Location Constraints Research Articles

The conditional p-dispersion problem

We introduce the conditional p-dispersion problem (c-pDP), an incremental variant of the p-dispersion problem (pDP). In the c-pDP, one is given a set N of n points, a symmetric dissimilarity matrix D of dimensions $$n\times n$$ , an integer $$p\ge 1$$ and a set $$Q\subseteq N$$ of cardinality $$q\ge 1$$ . The objective is to select a set $$P\subset N\setminus Q$$ of cardinality p that maximizes the minimal dissimilarity between every pair of selected vertices, i.e., $$z(P\cup Q) {:}{=}\min \{D(i, j), i, j\in P\cup Q\}$$ . The set Q may model a predefined subset of preferences or hard location constraints in incremental network design. We adapt the state-of-the-art algorithm for the pDP to the c-pDP and include an ad-hoc acceleration mechanism designed to leverage the information provided by the set Q to further reduce the size of the problem instance. We perform exhaustive computational experiments and show that the proposed acceleration mechanism helps reduce the total computational time by a factor of five on average. We also assess the scalability of the algorithm and derive sensitivity analyses.

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.

Location-Constrained Virtual Machine Placement (LCVP) Algorithm

Virtual machine (VM) placement is the current day research topic in cloud computing area. In order to solve the problem of imposing location constraints on VMs to meet their requirements in the process of VM placement, the location-constrained VM placement (LCVP) algorithm is proposed in this paper. In LCVP, each VM can only be placed onto one of the specified candidate physical machines (PMs) with enough computing resources and there must be sufficient bandwidth between the selected PMs to meet the communication requirement of the corresponding VMs. Simulation results show that LCVP is feasible and outperforms other benchmark algorithms in terms of computation time and blocking probability.

The implementation of a digital service approach to fostering team autonomy, distant collaboration, and knowledge scaling in large enterprises

BACKGROUND: Autonomous acting of individuals and as teams are key elements of agile, distributed, and partly or entirely distant working environments. The availability of relevant processes, methods, tools, and guidelines is key to leveraging team autonomy. OBJECTIVE: This article presents the design and implementation of a digital self-service kit (SSK) approach featuring high scalability, as well as a quality assurance and continuous improvement mechanism. As consumers, the teams within an organization can use these SSK’s anytime and on-demand without any constraints in location, time, or quota. As producers (of knowledge and experience), they can also assume active roles in the extension and continuous improvement of the SSK’s. METHODS: This has been achieved in open community networks where feedback is actively leveraged and constantly integrated in the SSK’s design. Such open Communities of Practices (CoP) ensure that all interested parties can contribute to the adequateness of both the content and the provision of the SSK’s in both local and distant corporate settings. Both the design and implementation have been done and evaluated in a large-scale international corporate environment where high cultural diversity, as well as distant collaboration are of key importance. RESULTS: The results presented in this article include a generic digital self-service approach to distance learning and coaching of teams in the particular context of the agile transformation of large corporate organizations. Key elements include a strong and systematic expert team involvement in the process of the setup and design of such digital SSK’s, as well as a well-explained and understood kit structure for efficient and effective utilization and re-contextualization of the contained knowledge into team-specific project contexts. This contributes to team autonomy as a major prerequisite for the agile transformation, as well as knowledge scaling across the organisation. CONCLUSIONS: The key insights gained from this experiment confirm the high relevance and effectivity of the approach especially during periods where distant collaborations are essential (e.g. during a pandemic crisis).

