mobility. Passenger demand and its spatial-temporal patterns derived from smart card and data obtained from the automated fare collection system facilitate transport capacity assessment scientifically. This paper utilize trip data obtained from an urban rail transit line to characterize passenger demand. A nonlinear integer programming model is proposed, with maximal transport capacity as the objective. A numerical case is adopted to verify the validity of the model with Genetic Algorithm, and the sensitivity of passenger demand pattern is analyzed in terms of service level and limited amount of rolling stocks, comparing to a single full-length route. The results indicate that short-turning route helps to increase the transport capacity under a certain condition and give some insights on urban rail transit operation and management.

关键词： short-turning route transport capacity nonlinear integer programming passenger demand data

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A New Model of Generalized Assignment Problem and Its Method 2

A New Model of Generalized Assignment Problem and Its Method

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2nd IEEE Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)

作者： Xiong, Sheng Yang, Yuqi Huai, Kaizhan PLA Univ Sci & Technol Inst Commun Engn Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467389792

The traditional assignment problem assumes that the number of persons is equal to that of the tasks, beyond that, one person is allowed to undertake only one task and one task must be accomplished by one person. However, in practical situation, a real task usually calls for more than one person, in some cases, those persons are required to work at the same time. If so, the classical assignment model will not be able to describe the problem accurately. In view of this situation, a new generalized assignment model based on nonlinear integer programming is presented in this paper. The new model gives a unified description of the generalized assignment problems in which one or more persons are required to work at the same time to complete a single task. As a result, it makes up for the deficiency of the existing generalized assignment model. Moreover, for the case of binary quadratic programming, a new branch and bound method is also proposed. The numerical results indicate that the generalized assignment model and method proposed are valid.

关键词： Generalized assignment problem nonlinear integer programming Quadratic integer programming Branch and bound method

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Soft-Decision Based Distributed Detection Over Correlated Sensing Channels 51

Soft-Decision Based Distributed Detection Over Correlated Se...

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51st Annual Conference on Information Systems and Sciences (CISS)

作者： Kasasbeh, Hadi Cao, Lei Viswanathan, Ramanarayanan Univ Mississippi Dept Elect Engn University MS 38677 USA

ISBN: (纸本)9781509047802

This paper proposes a new framework that performs spectrum sensing in soft decision based distributed detection systems while considering correlated sensors' readings. The main contribution is formulating the problem into a nonlinear integer programming problem for which the genetic algorithm is further applied to find a suboptimal solution. This framework is able to handle both soft and hard decisions while assuming correlation for any number of sensors, and hence largely extends the scenarios being considered in previous works. The results show that our scheme outperforms previous schemes and approaches the centralized detection scheme performance in terms of probability of error.

关键词： Soft decision distributed detection correlated readings nonlinear integer programming

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Amplitude-optimized Koopman-linear flow estimator for wind turbine wake dynamics: Approximation, prediction and reconstruction

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ENERGY 2023年第PartE期263卷

作者： Chen, Zhenyu Lin, Zhongwei Ren, Xin Chen, Kaixuan Zhang, Guangming Xie, Zhen Wang, Chuanxi She, Chao China Huaneng Grp Co Ltd Beijing 100031 Peoples R China North China Elect Power Univ Sch Control & Comp Engn State Key Lab Alternate Elect Power Syst Renewable Beijing 102206 Peoples R China Huaneng Clean Energy Res Inst Beijing 102209 Peoples R China Huairou Lab Beijing 101400 Peoples R China China Power Engn Consulting Grp Cent Southern China Elect Power Design Inst Co Ltd Wuhan 430064 Peoples R China

The low-order modeling of wind turbine dynamic wake is a challenging problem, which requires approximating high-dimensional, nonlinear dynamic systems with a limited number of states and linear structures. The Koopman-linear flow estimator is regarded as a promoting method in this area to approximate the dynamic wake field from a few physical-measured states. This paper presents optimization methods for the Koopman-linear flow estimator to improve its generalization applicability and modeling accuracy in specific applications. Firstly, the flow estimator's wake field prediction process is organized using Koopman modes and amplitudes;both are identified initially. Then, a optimization method is proposed to optimize the Koopman amplitudes for a given application scenario, which maintains a consistent form for uncontrolled and controlled systems based on the error-source analysis. After this, a sequential particle swarm optimization algorithm is adopted, which improves the computationally-intensive problem during sensor configuration optimization. The proposed algorithm quickly solves a feasible and optimized sensor configuration plan instead of the unavailable global -optimal one. The verification results show two conclusions: On the one hand, the nonlinearity during the yaw-induced wake deflection process is evident, which poses a significant challenge to the linear low-order approximation of the dynamic wake field. On the other hand, the proposed optimization methods highly improve the dynamic wake modeling accuracy under free-wake and yaw-controlled scenarios. Sparse sampling is necessary for dynamic wake behavior study in industrial. This paper solves the incomplete measurements and wake deflection nonlinearity problem caused by sparse sampling and promotes the generalization applicability for specific applications.

关键词： Flow reconstruction Wake Dynamic mode decomposition Koopman mode Optimal Koopman amplitudes nonlinear integer programming

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