Minimum Constraint Research Articles

Multi-UAV Aided Millimeter-Wave Networks: Positioning, Clustering, and Beamforming

In this paper, we propose to employ multiple unmanned aerial vehicle (UAV) base stations to serve ground users in the millimeter-wave (mmWave) frequency bands. To improve the spectrum efficiency, uniform planar arrays are equipped at the UAVs and users for compensation of the high path loss and for mitigation of interference. We formulate a problem to jointly optimize the UAV positioning, user clustering, and hybrid analog-digital beamforming (BF) for the maximization of user achievable sum rate (ASR), subject to a minimum rate constraint for each user. Since the problem is highly non-convex and involves high-dimensional variable matrices and combinatorial programming variables, we develop a suboptimal solution via alternating optimization, successive convex optimization, and combinatorial optimization. First, we design the UAV positioning and user clustering under the assumption of ideal beam patterns, which significantly decouples the UAV positioning and directional BF. Then, the transmit and receive BF variables are successively optimized to approach the ideal beam patterns. Our simulation results verify the convergence and superiority of the proposed algorithm. Significant performance gains can be obtained compared to some benchmark schemes in terms of the ASR, and the proposed hybrid BF solution closely approaches a performance bound given by fully-digital BF.

Bistatic inverse synthetic aperture radar sparse aperture self-focusing algorithm based on the joint constraint of compressed sensing and minimum Tsallias entropy

Based on the low imaging resolution of bistatic inverse synthetic aperture radar (Bi-ISAR) and the failure of pulse correlation under the condition of sparse aperture cause that of the traditional self-focusing algorithm, a Bi-ISAR sparse aperture self-focusing algorithm with the combined constraint of image quality optimization and sparsity is proposed. First, the proposed algorithm establishes the Bi-ISAR sparse aperture self-focusing signal model, reconstructs images through fast sparse Bayesian learning (FSBL), uses the minimum Tsallis entropy and constraints the reconstruction process, iteratively updates the phase error, and performs self-focusing to realize the initial phase correction of Bi-ISAR images. Simulation results show that the proposed algorithm has a fast convergence speed, strong robustness to noise, and high accuracy in reconstructing images.

The Timing of Collision Between Asia and the West Burma Terrane, and the Development of the Indo‐Burman Ranges

AbstractThe West Burma Terrane (WBT) is a small terrane bounded to the east by the Asian Sibumasu Block and to the west by the Indo‐Burman Ranges (IBR), the latter being an exhumed accretionary prism that formed during subduction of Indian oceanic lithosphere beneath Asia. Understanding the geological history of the WBT is important for reconstruction of the closure history of the Tethys Ocean and India‐Asia collision. Currently there are major discrepancies in the proposed timings of collision between the WBT with both India and Asia; whether the WBT collided with India or Asia first is debated, and proposed timings of collisions stretch from the Mesozoic to the Cenozoic. We undertook a multi‐technique provenance study involving petrography, detrital zircon U‐Pb and Hf analyses, rutile U‐Pb analyses and Sr‐Nd bulk rock analyses on sediments of the Central Myanmar Basins of the WBT. We determined that the first arrival of Asian material into the basin occurred after the earliest late Eocene and by the early Oligocene, thus placing a minimum constraint on the timing of WBT‐Asia collision. Our low temperature thermochronological study of the IBR records two periods of exhumation, in the early‐middle Eocene, and at the Oligo‐Miocene boundary. The Eocene event may be associated with the collision of the WBT with India. The later event at the Oligo‐Miocene boundary may be associated with changes in wedge dynamics resulting from increased sediment supply to the system; however a number of other possible causes provide equally plausible explanations for both events.

