Set Of Constraints Research Articles

Modelling and optimization of trajectory deviation for compound directional drilling in coal mines

During the sliding mode of compound directional drilling process in coal mines, the inclined angle and azimuth angle need to be changed to minimize the trajectory deviation between the actual trajectory and the designed trajectory. The inclined angle and azimuth angle can be changed by adjusting the tool face angle. In this article, a modelling and optimization method is proposed to obtain optimal tool face angle for sliding mode. Firstly, the gaussian process regression method is employed to build calculation model of trajectory deviation. The optimization model of trajectory deviation consists of the established calculation model of trajectory deviation and the set constraints. Then, the optimal inclination angle and azimuth angle are obtained by solving the constitutive optimization model using an improved particle swarm optimization algorithm. Next, the calculation model of tool face angle is built to represent the relationship between inclination angle, azimuth angle and tool face angle. The optimal tool face angle is calculated based on optimal inclined angle and azimuth angle. Finally, an industrial case study based on the actual drilling data verifies that the proposed method is beneficial to track designed trajectory during drilling process. The proposed method meets the requirements of on-site construction accuracy and ensures the safety and stability of drilling.

Efficient Frontier and Applications in Product Offering and Pricing

Problem definition: The joint assortment and pricing problem is notoriously difficult to solve, especially for large-scale issues subject to various operational constraints arising from business practices. In this paper, we delve into the joint optimization challenge under constrained logit choice models, accounting for product-differentiated price sensitivities across static, randomized, and dynamic contexts. Methodology/results: We develop a unified optimization methodology that applies efficient frontier and dimensional reduction and transforms the joint optimization problem into a single-variable one with respect to the total choice probability. The efficient frontier is employed to transform the nonconcave objective function equivalently into its concave counterpart. We show that the optimal prices are uniquely determined by the common target adjusted markup. The complexity of the mixed combinatorial optimization problem can be reduced by searching over efficient sets of polynomial size. In the randomized assortment and pricing problem in which the product offer sets and prices follow certain distribution, we show that randomization has the potential to elevate the total revenue to the exact efficient frontier, a feat that the static problem may fail to achieve (with a given total choice probability). For dynamic joint product selection and pricing, we find that the optimal policy adopts a simple time-threshold structure that can be precomputed. Furthermore, we illustrate the robustness of our methodology by extending the analysis to a variety of general settings, including the nested logit model. Managerial implications: The proposed methodology contributes to the increasingly popular topic in retail management by significantly reducing the computational complexity of joint product offering and pricing under different constraints. Our results regarding the effects of product set constraints and price bounds provide valuable insights and guidance to practitioners on product offering and pricing in various business scenarios. Funding: C. Ke acknowledges financial support from the National Natural Science Foundation of China [Grant 72101113]. L. Lu acknowledges financial support from the Hong Kong Research Grants Council [Grants 26501021 and 16502423]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0164 .

Distributed convex optimization over nonlinear networks under set constraints

Distributed convex optimization over nonlinear networks under set constraints

The Creative Potential of Evolving Constraints in Peer-to-Peer Reciprocal Coaching: A Three-way Investigation