Lightning Currents on Fastening Assemblies of an Aircraft Fuel Tank—Part III: Validation of the Current Assessment Method With Measurement

This article proposes a new fastener model and validate the stochastic process for the lightning current assessment in the aircraft assemblies proposed in the previous parts. In particular, the stochastic method concerns the finite-difference time domain (FDTD) fastener modeling for which the variability of the contact resistance has to be taken into account. The principle is to merge an electromagnetic fastener model with an uncertainty model. The new fastener model proposed in this article is a wire with a lumped resistor on a low conductive plate. This model is an improvement of the model of Part I, where the fastener is only represented by a wire with a lumped resistor. The proposed model in this article is able to ensure a good shielding effectiveness without current distribution disruptions provided that the conductivity of the plate is weak in contrast to the lumped resistor. Moreover, it has the benefits to be able to represent any fastener without location constraint in the FDTD grid. A log-normal distribution has been previously established as uncertainty model that represents the variability of the resistive parameter. The fastener model is included in the FDTD modeling of a realistic fuel tank with each lumped resistor taking a probabilistic value according to the log-normal law. To take into account, the variability of resistors, several simulations with different sets of resistance values are performed. The aim is to surround current measurements with simulated currents at various locations of the fuel tank for a lightning injection performed directly on a fuel tank fastener. This article demonstrates that a specific attention must be given to the modeling of fasteners close to the lightning injection point for the current assessment. Moreover, the results highlight the relevance of the use of an uncertainty model and its reliability for the lightning current assessment.

Active Power Loss Reduction for Radial Distribution Systems by Placing Capacitors and PV Systems with Geography Location Constraints

This paper presents a highly effective method of installing both capacitors and PV systems in distribution systems for the purpose of reducing total power loss in branches. Three study cases with the installation of one capacitor, two capacitors and three capacitors were implemented and then the optimal solutions were used to install one more photovoltaic (PV) system. One PV system with 20% active power of all loads and less than active power of all loads was tested for two different conditions: (1) with geography location constraint and (2) without geography location constraint for PV system placement. The results from two systems consisting of 33 and 69 nodes were obtained by using the Stochastic Fractal Search Optimization Algorithm (SFSOA). Simulation results show that this method can determine the appropriate location and size of capacitors to reduce the total power losses more effectively than other existing methods. Furthermore, the paper also demonstrates the real impact of using both capacitors and PV systems to reduce active power loss as well as improve the voltage profile of distribution systems. This paper also finds that if it is possible to place PV systems in all nodes in distribution systems, the benefit from reducing total loss is highly significant and the investment of PV system placement is highly encouraged. As a result, it is recommended that capacitors and PV systems be used in distribution networks, and we claim that two important factors of the installed components consisting of location and size can be determined effectively by using SFSOA.

Optimal Design of Bus Stop Locations Integrating Continuum Approximation and Discrete Models

Although transit stop location problem has been extensively studied, the two main categories of modeling methodologies, i.e., discrete models and continuum approximation (CA) ones, seem have little intersection. Both have strengths and weaknesses, respectively. This study intends to integrate them by taking the advantage of CA models’ parsimonious property and discrete models’ fine consideration of practical conditions. In doing so, we first employ the state-of-the-art CA models to yield the optimal design, which serves as the input to the next discrete model. Then, the stop location problem is formulated into a multivariable nonlinear minimization problem with a given number of stop location variables and location constraint. The interior-point algorithm is presented to find the optimal design that is ready for implementation. In numerical studies, the proposed model is applied to a variety of scenarios with respect to demand levels, spatial heterogeneity, and route length. The results demonstrate the consistent advantage of the proposed model in all scenarios as against its counterparts, i.e., two existing recipes that convert CA model-based solution into real design of stop locations. Lastly, a case study is presented using real data and practical constraints for the adjustment of a bus route in Chengdu (China). System cost saving of 15.79% is observed by before-and-after comparison.

User acceptance of virtual reality technology for practicing digital twin-based crisis management

ABSTRACT Digital Twin can provide emergency response staff with large quantities of useful information about the emergency. However, the capability of the staff to understand and use the information correctly is equally as important. Hence, regular crisis management training is required in sophisticated manufacturing systems. Still, the time and location constraints limit the frequency of conducting such practices. As such, virtual reality-based crisis management training methods were proposed in the literature. However, little research was conducted to investigate the underlying mechanisms that drive both the perception and the adoption of virtual reality for crisis management training among users. To address this research gap, this study proposed a research model to examine the effects of perceived usefulness, perceived ease of use, perceived behavioral control, application-specific self-efficacy, and attitude on users’ acceptance of the system. A partial least squares structural equation modeling approach was used for model testing based on 103 valid observations. The results demonstrated that the constructs proposed in our study determined user acceptance of the system, and the research model was able to explain 60% of the variance in behavioral intention. The likelihood of acceptance of related technologies may be increased by applying the findings of this study.

