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IEEE International Conference on Systems, Man, and Cybernetics

作者： Yen-Liang Pan Mu-Der Jeng Sheng-Luen Chung Yu-Xin Guo Department of Avionic Engineering Air Force Academy Kaohsiung 820 Taiwan R.O.C. Department of Electrical Engineering National Taiwan Ocean University Department of Electrical Engineering National Taiwan University of Science and Technology

ISBN: (纸本)9781479906505

Deadlock prevention policies are used to solve the deadlock problems of flexible manufacturing systems. Theory of regions is the efficient method for obtaining optimal (i.e. maximally permissive) controllers. All legal and live maximal behavior can be preserved by using marking/transition-separation instances (MTSIs) or event-state-separation-problem (ESSP) methods. However, solving all sets of inequalities is very time-consuming. Moreover, the number of linear programming problems (LPPs) of all legal markings is also exponential with net size. In this paper, a novel methodology is proposed to reduce the number of MTSIs/ESSPs and LPPs. Preciously, one new concept called critical ones of crucial marking/transition-separation instances (COCMTSI) is developed and used in this deadlock prevention policy that allows designers to employ few MTSIs to deal with deadlocks.

关键词： Petri nets linear programming problems deadlock prevention theory of regions flexible manufacturing system Flexible manufacturing systems Petri nets linear programming Policies Manufacturing systems

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Hybrid VNS-LP algorithm for online optimal coordination of directional overcurrent relays

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IET GENERATION TRANSMISSION & DISTRIBUTION 2020年第23期14卷 5447-5455页

作者： Damchi, Yaser Dolatabadi, Mohammad Shahrood Univ Technol Fac Elect Engn & Robot Shahrood Iran Vali E Asr Univ Rafsanjan Dept Math Rafsanjan Iran

Optimal coordination of directional overcurrent relays (DOCRs) in interconnected power systems is a highly constrained, non-convex and non-linear optimisation problem. In this study, use of a series of linear programming (LP) problems in a variable neighbourhood search (VNS) framework is proposed, in which pickup current settings can be considered either as continuous or discrete variables. Therefore, the proposed hybrid algorithm (VNS-LP) is suitable for coordination problem-solving in a network with different types of DOCRs. Furthermore, two versions of the VNS algorithm are proposed, the first of which is very easy to implement, while, the other is somewhat more sophisticated, and at the same time much faster and possibly suitable for online coordination in smart grids applications. One advantage of the second algorithm is that it relies only on elementary arithmetic and requires low RAM, which makes it implementable in any low-level programming environment. This, in turn, can increase the interoperability, which is of crucial importance when automating tasks. The efficiency of the proposed algorithm was investigated in several test systems. Numerical results indicate that the two proposed approaches outperform the previous methods. Moreover, the coordination problem is solved in a reasonably short time using a faster approach.

关键词： smart power grids power system interconnection optimisation overcurrent protection relay protection search problems power system protection online optimal coordination directional overcurrent relays DOCR interconnected power systems nonconvex optimisation problem nonlinear optimisation problem linear programming problems variable neighbourhood search framework pickup current settings continuous variables discrete variables coordination problem-solving VNS algorithm online coordination smart grids applications low-level programming environment hybrid VNS-LP algorithm VNS framework elementary arithmetic RAM

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Positive filtering for positive 2D fuzzy systems under l1 performance

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IET CONTROL THEORY AND APPLICATIONS 2019年第7期13卷 1024-1030页

作者： Wang, Li Qun Chen, Xiaoming Shen, Jun Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing 210016 Jiangsu Peoples R China

In this study, the problem of positive filtering is investigated for positive two-dimensional (2D) Roesser T-S fuzzy systems under $\ell _{1}$l1-induced performance. Error-bounding positive filters are constructed to estimate the output of positive 2D T-S fuzzy systems. Firstly, a novel characterisation for asymptotic stability of the filtering error system with $\ell _{1}$l1-induced performance is derived. Then, based on that characterisation, sufficient conditions are derived to design the required filters expressed by linear programming problems. Finally, the theoretical results are illustrated through a numerical example.