A security-aware service function chain deployment method for load balance and delay optimization

Network function virtualization (NFV) decouples network functions from hardware devices. However, it introduces security challenges due to its reliance on software, which facilitates attacks. This security problem has a significant negative impact on the interests of users. Existing deployment methods are not suitable for SFC requests with a security demand, causing the use of substrate resources unreasonable and lower acceptance ratio. Moreover, a strict delay requirement is another challenge for NFV. To make the use of the substrate resources more reasonable and reduce the transmission delay, this paper proposes a security-constraint and function-mutex-constraint consolidation (SFMC) method for virtual network function (VNF) to reduce resource consumption and transmission delay. In addition, a security-aware service function chain (SASFC) deployment method for load balance and delay optimization is presented, which deploys service function chains according to the consolidated results of the SFMC method. The SASFC method first obtains a candidate server node set using resource, hosting capacity, security and node load constraints. It then obtains candidate paths according to the metric of the minimum transmission delay and link load constraint using the Viterbi algorithm. Finally, the path with the highest VNF security level match degree among the candidate paths is adopted to deploy virtual links, and the corresponding server nodes are employed to deploy VNFs. As a result, the SASFC method makes the use of substrate resources more reasonable. It improves the acceptance ratio and long-term average revenue to cost ratio, reduces transmission delay, and achieves load balancing. Experiment results show that when the number of VNFs is five, the acceptance ratio and long-term average revenue to cost ratio of the SASFC method are close to 0.75 and 0.88, which are higher than those of the compared methods. Its transmission delay and proportion of bottleneck nodes are 7.71 and 0.024, which are lower than those of the compared methods. The simulations demonstrate the effectiveness of the SASFC method.

New U-Pb zircon ages of plagiogranites from the Coastal Complex ophiolite and Twillingate batholith, Newfoundland: Evidence for the oldest and overlapping silicic magmatism in the nascent Cambrian peri-Laurentia forearc and arc terranes

The Coastal Complex (CC) and Bay of Islands Complex (BOIC) represent two supra-subduction zone (SSZ) forearc ophiolitic assemblages of different ages within the Taconic Humber Arm Allochthon of the Western Newfoundland Appalachians. To further constrain age relationships between the CC and BOIC and earliest initiation of Iapetus subduction, we acquired LA-ICP-MS U-Pb zircon ages for eleven plagiogranites sampled along strike of the CC belt. These ages combined with three prior legacy ages establish an age range of 514.3–502.7 Ma for the six CC plagiogranite plutons. The oldest precise ca. 514.3 Ma CC pluton age represents the oldest Taconic arc-related plutonic activity yet documented in Western Newfoundland and provides a minimum age for the intruded CC ophiolite basement and initiation of westerly vergent subduction within the peri-Laurentian Iapetus Ocean. This confirms the Early Cambrian CC mafic–ultramafic basement is significantly older than the juxtaposed SSZ BOIC, which formed by later rifting of the CC forearc along younger forearc spreading center in the Late Cambrian by ca. 488.3 Ma. After subduction initiation a prolonged early period CC forearc silicic magmatism lasted at least ∼ 11.6 Ma until ca. 502.7 Ma, a range consistent with age spans of magmatism in modern juvenile forearcs. We also reinvestigated the Central Newfoundland Twillingate Granite batholith thought to be one of the earliest major felsic batholiths formed within the adjacent juvenile arc massif of the Notre Dame Subzone, part of the same peri-Laurentian arc. We determined a precise 3-sample composite age of 504.3 ± 1.8 Ma that signals the formation of earliest Notre Dame arc edifice developed by Middle Cambrian. It overlaps the end-stage CC forearc plagiogranite magmatism and places a minimum mid-Cambrian age constraint on intruded ophiolitic arc tholeiitic and boninitic pillow lavas of the Sleepy Cove and correlated Lushs Bight volcanics, suggesting basement continuity with the CC.

