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Metaheuristics for solving the biobjective single-path multicommodity communication flow problem

INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2019年第2期26卷 589-614页

作者： Masri, Hela Krichen, Saoussen Guitouni, Adel Univ Tunis Tunis Business Sch Tunis Tunisia Univ Tunis Inst Super Gest Tunis Tunis Tunisia Univ Victoria Peter B Gustavson Sch Business Victoria BC Canada

Single-path multicommodity flow problem (SMCFP) is a well-known combinatorial optimization problem, in which the flow of each commodity can be transmitted using only one path linking its destination to an appropriate origin within the addressed network. In this paper, we study the SMCFP in a multiobjective context by considering the simultaneous optimization of paths' delay and average reliability. The network is modeled as a finite set of nodes that can communicate using preestablished connections where each connection is characterized by a capacity, a lead time, and a reliability. A node can be an information producer or/and information consumer. The contention problem is solved by assigning a path and a dedicated bandwidth to each flow. The problem is formulated as a biobjective nonlinear optimization problem. This biobjective problem has not been considered in the literature. We design three alternative procedures for approximating the Pareto front. We proposed an MGA based on NSGA-II, a multiobjective variable neighborhood search and a new distance-based hybrid metaheuristic. The hybridization integrates a local search into the framework of genetic algorithm to effectively drive the search toward a better approximating of the Pareto front. The propounded algorithms' efficiencies are experimentally investigated on a test bed of instances applied to a planar and a grid network. A comparative study is conducted based on different multiobjective performance indicators.

关键词： multiple-objective programming metaheuristics network flows nonlinear programming

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Efficient linear network model for TEP based on piecewise McCormick relaxation

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第23期13卷 5404-5412页

作者： Goodarzi, Shahin Gitizadeh, Mohsen Abbasi, Ali Reza Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Fasa Univ Fac Engn Dept Elect Fasa Iran

This study presents a novel scheme for transmission expansion planning (TEP) based on piecewise McCormick relaxation. The model presented considers investment and operation cost and identifies the transmission lines to be built. Since the AC power flow equations are inherently non-convex and non-linear, the resulting TEP model will be a highly complex optimisation problem, in which the optimal global solution is not guaranteed to be found by the existing techniques. This study aims to transform the non-linear model of the power network into a novel linear one. The model proposed is much more precise compared with the DC approach, while the global solution is guaranteed to be found by the off-the-shelf solvers. This accurate transformation from a non-convex and non-linear AC-TEP formulation into a linear-TEP model enables the planner to get more insight into the power flow of the power system. The TEP problem is formulated as a mixed-integer linear programming problem and is solved using the efficient commercial solvers. The results of the case studies show the tractability and exactness of the proposed model as well as its superiority over the state-of-the-art schemes.

关键词： power transmission planning linear programming nonlinear programming integer programming investment concave programming load flow power transmission economics power transmission lines nonconvex AC-TEP formulation nonlinear AC-TEP formulation off-the-shelf solvers power network nonlinear model optimal global solution complex optimisation problem AC power flow equations transmission lines operation cost investment transmission expansion planning piecewise McCormick relaxation efficient linear network model efficient commercial solvers mixed-integer linear programming problem TEP problem power system linear-TEP model

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Database Building and Interpolation for an Online Safe Flight Envelope Prediction System

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2019年第5期42卷 1166-1174页

作者： Zhang, Y. de Visser, C. C. Chu, Q. P. Delft Univ Technol Fac Aerosp Engn Control & Simulat Sect Kluyverweg 1 NL-2629 HS Delft Netherlands

A study addresses offline construction of the database. The main focus and contribution of this study are database building and interpolation for the Database-Driven Safe Flight Envelope Prediction System (DEFEND) system. More importantly, through complexity analysis, the database approach is shown to be feasible for onboard real-time implementation within the aircraft control laws. Reachability analysis as the method to compute safe flight envelopes, as the theory provides a set-valued insight into safety and control design of dynamic systems. One advantage of this method is that all possible trajectories can be computed from all available control strategies and initial states, which naturally meets the safety guarantees. The computed results are called reachable sets, which are defined as a set of states that reach a certain target set within a certain time horizon and current control authority. Two sets of envelopes are computed using the level-set method toolbox. One is the pitching envelope, referred to the motion in the longitudinal plane with horizontal tail damage. The other is the rolling envelope, referred to the motion in the lateral plane with wing tip loss.

