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A bi-objective decision model and method for the integrated optimization of bus line planning and lane reservation

JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第5期43卷 1298-1327页

作者： Wu, Peng Xu, Ling Che, Ada Chu, Feng Fuzhou Univ Sch Econ & Management Fuzhou 350108 Peoples R China Northwestern Polytech Univ Sch Management Xian 710072 Peoples R China Univ Paris Saclay Univ Evry F-91025 Evry France

The increasingly serious traffic congestionmakes the bus system more and more inefficient. It is recognized all over the world that designing an attractive bus transit network is primordial to alleviate traffic congestion and reduce pollution, but it is a big challenge from an economic and technical point of view. In the literature, dedicated bus lanes are generally set up to improve the efficiency of bus transit network without considering bus line planning. This study investigates a new bi-objective bus line planning and lane reservation integrated optimization problem that is a complex combinatorial optimization problem. The objective is to minimize the total travel time of passengers and the lane reservation negative impact, simultaneously. For the problem, a bi-objective integer linear programming model is first formulated and the problem complexity is proved to be NP-hard. Then, problem properties are explored to reduce search space for optimal solutions, and an iterative and fuzzy method based on e-constraint is proposed to yield the Pareto frontier and suggest a preferred solution for decision-makers. Experimental results on a case study and randomly generated instances demonstrate the effectiveness and efficiency of the proposed model and method.

关键词： Integrated bus line planning and lane reservation Bi-objective optimization Integer programming iterative algorithm

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iterative Coding Scheme Satisfying GC Balance and Run-Length Constraints for DNA Storage With Robustness to Error Propagation

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JOURNAL OF COMMUNICATIONS AND NETWORKS 2022年第3期24卷 283-291页

作者： Park, Seong-Joon Lee, Yongwoo No, Jong-Seon Seoul Natl Univ Dept Elect & Comp Engn INMC Seoul 08826 South Korea

In this paper, we propose a novel iterative encoding algorithm for DNA storage to satisfy both the GC balance and run-length constraints using a greedy algorithm. DNA strands with run-length more than three and the GC balance ratio far from 50% are known to be prone to errors. The proposed encoding algorithm stores data with high flexibility of run-length at most m and GC balance between 0.5 +/- alpha for arbitrary m and alpha. More importantly, we propose a novel mapping method to reduce the average bit error compared to the randomly generated mapping method. By using the proposed method, the average bit error caused by the one base error is 2.3455 bits, which is reduced by 20.5%, compared to the randomized mapping. Also, it is robust to error propagation since the input sequence is partitioned into small blocks during the mapping step. The proposed algorithm is implemented through iterative encoding, consisting of three main steps: randomization, M-ary mapping, and verification. It has an information density of 1.833 bits/nt in the case of m = 3 and alpha = 0.05.

关键词： Bioinformatics constrained coding DNA stor-age error propagation greedy algorithm iterative algorithm

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Network Energy-Efficiency Maximization in UAV-Enabled Air-Ground-Integrated Deployment

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IEEE INTERNET OF THINGS JOURNAL 2022年第15期9卷 13209-13222页

作者： Li, Yan Xu, Shaoyi Wu, Yunpu Li, Dongji Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Southeast Univ Natl Mobile Commun Res Lab Nanjing 210096 Peoples R China Southwest Jiaotong Univ Sch Elect Engn Chengdu 610031 Peoples R China