This exposition reports and assesses the experience of the project ‘The Creative Potential of Evolving Constraints in Peer-to-Peer Reciprocal Coaching: A Three-way Investigation’ (hereafter 3WI), funded by the Interacting Minds Centre, Aarhus University. 3WI was designed to gauge the utility of evolving creativity constraints — that is, deliberately adopted restrictions (whether self-imposed or suggested by another) to choices in a given creative project — in the development of projects by the three participants: a dance artist and filmmaker, a songwriter, and an academic video-essayist. The format of 3WI was as follows. At monthly meetings from September to December 2021, each participant presented work in progress and exchanged feedback with the other two participants. Each meeting culminated in the setting of tasks and constraints designed to guide the development of individual projects over the subsequent month. After an introduction to the format and aims of 3WI, the exposition begins with a description of 3WI’s procedural and theoretical coordinates: the Critical Response Process, a formalised protocol for eliciting feedback on creative projects developed by choreographer Liz Lerman; The Five Obstructions (Lars Von Trier and Jørgen Leth, 2003), a film which models the provision of creativity constraints; and theory and scholarship concerning the utility of creativity constraints. The exposition continues with a description of the projects being developed by each participant (a dance performance and dance film; two songs; two sections of an academic videoessay), and an individual and illustrated account of the feedback meetings and development of those projects over the course of 3WI. These accounts are followed by a discussion reflecting on setting and receiving constraints, and an assessment of the experience of the project. We conclude with some contemplation of the ethics of constraint-setting and the lessons of the 3WI experience for other makers. Constraint-based procedures are commonly employed and recognised as generative in artistic and design contexts, and they are also used in experimental academic work. 3WI was an attempt to test the utility of constraint-setting as a form of formative peer-to-peer feedback in the development of real creative projects. This exposition will be of interest to artists and academics interested in deploying creativity constraints for the development of creative and creative-critical projects. It will be particularly relevant for those who work in collaborative and interdisciplinary contexts. <style> /* rules to make button only show up in META */ .download-accessible { display:none; } .meta-right-col .download-accessible { display: inline-block; padding: 9px; margin-bottom:25px; border: 1px solid black; background-color:white; } </style> <a class="download-accessible" href="/profile/download-media?work=2936353&file=3307182" title="This accessible PDF is a derivative of the original which it is meant to support and not replace.">Download Accessible PDF</a>

Does physical performance demonstrate patient-reported outcomes after lumbar spine surgery?

BackgroundDue to time and setting constraints in clinical practice, performing a comprehensive assessment with both questionnaires and physical performance tests may not be possible. This study aimed to demonstrate the relationship between physical performance and patient-reported outcomes in patients after Lumbar Spine Surgery (LSS).MethodsA cross-sectional study was conducted with 50 participants who were followed up at least six months after LSS. Participants were evaluated using the Visual Analog Scale (VAS) for activity and rest, Modified Oswestry Disability Index (mODI), Lumbar Spine Instability Questionnaire (LSIQ), One Leg Stance Test (OLST), Semi-Tandem Stance Test (STST), 4 m Gait Speed Test (4MGS), and Timed Up and Go Test (TUG).ResultsOLST was moderately correlated with the mODI (r=-0.442, p < 0.01). STST moderately correlated with mODI (r=-0.356, p < 0.05). TUG was strongly correlated with mODI (r = 0.564, p < 0.01). In addition, TUG showed a moderate correlation with a-VAS and LSIQ, respectively (r1 = 0.392, r2 = 0.475, p < 0.01). A strong correlation was found between 4MGS and mODI (r=-0.535, p < 0.01). 4MGS had a moderate correlation with LSIQ (r=-0.374, p < 0.01). A regression model summary showed that the TUG, OLST, and STST were not related to r-VAS, a-VAS, mODI, and LSIQ (p > 0.01). Higher gait speed on the 4MGS test was strongly associated with lower mODI scores (standardized ß=-0.538, p = 0.021).ConclusionLess activity pain and disability are associated with good balance and performance. 4MGS can mostly predict patient-reported function in patients after LSS.

The Detectability of CH4/CO2/CO and N2O Biosignatures Through Reflection Spectroscopy of Terrestrial Exoplanets

The chemical makeup of Earth’s atmosphere during the Archean (4–2.5 Ga) and Proterozoic eon (2.5–0.5 Ga) contrast considerably with the present-day: the Archean was rich in carbon dioxide and methane, and the Proterozoic had potentially higher amounts of nitrous oxide. CO2 and CH4 in an Archean Earth analog may be a compelling biosignature because their coexistence implies methane replenishment at rates unlikely to be abiotic. However, CH4 can also be produced through geological processes, and setting constraints on volcanic molecules such as CO may help address this ambiguity. N2O in a Proterozoic Earth analog may be evidence of life because N2O production on Earth is mostly biological. Motivated by these ideas, we use the code EXORELR to generate forward models and simulate spectral retrievals of an Archean and Proterozoic Earth-like planet to determine the detectability of CH4, CO2, CO, and N2O in their reflected light spectrum for wavelength range 0.25–1.8 μm. We show that it is challenging to detect CO in an Archean atmosphere for volume mixing ratio (VMR) ≤ 10%, but CH4 is readily detectable for both the full wavelength span and truncated ranges cut at 1.7 μm and 1.6 μm, although for the latter two cases the dominant gas of the atmosphere is misidentified. Meanwhile, N2O in a Proterozoic atmosphere is detectable for VMR = 10−3 and long wavelength cutoff ≥1.4 μm, but undetectable for VMR ≤ 10−4 . The results presented here will be useful for the strategic design of the future Habitable Worlds Observatory and the components needed to potentially distinguish between inhabited and lifeless planets.