Grey wolf optimizer for solving well placement optimization problem constrained to minimum well distance

Traditional optimizers require several experimentations to fine tune parameters and this makes them problem dependent and can compound the general simulation problem. Penalty method which is commonly used to solve constrained well placement optimization problem requires extensive experimentation to set up the right penalty parameter. Poor parameter set up affects performance of optimization tool. In this article, Grey Wolf Optimizer (GWO) is implemented as well placement optimizer. Superiority of feasible solutions method was proposed for handling the minimum well distance constraint. Powell-Skolnick (CPF-1) and Deb (CPF-2) constraint techniques were considered and their performances were compared to Unconstrained Problem Formulation (UCPF). Two field development strategies (DS-1 and DS-2) were considered and implemented in SPE1 (unimodal system) and PUNQ-S3 (multimodal system) reservoir models to evaluate the performances of CPF-1, CPF-2 and UCPF. Results revealed that under SPE1, UCPF gave the highest average Net Present Value (NPV) for DS-1 and DS-2 but with majority of the solutions violating the constraints whilst under PUNQ-S3, CPF-1 and CPF-2 showed superior performances against UCPF. Among the constraint satisfaction, CPF-2 showed relatively superior performance than CPF-1 in all cases except under DS-2 in PUNQ-S3.

Proportional topology optimisation with maximum entropy-based meshless method for minimum compliance and stress constrained problems

In this paper, proportional topology optimisation (PTO) with maximum entropy (maxent)-based meshless method is presented for two-dimensional linear elastic structures for both minimum compliance (PTOc) and stress constraint (PTOs) problems. The computation of maxent basis functions is efficient as compared to the standard moving least square (MLS) and possesses a weak Kronecker delta property leading to straightforward imposition of Dirichlet boundary conditions. The PTO is a simple, non-gradient, accurate, and efficient method compared to the standard topology optimisation methods. A detailed and efficient implementation of the computational algorithms for both PTOc and PTOs is presented. The maxent basis functions are calculated only once at the start of simulation and used in each optimisation iteration. Young’s modulus for each background cells is calculated using the modified solid isotropic material with penalisation (SIMP) method. A parametric study is also conducted on the degree of proportionality and history dependence of both PTOc and PTOs algorithms. A variety of numerical examples with simple and complex geometries, and structured and unstructured discretisations are presented to show the accuracy, efficiency, and robustness of the developed computational algorithms. Both PTOc and PTOs algorithms can handle large topological changes, and provide excellent optimisation convergence characteristics.

The Impact of Legal Recycling Constraints and Carbon Trading Mechanisms on Decision Making in Closed-Loop Supply Chain.

To investigate how legal constraints on the recycling rate of used products and carbon trading mechanisms affect the profits and other decisions of supply chain system members, this paper develops and solves a two-cycle game model in which the manufacturer dominates while the retailer takes a secondary position; the manufacturer produces only non-low-carbon new products in the first cycle and both new and low-carbon remanufactured products in the second cycle. Simultaneously, the effects of parameters such as recovery rate, unit carbon trading price, and carbon emission reduction factor on the decision making of members of the supply chain system are also discussed. Finally, the conclusions are verified by numerical analysis: (1) When carbon reduction is low, the manufacturer will choose the highest recycling rate to obtain the highest profit, and when carbon reduction is high, manufacturers tend to choose not to recycle when the minimum recycling rate bound by law harms the interests of manufacturers. (2) Under the implementation of the carbon trading mechanism, the unit carbon trading price affects the profits of the members of the supply chain system depending on the size of the carbon emission reduction, and the two are negatively correlated at lower carbon emission reductions and positively correlated at higher carbon emission reductions. (3) From the perspective of supply chain system members’ interests, legal constraints and the existence of carbon trading mechanisms are not always conducive to increasing the margins of members of the supply chain system, both relevant to the size of carbon emission reductions. (4) From the perspective of environmental benefits, supply chain members do not need to pay economic costs in all cases to contribute to environmental benefits, and the existence of minimum recycling rate constraints and carbon trading mechanisms are conducive to achieving carbon reduction targets.

OCSM : Finding overlapping cohesive subgraphs with minimum degree

Cohesive subgraph discovery in a network is one of the fundamental problems and investigated for several decades. In this paper, we propose the Overlapping Cohesive Subgraphs with Minimum degree (OCSM) problem which combines three key concepts for OCSM: (i) edge-based overlapping, (ii) the minimum degree constraint, and (iii) the graph density. To the best of our knowledge, this is the first work to identify overlapping cohesive subgraphs with the minimum degree by incorporating the graph density. Since the OCSM problem is NP-hard, we propose two algorithms: an advanced peeling algorithm and a seed-based expansion algorithm. Finally, we show the experimental study with real-world networks to demonstrate the effectiveness and efficiency of our proposed algorithms.