The unmanned aerial vehicle (UAV) technique combined with the cellular network is a promising and reliable technique to provide a low-cost, flexible, and easy-to-expandable network. In this article, we propose a UAV-assisted cooperative transmission network (UCTN), where UAVs and the base station (BS) transmit data jointly through the cooodination of the software-defined network (SDN). As the UAV has limited on-board energy, we aim to maximize the network energy efficiency (EE) by jointly optimizing the UAV-user association, UAV location, BS resource allocation, and the load allocation between the two systems. The formulated problem is a mixed-integer nonconvex optimization problem, which is intractable. To solve it, alternative optimization (AO) and Dinkelbach's method are adopted to recast the original problem into a tractable form. After that, the corresponding problem is divided into three subproblems and can be solved iteratively. An energy-constrained coalition game is proposed to solve the UAV-user association problem, and the UAV hovering point is carefully designed to balance the coalition serving time. Furthermore, the successive convex approximation (SCA) technique is adopted to optimize the BS transmit power and bandwidth allocation. Numerical experiments demonstrate that the proposed algorithm achieves significant performance gains over other benchmark schemes.

关键词： Autonomous aerial vehicles Internet of Things Games Throughput Resource management Bandwidth Optimization Coalition game iterative algorithm network energy efficiency (EE) resource optimization unmanned aerial vehicle (UAV)

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Deep Expectation-Maximization for Single-Pixel mage Reconstruction With Signal-Dependent Noise

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IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING 2022年 8卷 759-769页

作者： Mur, Antonio Lorente Peyrin, Francoise Ducros, Nicolas Univ Lyon Univ Claude Bernard Lyon 1 INSA Lyon UJM St EtienneCREATIS CNRS UMR 5220Inserm U1294 F-69621 Lyon France

Image reconstruction from a sequence of a few linear measurements that are corrupted by signal-dependent normally distributed noise is an inverse problem with many biomedical imaging applications, such as computerized tomography and optical microscopy. In this study, we focus on single-pixel imaging, where the set-up acquires a clown-sampled Hadamard transform of an image of the scene. Deep learning is a computationally efficient framework to solve inverse problems in imaging. Several neural-network architectures provide a link between deep and optimization-based image reconstruction methods. These deep-learning methods rely on a forward operator and lead to more interpretable networks. Here, we propose a novel network architecture obtained by unrolling an heuristic expectation-maximization algorithm. In particular, we compute the maximum a posteriori estimate of the unknown image given measurements corrupted by normally distributed signal-dependent noise. We show that the so-called expectation-maximization reconstruction network (EM-Net) applies to mixed Skellam-Gaussian noise models that are common in single-pixel imaging. We present reconstruction results from simulated and experimental single-pixel acquisitions. We show that EM-Net generalizes very well to noise levels not seen during training, despite having fewer learned parameters than alternative methods. The proposed EM-Net generally reconstructs images with fewer artifacts and higher signal-to-noise ratios, in particular in high-noise situations compared to other state of the art reconstruction algorithms that do not estimate the noise covariance.

关键词： Image reconstruction deep learning expectation-maximization iterative algorithm single-pixel imaging Skellam-Gaussian noise

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iterative METHODS FOR OBTAINING AN INFINITE FAMILY OF STRICT PSEUDO-CONTRACTIONS IN BANACH SPACES

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Acta Mathematica Scientia 2022年第5期42卷 1765-1778页

作者： Meng WEN Haiyang LI Changsong HU Jigen PENG School of Mathematics and Information Science Guangzhou UniversityGuangzhou 510006China School of Science Xi'an Polytechnic UniversityXi'an 710048China Department of Mathematics Hubei Normal UniversityHuangshi 435002China

In this paper,we introduce a general hybrid iterative method to find an infinite family of strict pseudo-contractions in a q-uniformly smooth and strictly convex Banach ***,we show that the sequence defined by the iterative method converges strongly to a common element of the set of fixed points,which is the unique solution of the variational inequality<(λφ−νF)z,jq(z−z)>≤0,for z∈⋂_(i=1)^(∞)Γ(S_(i)).The results introduced in our work extend to some corresponding theorems.