Hierarchical Robust Generalized Nash Equilibrium Seeking of High-Order Uncertain Nonlinear Systems.

This article investigates the distributed generalized Nash equilibrium (GNE) seeking problem of noncooperative games (NGs) for high-order strict-feedback nonlinear multiagent systems (MASs). In particular, the feasible action set of each agent is not only subject to local set and inequality constraints but also coupled through an equality constraint with other agents. This constraint structure is more general and covers most of the constraints in the GNE seeking literature. To accomplish the concerned GNE seeking objective, we propose a novel hierarchical GNE seeking approach in this article to decouple the distributed GNE seeking algorithm design into two layers. First, we construct a distributed primary-dual GNE estimator to generate virtual reference signals that converge to the GNE. Then, with the output of the estimator as the reference signal, we develop an adaptive tracking controller to solve the resultant tracking problems under output constraints. To overcome the negative effects of the disturbances, novel compensating terms associated with smooth functions and positive integrable time-varying functions are incorporated in the controller design, which thereby realizes the exact GNE seeking in the presence of nonvanishing mismatched disturbances. At last, an example is given to support the theoretical analysis of the proposed algorithms.

Distributed continuous-time algorithm for nonsmooth aggregative optimization over weight-unbalanced digraphs

This paper studies the problem of distributed continuous-time aggregative optimization with set constraints under a weight-unbalanced digraph, where the nonsmooth objective function of each agent relies both on its own decision and on the aggregation of all agents’ decisions. To eliminate the impact of unbalanced digraphs, a consensus-based estimator that tracks the aggregation information is designed through a gradient rescaling technique. Considering that cost functions are nondifferentiable in many scenarios, such as electric power management that takes price caps into account, a novel distributed continuous-time optimization algorithm via generalized gradient is presented in a two-time scale. Moreover, the convergence of the algorithm is established through nonsmooth analysis and singular perturbation theory. Compared to the existing results, which depend on undirected graphs, the proposed strategy is applicable to general digraphs, which may be weight-unbalanced. Further, the assumption on the differentiability of objective functions is relaxed. Finally, two numerical examples are provided to verify the findings.

Riverine Cu-distribution in sediments of the Jaba-Kawerong river system 30 years after cease of mining at Panguna/Bougainville

The investigation of surface and river sediments over 30 years after the cease of large scale Cu and Au mining operation at Panguna (Bougainville) shows the impact of mining and tailings disposal on the associated riverine environment. While Zn, Pb and Cd have elevated concentrations in the former mining area and are low (< 100, < 28, < 1 mg/kg, respectively) in sediment of the Jaba-Kawerong river system, Cu represents the dominant environmental metal emission. Sediments of active streams and overbank deposits range between 1000 and 3000 mg/kg Cu. Most samples exceed freshwater sediment or soil quality guideline values, indicating the probability of toxic effects on sediment dwelling or aquatic organisms and ecological or health risks associated to agricultural use of the former mining area and floodplains. Copper in surface and river sediments is associated to bornite, chalcopyrite and chloritized biotite of the primary Panguna ore mineral assemblage. This attests to ongoing remobilization of sediment and/or reflects mobilization of additional Cu bearing material from the waste rock dump of the Panguna mine. Copper in surface and river sediments is also contained in secondary Cu-phases such as covellite as well as hydrated basic Cu-sulfates, which formed under locally variable redox conditions. Fe-oxihydroxides, occurring in variable abundance as reflected by Fe concentrations between 18,200 and 379,000 mg/kg (Mn 145–3086 mg/kg), can be identified as further Cu-carriers, taking up the metal from the aqueous phase in the sedimentary pore space. Mine derived input of Cu bearing minerals is confined to the sedimentary body of the Jaba-Kawerong river system. The diversity of Cu bearing phases with different environmental and processing properties sets constraints on re-processing sediments as secondary Cu-ores or re-using of sediments as building material.