Machine Learning-Based Vision-Aided Beam Selection for mmWave Multiuser MISO System

In this letter, we propose a machine learning-based vision-aided beam selection (ML-VBS) for millimeter-wave indoor multi-user communications. The proposed scheme is aimed at addressing the beam selection overhead with narrow beams in a multi-user scenario. The proposed scheme relies on a base station (BS) equipped with a single camera to observe the scene and estimates the angles to the multiple users. Given the estimated angle information and the limited number of radio frequency chains at the BS, two serial deep neural network structures are employed for joint user and beam selection subject to a minimum rate constraint. The numerical evaluation shows that the proposed ML-VBS scheme achieves a good performance in terms of the multi-user angle estimation, achievable sum rate and low computational complexity compared to conventional beam selection techniques.

Modelling the impact of birth control policies on China's population and age: effects of delayed births and minimum birth age constraints.

We consider age-structured models with an imposed refractory period between births. These models can be used to formulate alternative population control strategies to China’s one-child policy. By allowing any number of births, but with an imposed delay between births, we show how the total population can be decreased and how a relatively older age distribution can be generated. This delay represents a more ‘continuous’ form of population management for which the strict one-child policy is a limiting case. Such a policy approach could be more easily accepted by society. Our analyses provide an initial framework for studying demographics and how social constraints influence population structure.

Max-Min Energy-Efficient Optimization for Cognitive Heterogeneous Networks With Spectrum Sensing Errors and Channel Uncertainties

In this letter, we design a robust resource allocation algorithm for a non-orthogonal multiple access (NOMA)-based cognitive heterogeneous network under spectrum sensing errors and channel uncertainties. Our objective is to maximize the minimum energy efficiency of femtocells subject to the maximum power constraint, the cross-tier interference constraint and the minimum rate constraint. The infinite-dimensional robust constraints with channel uncertainties are converted into convex ones by using a worst-case transformation approach. Then, the deterministic non-convex problem is transformed into a convex one by using convex optimization theory. Numerical results demonstrate that the proposed algorithm can achieve fast convergence and strong robustness.

Control of the shape of bubble growth on underwater substrates with different sizes of superhydrophobic circles

Inspired by the everyday experience of changing the shape of a blown-up balloon by imposing a constraint, a method to control the shape of underwater bubbles is proposed by tangential constraint forces generated by the wettability difference (WD), and two bubble growth modes are distinguished based on the tangential constraint force strength and the minimum apparent contact angle (CA) of the bubble after the WD constraint. First, the critical growth shape of the bubble with a combined shape of a vertical cylinder and hemispherical top is identified, and its corresponding critical contact radius RCritical = 2.7 mm is solved by the Young–Laplace equation. Then, the effects of the radii of the superhydrophobic circle (SBC) on the bubble growth shapes are studied experimentally. The result shows that as the SBC radius decreases, the minimum apparent CA of the bubble decreases, and the minimum tangential constraint forces increase. Therefore, the bubble growth mode changes from the bell mode (with a minimum apparent CA greater than 90°) with a weaker constraint to the Ω mode (with a minimum apparent CA less than 90°) with a stronger constraint, and the bubble growth shape tends toward spherical from a flattened sphere. The maximum bubble trapping rate, Laplace pressure difference at the apex and bottom of the bubble, the aspect ratio, and the bubble filling ratio also increase as the SBC radius deceases. Furthermore, our results suggest that the proper WD-patterned arrays on underwater substrates can enhance their application efficiency, and the size of SBCS # R4 is probably the best choice in all cases.