Heuristic and Backtracking Algorithm for Multimanned Assembly Line Balancing Problem with Location Constraints

This article examines the problem of balancing modern assembly lines for large-size products typical for the automotive industry. The model of a multimanned assembly line balancing problem is proposed, in which assembly tasks are assigned to specific areas closely related to the place of the performance thereof on the vehicle. The model takes into account additional location restrictions. The proposed approach fits in with current trends aiming at minimizing the space occupied by assembly lines along with reducing the number of stations. A hybrid method is proposed combining modified known heuristics of task assignments to workstations with bounding and backtracking techniques in order to determine the assignment of workers to tasks.

Improving accuracy of road projects’ estimates in the Ghanaian construction industry

PurposeThe inaccuracy of preliminary estimates sometimes results in wasted development effort if the project is abandoned. To curb this menace, this study aims to assess the different measures to improve the accuracy of road project estimates.Design/methodology/approachQuantitative research design was used for this study, and questionnaire was designed to retrieve data from the target population. Engineers and quantity surveyors in Accra, Ghana formed the target population and were contacted by using an e-questionnaire through their professional bodies owing to location constraints. Descriptive and exploratory factor analyses were used in analysing the retrieved data. Mann–Whitney U non-parametric test was also used to compare the opinions of the respondents.FindingsThe study revealed that factors categorised as due diligence by estimator should be given more attention for accuracy of estimates to be improved.Research limitations/implicationsThis study was limited to Accra, Ghana owing to time and distance constraint.Practical implicationsProper consideration must be given to preliminary site investigation when preparing the estimates for road projects. This will provide the estimator with information on the physical features of the project environment.Originality/valueDefined clusters of measures to improve estimate accuracy as highlighted in this study rather than merely ranked variables which are done by previous research studies will set the tone and provide insights for effective stakeholders’ actions. The study also bridges the gap between theory and practice by outlining how the findings can be implemented practically to achieve more accurate preliminary estimate for road projects. With efforts aligned with the core characteristics of each cluster, accuracy can be improved.

Multiple gateway placement in large‐scale constellation networks with inter‐satellite links

SummaryMultiple gateways are required in large satellite constellation networks (LSCNs) with inter‐satellite links (ISLs), and their placement may greatly affect the system performance. Gateway placement can be optimized to achieve better network performance under the non‐uniform ground demand distribution. This paper formulates a gateway placement optimization model for LSCN with ISLs, aiming at achieving an optimal overall performance including delay, traffic peak, and load balance. The constraints of potential gateway location, gateway‐satellite connectivity, and max hop‐count are considered. A genetic algorithm (GA)‐based method is proposed to solve the integer optimization problem with the help of quasi‐evenly distributed reference layout. A Starlink‐like constellation with ISLs is adopted in the simulation. The simulation results show that the optimized layout has better performance than the reference layout. Additionally, the locations with high user demand or at the middle of ocean are preferred by gateways. The network performance is jointly influenced by gateway placement, demand distribution, constellation configuration, node, and link capacities. The abnormally high ISL hop‐count is found in the south Indian Ocean, which is caused by constellation and ISL configuration.