关键词： MKC iterative algorithm strict pseudo-contraction β-Lipschitzian d-strongly monotone Banach spaces

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Shortest Dubins Paths to Intercept a Target Moving on a Circle

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2022年第11期45卷 2107-2120页

作者： Manyam, Satyanarayana Gupta Casbeer, David W. Von Moll, Alexander Fuchs, Zachariah Infoscitex Corp 4027 Col Glenn HwySuite 210 Dayton OH 45431 USA Air Force Res Labs Control Ctr Excellence Wright Patterson AFB OH 45433 USA Univ Cincinnati Dept Elect Engn Cincinnati OH 45221 USA

We present a path planning problem for a pursuing unmanned aerial vehicle (UAV) to intercept a target traveling on a circle. The target is cooperative, and its position, heading, and speed are precisely known. The pursuing UAV has nonholonomic motion constraints, and therefore the path traveled must satisfy the minimum turn radius constraints. We consider the class of Dubins paths as candidate solutions, and analyze the characteristics of the six modes of Dubins paths where the final position is restricted to lie on the target circle with heading in the tangential direction of the circle. For each Dubins mode, we derive the feasibility limits, discontinuities, and local extrema. Using this analysis the intercepting paths are found by a systematic bisection search in the feasible regions of each of the Dubins modes. We prove that the algorithm finds the optimal (shortest length) intercepting path if it is a Dubins path. If the shortest intercepting path is not a Dubins path for any given instance, the algorithm finds a tight lower bound and an upper bound to the optimal solution.

关键词： Autonomous Unmanned Aerial Vehicles Path Planning Fixed Wing Aircraft Optimal Control iterative algorithm Aerial Refueling Ocean Currents Autopilot Python

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A tri-level approach for coordinated transmission and distribution system expansion planning considering deployment of energy hubs

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第19期16卷 3966-4006页

作者： Allahvirdizadeh, Yousef Shayanfar, Heidarali Moghaddam, Mohsen Parsa Iran Univ Sci & Technol Sch Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran *** Iran Tarbiat Modares Univ Sch Elect & Comp Engn Tehran Iran

This paper presents a tri-level stochastic coordinated transmission and distribution system expansion (CTDS) planning considering the deployment of energy hubs (EHs) across the distribution systems (DSs). The first level of the proposed optimization approach deals with transmission system expansion planning (TEP), while the second level develops distribution system expansion planning (DEP). Market clearing is done in the third level to update the locational marginal prices (LMPs) for different distribution system operators (DSOs). The EHs include photovoltaic cells (PVs), wind turbines (WTs), combined heating and power units (CHPs), boilers, and electrical and absorption chillers. The proposed tri-level approach is solved with an iterative algorithm based on the diagonalization approach and tested on the modified IEEE 30-bus transmission systems (TS) with several DSOs. Each DSO includes 18-bus electrical, heating, and cooling energy systems. The numerical analysis shows that the total cost of the transmission system operator (TSO) is not changed with implementing the uncoordinated approach. However, the total cost of the whole system is reduced by 6.54% with accommodation of the EHs in the uncoordinated approach. Moreover, the total cost of the TSO as well as the whole system are reduced by 41.11% and 16.96%, respectively, with the proposed (CTDS) planning.

关键词： photovoltaic cells transmission system expansion planning cooling energy systems optimisation distribution system operators absorption chillers energy hubs cogeneration wind turbines power transmission planning optimization approach boilers diagonalization approach modified IEEE 30-bus transmission systems power distribution planning distribution system expansion planning combined heating and power units iterative algorithm tri-level stochastic coordinated transmission transmission system operator

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The optimization of self-interference in wideband full-duplex phased array with joint transmit and receive beamforming

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JOURNAL OF COMBINATORIAL OPTIMIZATION 2022年第4期44卷 3136-3152页

作者： Wang, Xiaoxin Jiang, Zhipeng Yang, Wenguo Gao, Suixiang Univ Chinese Acad Sci Sch Math Sci Beijing Peoples R China