A graph theoretic approach to non-anticipativity constraint generation in multistage stochastic programs with incomplete scenario sets

Multistage-stochastic programming (MSSP) problems under both endogenous and exogenous uncertainties with gradual realization have been gaining attention in the literature, particularly, in chemical engineering applications. Recently several approaches have been introduced to generate the minimum cardinality non-anticipativity constraint (NAC) set for stochastic programs with various scenario set structures. However, they have been limited to uncertain parameters where the realizations occur instantaneously or the full set of scenarios is required, and may require reformulating the problem. This paper proposes an algorithm for generating a minimum cardinality set of NACs for MSSP problems under both endogenous and exogenous uncertainties with gradual realization without the need for (often non-trivial) reformulations. In addition, a heuristic version of this algorithm, which does not guarantee minimum NAC set, but allows for an efficient decomposable implementation, is developed. A thorough computational study demonstrates the benefit of reducing the NAC set, and compares the case of minimum vs near-minimum NAC sets, which has not been widely studied before.

Orthogonal State Reduction Variational Eigensolver for the Excited-State Calculations on Quantum Computers.

Variational quantum eigensolver (VQE) is a promising method for ground-state calculations on current noisy intermediate-scale quantum computers. However, the research progress of excited-state calculations on quantum computers is relatively slow. In order to extend the framework of VQE for excited-state calculations, we propose a new algorithm, orthogonal state reduction variational eigensolver (OSRVE), to determine the energies of excited states. Theoretical derivations prove that the optimized state in the OSRVE method can ensure the energy minimum and orthogonality constraint simultaneously, and OSRVE is also applicable for the degenerate state. The performance of OSRVE is demonstrated by numerical calculations of the H4 and H2O molecules. Compared with other excited-state calculation algorithms, OSRVE has obvious advantages in calculating lower-order excited states. This work extends the VQE algorithm to excited-state calculations, and OSRVE can be implemented on near-term quantum computers.

Assessment of the Modeling of Demand Response as a Dispatchable Resource in Day-Ahead Hydrothermal Unit Commitment Problems: The Brazilian Case

Modern power systems have experienced large increases in intermittent and non-dispatchable sources and a progressive reduction in the size of hydro reservoirs for inflow regularization. One method to mitigate the high uncertainty and intermittency of the net load is by Demand Response (DR) mechanisms, to allow a secure and reliable system dispatch. This work applied a mixed integer linear programming formulation to model DR as a dispatchable resource in the day-ahead hydrothermal scheduling problem, taking into account minimum load curtailment constraints, minimum up/down load deduction times, as well as piecewise linear bid curves for load shedding in eligible loads. The methodology was implemented in the official model used in Brazil and tested in large-scale problems to obtain the optimal daily dispatch and hourly pricing. The results show the positive impact of dispatchable DR loads in cost reduction and in mitigating peak values of energy prices, even for predominantly hydro systems, helping to preserve the reservoir levels and increasing the security of the supply in the future.

Deploying a GIS-Based Multi-Criteria Evaluation (MCE) Decision Rule for Site Selection of Desalination Plants

Water supply is one of the most critical infrastructures for development, and by desalinating the water of the Persian Gulf, water demands may be satisfied. The countries of the Persian Gulf basin have applied this technology and compensated for the country’s water shortage, whereas because of Iran’s unlimited access to water, desalination has only been applied on a local scale. Due to serious hydrological stress and periodic water shortages in Iran’s southern coastal area, seawater desalination may be necessary as an optional solution for water supply. Site selection for desalination plants is difficult as it may have a direct influence on the territorial and water environment, as well as disrupt biological systems, hence, the objective of this study was to identify desalination sites across the coastline of Hormozgan. To choose a suitable site, a multi-criteria evaluation (MCE) design was applied, with three scenarios evaluated in the constraints part and two scenarios considered in the criteria weight section. Altogether, out of 21 determination criteria considered for the construction of desalination facilities, 14 were associated to the inland and coastal segment, six with the marine zone, and one with the water quality phase. The results showed that about 33,584 ha in the optimal scenario, or when minimum and maximum constraints were applied, approximately 109,553 and 7182 ha, respectively, of the region, including a total of 11 zones, were suitable for the building of desalination facilities. In conclusion, this study was the first to consider MCE with many criteria and different scenarios for developing a decision rule for the installation of desalination facilities based on environmental and marine factors.