关键词： Mean Aerodynamic Chord Control Surfaces Aerodynamic Characteristics True Airspeed Earth Reference Frame Optimal Control nonlinear programming Cessna Citation II Horizontal Stabilizers Structural Damage

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Training Structured Neural Networks Through Manifold Identification and Variance Reduction

arXiv

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arXiv 2021年

作者： Huang, Zih-Syuan Lee, Ching-Pei Academia Sinica

This paper proposes an algorithm, RMDA, for training neural networks (NNs) with a regularization term for promoting desired structures. RMDA does not incur computation additional to proximal SGD with momentum, and achieves variance reduction without requiring the objective function to be of the finite-sum form. Through the tool of manifold identification from nonlinear optimization, we prove that after a finite number of iterations, all iterates of RMDA possess a desired structure identical to that induced by the regularizer at the stationary point of asymptotic convergence, even in the presence of engineering tricks like data augmentation that complicate the training process. Experiments on training NNs with structured sparsity confirm that variance reduction is necessary for such an identification, and show that RMDA thus significantly outperforms existing methods for this task. For unstructured sparsity, RMDA also outperforms a state-of-the-art pruning method, validating the benefits of training structured NNs through regularization. Implementation of RMDA is available at https://***/zihsyuan1214/rmda. © 2021, CC BY.

关键词： nonlinear programming

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Joint bandwidth and power allocation for multiple services in TV white space

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IET COMMUNICATIONS 2019年第5期13卷 569-577页

作者： Tian, Zhong Wang, Jun Wang, Jintao Song, Jian Tsinghua Univ Beijing Natl Res Ctr Informat Sci & Technol BNRis Beijing Peoples R China

As the bandwidth resource in TV white space (TVWS) is permitted to be used for the secondary users, multiple secondary networks coexisting in the same geographical area can provide multiple services without interfering with the primary service, such as the TV broadcasting. To satisfy the minimum rate requirements and maximise the sum rate of the multiple services, the problem of resource allocation can be modelled as a mixed integer non-linear programming (MINLP). According to this model, the joint bandwidth and power allocation (JBPA) method is proposed to solve the resource allocation for multiple services. The JBPA method is sub-optimal, which can approximate the performance of the optimal two-step exhaustive search (TSES) method very well, especially when the number of services is larger than the number of idle channels. Compared with TSES, the JBPA method decreases the complexity from exponential level to polynomial level. Besides, compared with one channel occupied by single service, the JBPA can serve more services and provide stable performance when the number of services varies dynamically. Compared with the algorithm random bandwidth allocation, the JBPA can approximate the optimal performance provided by TSES better with the time complexity of the same order.

关键词： bandwidth allocation algorithm random bandwidth allocation TV white space radio spectrum management two-step exhaustive search method resource allocation multiple services JBPA method nonlinear programming multiple secondary networks single service integer programming computational complexity bandwidth resource power allocation primary service joint bandwidth/power allocation

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A derivative-free affine scaling trust region methods based on probabilistic models with new nonmonotone line search technique for linear inequality constrained minimization without strict complementarity

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2019年第4期96卷 663-691页

作者： Wang, Peng Zhu, Detong Hainan Normal Univ Math & Stat Coll Haikou 570203 Hainan Peoples R China Shanghai Normal Univ Math & Stat Coll Shanghai Peoples R China

In this paper, a derivative-free trust region methods based on probabilistic models with new nonmonotone line search technique is considered for nonlinear programming with linear inequality constraints. The proposed algorithm is designed to build probabilistic polynomial interpolation models for the objective function. We build the affine scaling trust region methods which use probabilistic or random models within a classical trust region framework. The new backtracking linear search technique guarantee the descent of the objective function, and new iterative points are in the feasible region. In order to overcome the strict complementarity hypothesis, under some reasonable conditions which are weaker than strong second order sufficient condition, we give the new and more simple identification function to structure the affine matrix. The global and local fast convergence of the algorithm are shown and the results of numerical experiments are reported to show the effectiveness of the proposed algorithm.

关键词： Derivative-free optimization affine matrix nonlinear programming probabilistic models global convergence nonmonotone linear search

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Multi-objective and multi-period distribution expansion planning considering reliability, distributed generation and self-healing

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IET GENERATION TRANSMISSION & DISTRIBUTION 2019年第2期13卷 219-228页

作者： Pinto, Rafael S. Unsihuay-Vila, Clodomiro Fernandes, Thelma S. P. Univ Fed Parana UFPR Elect Engn Dept Curitiba Parana Brazil