Full-duplex (FD) wireless and phased arrays are both promising techniques that can significantly improve data rates in future wireless networks. However, integrating FD with transmit (Tx) and receive (Rx) phased arrays is extremely challenging, due to the large number of self-interference (SI) channels. In this paper, a model is proposed to minimize the self-interference without large TxBF and RxBF gain losses through optimizing the TxBF and RxBF weights. As the model involves complex numbers and is non-convex, an iterative algorithm by solving series convex model is given to obtain an approximate solution. Meanwhile, in each step of the iterative algorithm, the sub model is translated into real number model. Then in order to balance the Tx and Rx gains, a penalty term is added into the sub model of each step of the iterative algorithm. Simulation results show that, the iterative algorithm is effective and can get good results, and the penalty term can both minimize the SI and make two gains balance.

关键词： Full-duplex wireless Phased array optimization iterative algorithm Non-convex optimization Complex number optimization

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On the Solution of Generalized Lyapunov Equations for a Class of Continuous Bilinear Time-Varying Systems

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AUTOMATION AND REMOTE CONTROL 2022年第5期83卷 677-691页

作者： Yadykin, I. B. Galyaev, I. A. Vershinin, Yu A. Russian Acad Sci Trapeznikov Inst Control Sci Moscow 117997 Russia

We have developed a method and algorithms for solving the generalized Lyapunov equation for a wide class of continuous time-varying bilinear systems based on the Gramian method and an iterative solution construction method proposed earlier for such equations. The approach consists in diagonalizing the original system, obtaining a separable spectral decomposition of the Gramian of the time-invariant linear part in terms of the combination spectrum of the dynamics matrix of the linear part, applying the spectral decomposition of the kernel matrix of the solution obtained at the previous step at each iteration step, and then aggregating the matrix entries. A spectral decomposition of the Gramians of controllability and observability of a time-varying bilinear system is obtained as the sum of sub-Gramian matrices corresponding to pair combinations of the eigenvalues of the dynamics matrix of the linear part. A new method and algorithm for entry-by-entry calculation of matrices for solving the generalized Lyapunov equation for bilinear systems has been developed. The fundamental novelty of the approach lies in the transfer of calculations from the solution matrix to the calculation of the sequence of its entries at each iteration step.

关键词： spectral decomposition generalized Lyapunov equation bilinear system time-varying system iterative algorithm Volterra matrix equation

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Finding minimal solutions to the system of addition-min fuzzy relational inequalities

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FUZZY OPTIMIZATION AND DECISION MAKING 2022年第4期21卷 581-603页

作者： Wu, Yan-Kuen Wen, Ching-Feng Hsu, Yuan-Teng Wang, Ming-Xian Zhejiang Yuexiu Univ Foreign Languages Sch Int Business Shaoxing Key Lab Intelligent Monitoring & Prevent Shaoxing Zhejiang Peoples R China Kaohsiung Med Univ Ctr Fundamental Sci Kaohsiung Taiwan Kaohsiung Med Univ Res Ctr Nonlinear Anal & Optimizat Kaohsiung Taiwan Kaohsiung Med Univ Hosp Dept Med Res Kaohsiung 80708 Taiwan Shanghai Business Sch Res Ctr Finance Shanghai Peoples R China Zhejiang Yuexiu Univ Foreign Languages Sch Int Business Shaoxing 312000 Zhejiang Peoples R China

In the literature, a BitTorrent-like peer-to-peer file-sharing system has been modelled as a system of addition-min fuzzy relational inequalities (FRIs). Finding all minimal solutions of such a system is considered a difficult task because the minimal solutions to addition-min FRIs are usually not unique and are often infinite in number. In this paper, we study the properties of the minimal solutions of such a system and propose an iterative algorithm to find the minimal solutions for any given solution (included the maximum solution). The proposed algorithm not only finds the minimal solutions efficiently, but also finds many minimal solutions in different iterative sequences of variables.

关键词： Minimal solution Addition-min composition Fuzzy relational inequality iterative algorithm

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