Prescribed‐Time Distributed Optimization With Set Constraints Based on Time‐Domain Transformation

ABSTRACTThis paper delves into the prescribed‐time distributed optimization problem for multi‐agent systems (MASs), considering set constraints. First, we transform the challenging optimization problem from the prescribed‐time ‐domain into the asymptotic time ‐domain through a time‐domain transformation (TDT) technique. This strategic shift substantially mitigates the analytical complexities inherent in the original formulation. Second, we develop a novel class of TDT‐based optimization algorithms, utilizing gradient projection and Lagrange multipliers. This algorithm is tailored to efficiently tackle the distributed optimization problem while adhering to the set constraints. To further alleviate the computational and communication overheads, we introduce a corresponding TDT‐based event‐triggered optimization algorithm. Moreover, a rigorous analysis of both the optimal solution to the optimization problem and the system's stability is given by using optimization theory and Lyapunov stability theory. This comprehensive analysis provides valuable insights into the behavior and performance of our proposed approach. Finally, two numerical simulation results are presented to demonstrate the feasibility as well as effectiveness of the offered distributed control arrangement.

Cosmological Models in Lovelock Gravity: An Overview of Recent Progress

In the current review, we provide a summary of the recent progress made in the cosmological aspect of extra-dimensional Lovelock gravity. Our review covers a wide variety of particular model/matter source combinations: Einstein–Gauss–Bonnet as well as cubic Lovelock gravities with vacuum, cosmological constant, perfect fluid, spatial curvature, and some of their combinations. Our analysis suggests that it is possible to set constraints on the parameters of the above-mentioned models from the simple requirement of the existence of a smooth transition from the initial singularity to a realistic low-energy regime. Initially, anisotropic space naturally evolves into a configuration with two isotropic subspaces, and if one of these subspaces is three-dimensional and is expanding while another is contracting, we call it realistic compactification. Of course, the process is not devoid of obstacles, and in our paper, we review the results of the compactification occurrence investigation for the above-mentioned models. In particular, for vacuum and Λ-term EGB models, compactification is not suppressed (but is not the only possible outcome either) if the number of extra dimensions is D⩾2; for vacuum cubic Lovelock gravities it is always present (however, cubic Lovelock gravity is defined only for D⩾3 number of extra dimensions); for the EGB model with perfect fluid it is present for D=2 (we have not considered this model in higher dimensions yet), and in the presence of spatial curvature, the realistic stabilization of extra dimensions is always present (however, such a model is well-defined only in D⩾4 number of extra dimensions).

Topology Optimization of the Bracket Structure in the Acquisition, Pointing, and Tracking System Considering Displacement and Key Point Stress Constraints

The lightweight and displacement-stable design of the mechanical support structure within the APTS (Acquisition, Pointing, and Tracking System) is crucial for enhancing the payload capacity of remote sensing, satellite communication, and laser systems, while still meeting specified functional requirements. This paper adopts the Solid Isotropic Material with Penalization (SIMP) method to investigate the structural topology optimization of the L-shaped bracket in the APTS, aiming to minimize structural compliance while using volume, key point displacement, and maximum stress as constraints. In the optimization model, differences in the topology of the L-shaped bracket structure are explored to minimize structural compliance, which was performed under volume, key point displacement, and stress constraints, and the results are compared with the initial reinforced structure. The innovative L-shaped bracket structure obtained through topology optimization uses significantly less material than the initial reinforced design, while still meeting the displacement and stress constraints. After smoothing, rounding, and finite element analysis, the displacement and stress performance of the optimized L-shaped bracket structure satisfies the set constraints. The method proposed in this paper offers an innovative solution for the lightweight design of mechanical support structures in APTS, with significant engineering application potential.

Consensus Seeking in Large-Scale Multiagent Systems With Hierarchical Switching-Backbone Topology.