关键词： fuzzy systems linear programming filtering theory asymptotic stability positive filtering positive 2D fuzzy systems two-dimensional Roesser T-S fuzzy systems error-bounding positive filters positive 2D T-S fuzzy systems filtering error system 1 performance linear programming problems asymptotic stability

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Implementation of interior-point methods for LP based on Krylov subspace iterative solvers with inner-iteration preconditioning

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2019年第1期74卷 143-176页

作者： Cui, Yiran Morikuni, Keiichi Tsuchiya, Takashi Hayami, Ken UCL Dept Comp Sci Gower St London WC1E 6BT England Univ Tsukuba Div Informat Engn 1-1-1 Tennodai Tsukuba Ibaraki 3050006 Japan Natl Grad Inst Policy Studies Minato Ku 7-22-1 Roppongi Tokyo 1068677 Japan Natl Inst Informat Chiyoda Ku 2-1-2 Hitotsubashi Tokyo 1018430 Japan Grad Univ Adv Studies SOKENDAI Chiyoda Ku 2-1-2 Hitotsubashi Tokyo 1018430 Japan

We apply novel inner-iteration preconditioned Krylov subspace methods to the interior-point algorithm for linear programming (LP). Inner-iteration preconditioners recently proposed by Morikuni and Hayami enable us to overcome the severe ill-conditioning of linear equations solved in the final phase of interior-point iterations. The Krylov subspace methods do not suffer from rank-deficiency and therefore no preprocessing is necessary even if rows of the constraint matrix are not linearly independent. By means of these methods, a new interior-point recurrence is proposed in order to omit one matrix-vector product at each step. Extensive numerical experiments are conducted over diverse instances of 140 LP problems including the Netlib, QAPLIB, Mittelmann and Atomizer Basis Pursuit collections. The largest problem has 434,580 unknowns. It turns out that our implementation is more robust than the standard public domain solvers SeDuMi (Self-Dual Minimization), SDPT3 (Semidefinite programming Toh-Todd-Tutuncu) and the LSMR iterative solver in PDCO (Primal-Dual Barrier Method for Convex Objectives) without increasing CPU time. The proposed interior-point method based on iterative solvers succeeds in solving a fairly large number of LP instances from benchmark libraries under the standard stopping criteria. The work also presents a fairly extensive benchmark test for several renowned solvers including direct and iterative solvers.

关键词： linear programming problems Interior-point methods Inner-iteration preconditioning Krylov subspace methods

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Two Stage Indian Food Grain Supply Chain Network Transportation-Allocation Model

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IFAC-PapersOnLine 2016年第12期49卷 1767-1772页

作者： Mogale, D.G. Kumar, Sri Krishna Kumar Tiwari, Manoj Department of Industrial and Systems Engineering Indian Institute of Technology Kharagpur KharagpurWest Bengal721 302 India

This paper investigates the food grain supply chain, transportation allocation problem of Indian Public Distribution System (PDS). The different activities of Indian food grain supply chain are procurements, storage, movement, transportation and distribution. We have developed a mixed integer nonlinear programming model (MINLP) to minimize the transportation, inventory and operational cost of shipping food grains from the cluster of procurement centers of producing states to the consuming state warehouses. A recently developed chemical reaction optimization (CRO) algorithm is used for testing the model which gives the superior computational performance compared to other metaheuristics. © 2016

关键词： Food storage Chemical reactions Integer programming Nonlinear programming Supply chains Allocation problems Chemical reaction optimizations Computational performance Distribution systems Food grain Mixed integer non linear programming problems Mixed integer nonlinear programming models Supply chain network

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Effective Method for Wind and Solar Power Grid Systems Based on Recurrent Neural Networks

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JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS 2014年第6期18卷 1034-1043页

作者： Kimura, Keisuke Kimura, Takayuki Hiraguri, Takefumi Jin'no, Kenya Nippon Inst Technol 4-1-1 Gakuendai Minami Saitama Saitama 3458501 Japan

In this paper, the control method based on recurrent neural networks is proposed for optimizing large-scale wind and solar power generation systems. Recently, an optimal control method based on recurrent neural networks was proposed for wind and solar power generation systems. In this method, optimization problems are regarded as linear programming problems, which are solved by recurrent neural networks. Results suggest that this control method based on recurrent neural networks could be implemented in real-world systems. However, only small power generation systems were used to evaluate this control method in previous studies. Then, the method for power generation systems is evaluated by more realistic conditions. The results of our numerical experiments show that this control method delivers high performance with large-scale power generation systems. Furthermore, if the power generation systems has specific topologies, almost 20% of the supplying capacity is improved.