A Reliability-aware 5G Network Slice Reconfiguration and Embedding Algorithm

Considering the problems of low resource utilization and poor reliability of traditional network slice embedding, a Reliability-aware Network Slice (NS) Reconfiguration and Embedding (RNSRE) strategy is proposed. Firstly, a utility function of reliable embedding oriented reliability and available resources is established. Then, considering the resource requirements and the location constraints of Virtual Network Function (VNF), a method is proposed to quantify the reliability requirement of VNF. Based on the above works, the reliable network slice embedding problem is formulated as an integer linear programming which maximizes the profits of reliable VNF deployment while minimizing the consumption of link bandwidth resource. Finally, according to different types of network slices, a network slice reliable embedding algorithm based on neighborhood search and a network slice reconfiguration embedding algorithm based on key VNF backup are proposed. Simulation results show that the proposed algorithms improve the resources utilization and reduce the embedding cost while meeting the reliability of VNF.

Accuracy of road construction preliminary estimate: examining the influencing factors

PurposePreparation of preliminary estimate is difficult owing to the lack of full project details in the early phases of the construction project. This paper seeks to assess the estimation techniques used for road projects and the critical factors affecting their accuracy in the Ghanaian construction industry.Design/methodology/approachQuantitative research design was adopted and questionnaire was designed to retrieve data. The target population were engineers and quantity surveyors who were contacted using an e-questionnaire through their professional bodies owing to location constraints. Retrieved data were analysed using descriptive and exploratory factor analysis. In order to compare the opinions of the respondents, the Mann–Whitney U-test was employed.FindingsThe survey revealed that subjective, parametric, comparative and analytical estimations are in use in Ghana. The most critical factors influencing the accuracy of estimation techniques are improper project planning, insufficient preliminary site investigation and usage of shortcuts, among others.Research limitations/implicationsThis study was limited to Accra, Ghana, due to time and distance constraint.Practical implicationsFor accuracy of preliminary estimates to be improved, estimators being the custodian of the estimate are expected to be devoid of errors such as arithmetic calculation errors, inaccurate quantity measurement and error of omission. The usage of estimating software can eliminate these human errors.Originality/valueThe study will assist policymakers and stakeholders in aligning mitigative actions for factors influencing preliminary estimate of road projects with defined clusters rather than basic ranks. With attention focussed on the characteristics of each cluster, accuracy of preliminary estimate can be improved.

A review on non-terrestrial wireless technologies for Smart City Internet of Things

Smart City Internet of Things will become a fundamental infrastructure to support massive machine-type communications between the widely deployed sensors serving big cities. Since there exists many location constraints for the existing terrestrial Internet of Things, the non-terrestrial Internet of Things sheds light on breaking these limits. Therefore, this article conducts a comprehensive survey on non-terrestrial Internet of Things technologies for Smart City, which is an important complement to terrestrial Internet of Things. We first present the application scenarios of Internet of Things and point out where the existing terrestrial Internet of Things cannot work perfectly. Two non-terrestrial Internet of Things technical proposals are then introduced, namely satellite Internet of Things and unmanned aerial vehicle Internet of Things. However, the focuses of these non-terrestrial Internet of Things are distinct, that is, the major problems of satellite and unmanned aerial vehicle Internet of Things are the high dynamic nature of channel and high maneuverability of unmanned aerial vehicles, respectively. The key technologies for satellite and unmanned aerial vehicle Internet of Things are then reviewed separately. Both physical and non-physical layer technologies are surveyed for satellite Internet of Things, and the route planning is mainly investigated for the unmanned aerial vehicle Internet of Things. Finally, we draw a conclusion and give some potential research directions of non-terrestrial Internet of Things.

Discrete-time robust fuzzy control synthesis for discretized and perturbed ship fin stabilizing systems subject to variance and pole location constraints

A discrete-time robust fuzzy controller design problem for the discretized and perturbed nonlinear ship fin stabilizing systems is studied in this paper. The discrete-time Takagi–Sugeno fuzzy model is used to represent the nonlinear ship fin stabilizing systems. The control performance considered in this paper includes stability requirement, pole location constraint, individual state variance constraint, and minimum output variance. Applying the Lyapunov theory, a discrete-time robust fuzzy controller is designed based on parallel distributed compensation technology and the relevant conditions are deduced in the form of linear matrix inequalities. By solving these conditions, a discrete-time robust fuzzy controller can be obtained to satisfy the above performance constraints. At last, a simulation for controlling a discrete-time nonlinear ship fin stabilizing system is provided to show the feasibility and applicability of the proposed robust fuzzy control method.