Recent developments in multiagent consensus problems have heightened the role of network topology when the agent number increases largely. The existing works assume that the convergence evolution typically proceeds over a peer-to-peer architecture where agents are treated equally and communicate directly with perceived one-hop neighbors, thus resulting in slower convergence speed. In this article, we first extract the backbone network topology to provide a hierarchical organization over the original multiagent system (MAS). Second, we introduce a geometric convergence method based on the constraint set (CS) under periodically extracted switching-backbone topologies. Finally, we derive a fully decentralized framework named hierarchical switching-backbone MAS (HSBMAS) that is designed to conduct agents converge to a common stable equilibrium. Provable connectivity and convergence guarantees of the framework are provided when the initial topology is connected. Extensive simulation results on different-type and varying-density topologies have shown the superiority of the proposed framework.

Side-Constrained Dynamic Traffic Equilibria

Dynamic flows are a well-studied model for car traffic in road networks. The assumption that every driver chooses her route in such a way as to selfishly minimize her own travel costs leads to the solution concept of dynamic equilibria, that is, dynamic flows wherein every flow particle travels along a cost minimal route (under the travel costs induced by this flow). In practice, however, there are often additional constraints on certain parts of the networks that restrict the options of the individual drivers like traffic limits due to security concerns in tunnels or to keep emission levels in some areas below certain thresholds. In “Side-Constrained Dynamic Traffic Equilibria,” Graf and Harks develop a general framework for incorporating such additional side constraints into dynamic flow models. They provide characterization results for the resulting equilibria via (quasi-)variational inequalities and show the first existence result for the nonconvex setting of volume constraints.

Optimal planning method of distributed generation in AC/DC microgrid considering power balance

Abstract To optimize AC/DC hybrid microgrid power planning, improve operational efficiency, and balance power distribution, we constructed an optimization model for AC/DC microgrid power generation, covering power, economy, reliability, and environmental protection, and set constraints to solve optimal planning. The experiment shows that this method enhances voltage stability, improves power supply quality, enhances distributed power generation efficiency, and reduces carbon emissions.

Distributed Online Learning Algorithm for Noncooperative Games Over Unbalanced Digraphs.

This article investigates constrained online noncooperative games (NGs) of multiagent systems over unbalanced digraphs, where the cost functions of players are time-varying and are gradually revealed to corresponding players only after decisions are made. Moreover, in the problem, the players are subject to local convex set constraints and time-varying coupling nonlinear inequality constraints. To the best of our knowledge, no result about online games with unbalanced digraphs has been reported, let alone constrained online games. To seek the variational generalized Nash equilibrium (GNE) of the game online, a distributed learning algorithm is proposed based on gradient descent, projection, and primal-dual methods. Under the algorithm, sublinear dynamic regrets and constraint violations are established. Finally, online electricity market games illustrate the algorithm.

Combining Type Checking and Set Constraint Solving to Improve Automated Software Verification

Abstract This technical note shows how we have combined prescriptive type checking and constraint solving to increase automation during software verification. We do so by defining a type system and implementing a typechecker for $\{log\}$ (read ‘setlog’), a Constraint Logic Programming language and satisfiability solver based on set theory. The constraint solver is proved to be safe w.r.t. the type system. Two industrial-strength case studies are presented where this combination is used with very good results.

OPTIMIZATION ALGORITHM OF PUBLIC SERVICE FACILITIES LAYOUT IN EARTHQUAKE-STRICKEN AREAS BASED ON SA ALGORITHM

The environment in earthquake-stricken areas is complex and changeable. The optimization of public service facility layout usually involves multiple objectives, such as maximizing coverage, minimizing service distance, optimizing resource allocation, etc. The coupling conflict between these objectives weakens the functions of public service facilities in earthquake-stricken areas. To improve the emergency response speed of the earthquake-stricken regions and reduce disaster losses, a simulated annealing (SA) based optimization algorithm for the layout of public service facilities in earthquake-stricken areas is proposed. Considering the public service demand in different stages of the earthquake-stricken area, set the minimum maximum weighted distance, the minimum number of facility points, and the minimum total weighted distance of the service demand point area within the service area of the public service facility point as the objective function, and set constraints such as each demand point is covered by at least one facility point, and the minimum number of public service facility points, build a multi-objective optimization model of public service facilities layout to avoid coupling conflicts between multiple objectives. The SA algorithm is used to solve the multi-objective optimization model of public service facility layout. SA algorithm adopts temperature update function and sets heuristic cooling criteria. Combining the success-failure method and the variable scale method, a new solution is generated using the effective offset. The improved Metropolis algorithm is used to set the acceptance criteria for the solution to obtain the optimal layout result for public service facilities in earthquake-stricken areas. The experimental results show that the algorithm can effectively optimize the layout of public service facilities in earthquake-stricken areas, and improve facility coverage and resource utilization.