关键词： complex networks linear programming problems recurrent neural networks renewable energy systems

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Feasibility of piecewise-constant control sequences for timed continuous Petri nets

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AUTOMATICA 2013年第12期49卷 3654-3660页

作者： Leclercq, Edouard Lefebvre, Dimitri Univ Le Havre GREAH F-76600 Le Havre France

In this study, the determination of control actions for timed continuous Petri nets is investigated by the characterisation of attractive regions in marking space. In particular, attraction in finite time, which is important for practical issues, is considered. Based on the characterisation of attractive regions, the domain of admissible piecewise constant control actions is computed, and sufficient conditions to verify the feasibility of the control objectives are proposed. As a consequence, an iterative procedure is presented to compute piecewise constant control actions that correspond to local minimum time control for timed continuous Petri nets. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Petri nets Timed continuous Petri nets Control design linear programming problems

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Matrix correction of a dual pair of improper linear programming problems

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Computational Mathematics and Mathematical Physics 2007年第4期47卷 564-578页

作者： Erokhin, V.I. Borisoglebsk State Pedagogical University Borisoglebsk 397160 ul. Narodnaya 43 Russian Federation

A matrix is sought that solves a given dual pair of systems of linear algebraic equations. Necessary and sufficient conditions for the existence of solutions to this problem are obtained, and the form of the solutions is found. The form of the solution with the minimal Euclidean norm is indicated. Conditions for this solution to be a rank one matrix are examined. On the basis of these results, an analysis is performed for the following two problems: modifying the coefficient matrix for a dual pair of linear programs (which can be improper) to ensure the existence of given solutions for these programs, and modifying the coefficient matrix for a dual pair of improper linear programs to minimize its Euclidean norm. Necessary and sufficient conditions for the solvability of the first problem are given, and the form of its solutions is described. For the second problem, a method for the reduction to a nonlinear constrained minimization problem is indicated, necessary conditions for the existence of solutions are found, and the form of solutions is described. Numerical results are presented. © Nauka/Interperiodica 2007.

关键词： linear programming problems Methods for solving systems of linear algebraic equations Modifying the coefficient matrix

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Effective Parameter Estimation for S-system Models using LPMs and Evolutionary Algorithms

Effective Parameter Estimation for S-system Models using LPM...

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2010 IEEE World Congress on Computational Intelligence

作者： Kimura, Shuhei Amano, Yusuke Matsumura, Koki Okada-Hatakeyama, Mariko Tottori Univ Grad Sch Engn 4-101 Koyama Minami Tottori 6808552 Japan RIKEN Res Ctr Allergy & Immunol Yokohama Kanagawa 2300045 Japan

ISBN: (纸本)9781424481262

An S-system model is considered as an ideal model for describing genetic networks. As one of effective techniques for inferring S-system models of genetic networks, the problem decomposition strategy has been proposed. This strategy defines the inference of a genetic network consisting of N genes as N subproblems, each of which is a 2(N + 1)-dimensional function optimization problem. When we try to infer large-scale genetic networks consisting of many genes, however, it is not always easy for function optimization algorithms to solve 2(N + 1)-dimensional problems. In this study, we thus propose a new technique that transforms the 2(N + 1)-dimensional S-system parameter estimation problems into (N + 2)-dimensional problems. The proposed technique reduces the search dimensions of the problems by solving linear programming problems. The transformed problems are then optimized using evolutionary algorithms. Finally, through numerical experiments on an artificial genetic network inference problem, we show that the proposed dimension reduction approach is more than 3 times faster than the problem decomposition approach.

关键词： LPM S-system model artificial genetic network inference problem decomposition strategy dimension reduction approach dimensional function optimization problem evolutionary algorithm genetic algorithms genetic network genetics linear programming linear programming problems parameter estimation parameter estimation

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A Hierarchical Matrix Inversion Algorithm for Vectorless Power Grid Verification

A Hierarchical Matrix Inversion Algorithm for Vectorless Pow...

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IEEE and ACM International Conference on Computer-Aided Design

作者： Xiong, Xuanxing Wang, Jia IIT Dept Elect & Comp Engn Chicago IL 60616 USA

ISBN: (纸本)9781424481927

Vectorless power grid verification is a powerful technique to validate the robustness of the on-chip power distribution network for all possible current waveforms. Formulated and solved as linear programming problems, vectorless power grid verification demands intensive computational power due to the large number of nodes in modern power grids. Previous work showed that the performance bottleneck of this powerful technique is within the sub-problem of power grid analysis, which essentially computes the inverse of the sparse but large power grid matrix. In this paper, we propose a hierarchical matrix inversion algorithm to compute the rows of the inverse efficiently by exploiting the structure of the power grid. The proposed algorithm is integrated with a previous dual algorithm addressing an orthogonal sub-problem for vectorless power grid verification. Results show that the proposed hierarchical algorithm accelerates the matrix inversion significantly, and thus makes the overall vectorless power grid verification efficient.

关键词： current waveforms dual algorithm hierarchical matrix inversion algorithm integrated circuit design linear programming linear programming problems on-chip power distribution network orthogonal sub-problem power grid analysis power grid matrix power grids power supply circuits vectorless power grid verification

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