Robust fuzzy control for nonlinear discrete-time systems with internal and external noises subject to multi-variance constraints and pole location constraints

Robust fuzzy control for nonlinear discrete-time systems with internal and external noises subject to multi-variance constraints and pole location constraints

The Effect of the Intensity of Telework Use on Employees’ Work-Life Balance

The intensive penetration of information and communication technologies into the labour market has also determined the modernisation of work organization processes. The digitization of information and telecommunications enabled to perform most of intellectual activities not only in the work premises but also in other spaces distant from the main workplace. Thus, as the technology revolution gradually releases modern intellectual work from the constraints of the physical location, telework is becoming an increasingly accelerating trend in the world. Together with technological changes allowing to reach the employee 24 hours a day and 7 days a week create challenges for teleworkers seeking to successfully reconcile two areas of life – work and personal life. Employees from different fields, among them accounting, audit, finances, analysis and others that carry out tasks via telework face this challenge.Relevance of the scientific research problem formulated in this paper was determined by the lack of studies in the scientific research to date, which would evaluate the intensity of telework use as an important factor that has a different effect on work-life balance.The research aim is to reveal the effect of the intensity of telework use on employee work-life balance. A quantitative study – the survey of telework employees was conducted and 320 respondents were surveyed. The results of the empirical study revealed that the intensity of telework use had equally positive effect only on two dimensions of work-life balance: time intended for the family and friends and time intended for oneself.

Planning PEV Fast-Charging Stations Using Data-Driven Distributionally Robust Optimization Approach Based on ϕ-Divergence

Plug-in electric vehicles are widely acknowledged as an effective tool for numerous environmental and economic concerns. In this article, a novel model for the planning of fast-charging stations is established based on a data-driven distributionally robust optimization approach, which aims to minimize the expected planning cost for both transportation network and distribution network. φ-divergence, a statistical measure, is utilized to establish the serviceability constraints. On the other hand, a modified capacitated flow refueling location model is employed to develop the location constraints. In addition, ac power flow constraints are developed to model the operation of DN with the penetrations of PEVs. Finally, a case study is illustrated to validate the proposed planning model.

User experience-driven secure task assignment in spatial crowdsourcing

With the ubiquity of mobile devices and wireless networks, Spatial Crowdsourcing (SC) has earned considerable importance and attention as a new strategy of problem-solving. Tasks in SC have location constraints and workers need to move to certain locations to perform them. Current studies mainly focus on maximizing the benefits of the SC platform. However, user average waiting time, which is an important indicator of user experience, has been overlooked. To enhance user experience, the SC platform needs to collect lots of data from both workers and users. During this process, the private information may be compromised if the platform is not trustworthy. In this paper, we first define user experience-driven secure task assignment problem and propose two privacy-preserving online task assignment strategies to minimize the average waiting time. We securely construct an encrypted bipartite graph to protect private data. Based on this encrypted graph, we propose a secure Kuhn-Munkres algorithm to realize task assignment without privacy disclosure. Theoretical analysis shows the security of our approach and experimental results demonstrates its efficiency and effectiveness.

Comments on “Secure Data Sharing in Cloud Computing Using Revocable-Storage Identity-Based Encryption”

Cloud computing can provide a flexible way to effectively share data among multiple users since it can overcome the time and location constraints of computing resource usage. However, the users of cloud computing are still reluctant to share sensitive data to a cloud server since the cloud server should be treated as an untrusted entity. In order to support secure and efficient data sharing in a cloud computing environment, Wei et al. recently extended the concept of identity-based encryption (IBE) to support key revocation and ciphertext update functionalities, and proposed a revocable-storage identity-based encryption (RS-IBE) scheme. In this article, we show that the RS-IBE scheme of Wei et al. does not satisfy the correctness property of RS-IBE. We also propose a method to modify the existing RS-IBE scheme.