The value of owning the symbols that orientate us within Subjectivity

Judith Butler contests Ernesto Laclau and Slavoj Žižek's argument that the limits to symbolisation which shape political action are best accounted for through Jacques Lacan's account of the Symbolic, Imaginary and Real. Butler agrees that we each emerge as social subjects on the condition of foreclosures, but disagrees that such foreclosures are prior to the social or explicable through a universal account of kinship. Oyèrónkẹ́ Oyĕwùmí has a somewhat similar critique of the Eurocentric foundations of feminist concepts. She argues that Western hierarchies, organised through ‘bio-logic’ or ‘body-reasoning’ with an emphasis on the sex/gender binary, are culturally particular. Oyĕwùmí distinguishes between relational, dynamic, fluid social hierarchies organised by seniority, and hierarchies organised by body-reasoning which are orientated towards fixity, and certainties. In this article I outline Bracha Ettinger's matrixial theory and argue that while it does not do what either Oyĕwùmí (transcend the terms of the nuclear family) or Butler (divest Lacan's paternal law of its power) advocate, it does provide us with the language to better account for how ‘body-reasoning’ structures our orientations and sets constraints on transformative processes. Through an account of multiple strata of subjectivity, within an expanded Symbolic, inscribed in social life through symbolic filters based on corporeality, matrixial theory enables us to account for the embeddedness of a strong orientation towards constant individuation, alongside a persistent disavowal and fear of processes of co-emergence at a non-cognitive level of subjectivity within Western thought. In their exchange, Laclau theorises social transformation through articulatory logics whereas Butler stresses the need for the work of cultural translation. Drawing on Ettinger’s and Oyĕwùmí's work, I propose that practices of translation must include a rigorous accounting for our orientations and investments within Subjectivity.

A negative-carbon planning method for agricultural rural industrial park integrated energy system considering biomass energy and modern agricultural facilities

Biomass energy, recognized as a “zero-carbon” energy, has gradually become a crucial approach to promoting the low-carbon transformation of agricultural rural industrial parks (ARIP). Meanwhile, modern agricultural facilities (MAF) can play a significant role in adjusting agricultural load. Therefore, this paper proposes a negative-carbon planning method for the ARIP integrated energy system (IES). Firstly, carbon activities occurring during the operation of ARIP are sorted out and modeled based on the life cycle assessment (LCA) method, especially modeling the “zero-carbon” and “negative-carbon” benefits of biomass energy. At the same time, the models of both agricultural irrigation systems and straw bundling direct combustion heating are constructed in the ARIP planning. Then, a negative-carbon planning model for ARIP IES is established with the goal of minimizing the annualized total cost, where carbon emission reduction is integrated into the optimization objectives through carbon trading. On this basis, a two-stage distributionally robust optimization (DRO) planning model is constructed, where a box-like set and comprehensive norm constraints are used to model the seasonal differences of agricultural industry loads and the uncertainty of probability distribution in photovoltaic (PV) scenarios. Especially, a box set with adjustable uncertainty coefficients is introduced to simulate fluctuations of output in PV scenario. Finally, the CPLEX solver is used to solve the planning model. verify the effectiveness of the proposed planning method in enhancing the economic and environmental effects of ARIP. Results indicate that the proposed planning model can reduce the total cost by 49.584 × 104 $. Besides, the annual carbon emissions can be reduced from 37533.98 t CO2-eq to −15834.5 t CO2-eq. Especially, the carbon sequestration effect of biochar is the key link in achieving “negative carbon” in ARIP.