Enhanced Parallel-Particle Swarm Optimization (EP-PSO) Approach for Solving Nurse Rostering Problem

A Nurse Rostering Problem is a highly-constrained combinatorial optimization problem, where we assign several nurses to shifts by violating minimum constraints. Due to massive number of constraints, these problems are difficult to handle manually. The advantage of automating the task is to generate a roster having not only high quality but also more flexibility by reducing the workload, time and effort of head nurses. The PSO algorithm is extremely dependent upon settings of control parameters and balance the exploration and exploitation in search space. These problems are avoided by proposed an ES-PSO Algorithm. Highly constrained problems have huge search space to find an optimal solution, hence to cover that space and find the solution in the stipulated time necessary to increase population. However, it may take more time for particle updating and fitness evaluations. To improve execution time of the compute-intensive task, we have used OpenMP and CUDA framework. The adapted algorithm improves the outcome by minimizing penalty and reduces stuff of compute-intensive tasks.

Applying a Bayesian approach for refining the chronostratigraphy of the Yumidong site in the Three Gorges region, central China

Yumidong (Corn Cave) is a newly discovered Paleolithic site in the Three Gorges region of central China. Numerous Paleolithic artifacts have been excavated from the sedimentary deposits of the cave in association with faunal remains attributed to the Middle-Late Pleistocene Ailuropoda - Stegodon fauna of southern China. To establish the chronology of the sedimentary sequence (>5 m thick), 14 C dating was applied to bone and charcoal samples (n = 6); the U-series method was used to date in situ precipitated speleothems (n = 12), transported speleothem samples (n = 6) and 18 subsamples of a fossil tooth; and the coupled ESR/U-series method was used to date fossil teeth (n = 6). The derived dates were combined using a hierarchical Bayesian approach to generate a unified chronostratigraphy for the Yumidong sequence. In our Bayesian analyses, the 14 C and coupled ESR/U-series dates were considered to provide direct age estimates for the target layers, while the U-series dates of the in situ precipitated speleothems and fossil tooth were used as minimum age constraints and those of the transported speleothem fragments as maximum age constraints. The Bayesian analyses provided robust time intervals for the archeological layers: L2-Upper (14–23 ka), L2-Lower (27–63 ka), L3 (106–171 ka), L4 (140–192 ka), L10 (157–229 ka), L11 (181–256 ka), and L12 (214–274 ka) with a probability of 95%, allowing the establishment of a ∼300 ka long geological and archeological history for the Yumidong site and placing it as a reference site for Paleolithic cultural evolution in the Three Gorges region from the late Middle Pleistocene to Late Pleistocene.

Radiometric dating of Meipu hominin site in China by coupled ESR/U-series and cosmogenic 26Al/10Be burial dating methods

The Three Gorges and Western Hubei area in the geographic central part of China was a potential migration corridor for early hominin and mammals linking South and North China during the Pleistocene period. Some key early hominin sites are known in this region where limestone cave and fissure sites are numerous but difficult to date as beyond the dating range of OSL and mass spectrometry U-series method. Here, we report radiometric dating study for such a hominin site, Meipu (Hubei Province), by coupled ESR and U-series dating of nine fossil teeth and cosmogenic 26 Al/ 10 Be burial dating of one quartz sediment. The burial age calculated by simple burial model (573 ± 266 ka) gives a minimum age constraint of the sediment. The fossil dating provided two main age groups at 541 ± 48 ka and 849 ± 39 ka, the older age group is in agreement with the U-series age (>630 ka) of the flowstone overlying the fossil layer and the paleomagnetic data which placed the Brunhes-Matuyama boundary in the fossil layer. The reason of this age difference is probably caused by the U-content discrepancy in the enamel of the dated fossil samples. This study exhibits the limitation of ESR/U-series fossil dating and the importance of using multiple dating approach when it is possible in order to identify the problematic ages. • A key hominin site in Three Gorges area at the corridor between South and North China was dated by radiometric methods. • Two radiometric dating methods were applied directly to the fossil layer of the Meipu hominin site. • The results of multiple dating approach were compared to constrain the age of an Early-Middle Pleistocene hominin site.