This study describes a methodology to solve the multi-period distribution expansion planning problem considering reliability, distributed generation (DG), capacitor and switch placement in the context of smart grids. The developed computational model is formulated as a mixed integer nonlinear optimisation problem and solved through the combination of meta-heuristics, stochastic simulation methods (Monte-Carlo simulation), and application of optimal power flow. The main objectives of this optimisation problem are defining the best choice to install power system components and determining the installation period and size of components to minimise investment cost while maximising system reliability. The proposed method was implemented in a modified version of the IEEE-RBTS bus 2 and in a 90-bus test system. The obtained results show a reduction of >20% of the operating cost and >70% of the average interruption time. In addition, it was performed scenarios not including DG, self-healing, and reliability analysis, individually. The analyses show the impact in the results by including a new variable in the expansion planning, increasing up to 40% in the fitness function value. Furthermore, it is presented with a discussion of the impact of the method to estimate the reliability indexes on the optimisation process.

关键词： power distribution planning power generation planning distributed power generation power distribution reliability power generation economics power generation reliability power distribution economics Monte Carlo methods load shedding minimisation integer programming nonlinear programming smart power grids load flow multiobjective distribution expansion planning multiperiod distribution expansion planning distributed generation self-healing smart grids computational model mixed integer nonlinear optimisation problem stochastic simulation methods Monte-Carlo simulation optimal power flow loading shedding power system components installation period investment cost minimisation system reliability maximisation IEEE-RBTS bus 2test system IEEE-RBTS 90-bus test system reliability analysis fitness function value reliability index estimation

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Muntz-Legendre spectral collocation method for solving delay fractional optimal control problems

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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2019年 351卷 344-363页

作者： Hosseinpour, Soleiman Nazemi, Alireza Tohidi, Emran Shahrood Univ Technol Fac Math Sci POB ***-316 Shahrood Iran Kosar Univ Bojnord Dept Math POB *** Bojnord Iran

In this paper, a numerical method is applied for solving delay fractional optimal control problems (DFOCPs). The fractional derivative is described in the Caputo sense. Since the fractional derivative of Muntz polynomials can be expressed in terms of the same polynomials, those polynomials can accurately represent properties of fractional calculus. In some situations such as in the frequency response based analysis of control systems containing a time-delay, it is necessary to substitute exponential function with an approximation in the form of a rational function. The most common approximation is the Pade approximation. At the first step, using Pade approximation, the delay problem is transformed to a non delay problem. Next, using the operational matrix of the fractional derivative of Mintz polynomials and pseudospectral method, fractional optimal control problem (FOCP) is reduced to a nonlinear programming problem. Some numerical examples are given to illustrate the effectiveness of the proposed scheme. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Delay fractional optimal control problem Operational matrix Muntz polynomials Pseudospectral method Pade approximation nonlinear programming

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A single server retrial fuzzy queue with priority and unequal service rates

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2019年第1期37卷 811-820页

作者： Kalpana, B. Anusheela, N. Bharathiar Univ Res & Dev Ctr Coimbatore 641046 Tamil Nadu India Govt Arts Coll Ooty Dept Math Ooty Tamil Nadu India

This paper develops a latest mathematical model to derive the membership function of fuzzy retrial queue with single server queue model FM1, FM2/FM1, FM2/1 with priority and unequal service rates. The vital aim of this paper is to combine the parametric non linear programming technique and Yager's ranking method. Using alpha - cut approach and Zadeh's principle the fuzzy queues are changed into crisp queues in this paper. The membership function of the system characteristics is derived for different values of a. The numerical example is given to check the validity of the model.

关键词： Fuzzy sets membership function nonlinear programming priority retrial queue

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Transition motion planning for multi-limbed vertical climbing robots using complementarity constraints

arXiv

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arXiv 2021年

作者： Zhang, Jingwen Lin, Xuan Hong, Dennis W. Department of Mechanical and Aerospace Engineering University of California Los AngelesCA90095 United States

— In order to achieve autonomous vertical wall climbing, the transition phase from the ground to the wall requires extra consideration inevitably. This paper focuses on the contact sequence planner to transition between flat terrain and vertical surfaces for multi-limbed climbing robots. To overcome the transition phase, it requires planning both multicontact and contact wrenches simultaneously which makes it difficult. Instead of using a predetermined contact sequence, we consider various motions on different environment setups via modeling contact constraints and limb switchability as complementarity conditions. Two safety factors for toe sliding and motor over-torque are the main tuning parameters for different contact sequences. By solving as a nonlinear program (NLP), we can generate several feasible sequences of foot placements and contact forces to avoid failure cases. We verified feasibility with demonstrations on the hardware SiLVIA, a six-legged robot capable of vertically climbing between two walls by bracing itself in-between using only friction. © 2021, CC0.

关键词： nonlinear programming

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