Optimized Cost-Effective Node Deployments in Asynchronous Time Local Positioning Systems

Díez-González, Javier; Álvarez, Rubén; Pérez, Hilde

doi:10.1109/access.2020.3018624

Cited by 16 publications

(7 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is also the case for the TLP. The firefly algorithm [47], the grey wolf optimiser [48], GA [49,50], simulated annealing [51], the elephant herding optimisation [52], cuckoo search [53] or MA [45,54,55] have been proposed for the NLP.…”

Section: State-of-the-art Methodologies For the Tlpmentioning

confidence: 99%

Optimal COVID-19 Adapted Table Disposition in Hostelry for Guaranteeing the Social Distance through Memetic Algorithms

et al. 2021

Self Cite

View full text Add to dashboard Cite

The COVID-19 pandemic has challenged all physical interactions. Social distancing, face masks and other rules have reshaped our way of living during the last year. The impact of these measures for indoor establishments, such as education or hostelry businesses, resulted in a considerable organisation problem. Achieving a table distribution inside these indoor spaces that fulfilled the distancing requirements while trying to allocate the maximum number of tables for enduring the pandemic has proved to be a considerable task for multiple establishments. This problem, defined as the Table Location Problem (TLP), is categorised as NP-Hard, thus a metaheuristic resolution is recommended. In our previous works, a Genetic Algorithm (GA) optimisation was proposed for optimising the table distribution in real classrooms. However, the proposed algorithm performed poorly for high obstacle density scenarios, especially when allocating a considerable number of tables due to the existing dependency between adjacent tables in the distance distribution. Therefore, in this paper, we introduce for the first time, to the authors’ best knowledge, a Memetic Algorithm (MA) optimisation that improves the previously designed GA through the introduction of a Gradient Based Local Search. Multiple configurations have been analysed for a real hostelry-related scenario and a comparison between methodologies has been performed. Results show that the proposed MA optimisation obtained adequate solutions that the GA was unable to reach, demonstrating a superior convergence performance and an overall greater flexibility. The MA performance denoted its value not only from a COVID-19 distancing perspective but also as a flexible managing algorithm for daily table arrangement, thus fulfilling the main objectives of this paper.

show abstract

Section: State-of-the-art Methodologies For the Tlpmentioning

confidence: 99%

Optimal COVID-19 Adapted Table Disposition in Hostelry for Guaranteeing the Social Distance through Memetic Algorithms

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…Each one of these considerations makes the TLP factorial in complexity [31] and very similar to the technological NLP, which has been assigned as NP-Hard [22,23]. As a consequence, the finding of an optimal solution for the TLP recommends a heuristic approach similarly to the NLP and can also be categorized as NP-Hard.…”

Section: Analysis and Complexity Studies On The Table Location Problemmentioning

confidence: 99%

Table Organization Optimization in Schools for Preserving the Social Distance during the COVID-19 Pandemic

et al. 2020

Self Cite

View full text Add to dashboard Cite

The COVID-19 pandemic has supposed a challenge for education. The school closures during the initial coronavirus outbreak for reducing the infections have promoted negative effects on children, such as the interruption of their normal social relationships or their necessary physical activity. Thus, most of the countries worldwide have considered as a priority the reopening of schools but imposing some rules for keeping safe places for the school lessons such as social distancing, wearing facemasks, hydroalcoholic gels or reducing the capacity in the indoor rooms. In Spain, the government has fixed a minimum distance of 1.5 m among the students’ desks for preserving the social distancing and schools have followed orthogonal and triangular mesh patterns for achieving valid table dispositions that meet the requirements. However, these patterns may not attain the best results for maximizing the distances among the tables. Therefore, in this paper, we introduce for the first time in the authors’ best knowledge a Genetic Algorithm (GA) for optimizing the disposition of the tables at schools during the coronavirus pandemic. We apply this GA in two real-application scenarios in which we find table dispositions that increase the distances among the tables by 19.33% and 10%, respectively, with regards to regular government patterns in these classrooms, thus fulfilling the main objectives of the paper.

show abstract

“…Among LPS, those based on temporal measurements have the best trade-off among accuracy, stability, robustness, easy-to-implement hardware architectures and costs [ 19 ]. Time-Based Positioning architectures are divided considering three main categories depending on the time lapses computed to determine the target location: Time of Arrival (TOA) systems [ 20 ], Time Difference of Arrival (TDOA) systems [ 21 ], and Asynchronous Time Difference of Arrival (A-TDOA) [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

“…TDOA architecture allows the independence from the emission timestamp of the positioning signal thus reducing the synchronization errors of the TOA architecture and with a reduction in the signal path noise cumulated during the transmission with regards to the A-TDOA architecture which is particularly relevant in complex urban scenarios. Besides, the consideration of all the architecture sensors as coordinator sensors in the TDOA synchronous architecture makes the system more versatile and less dependent on particular sensors of the architecture compromising the system availability in failure cases or partial bad connections with the coordinator sensor of the A-TDOA architecture [ 19 , 29 ].…”

Section: Introductionmentioning

confidence: 99%

Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios

Verde

Díez-González

Ferrero-Guillén

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

Local Positioning Systems (LPS) have become an active field of research in the last few years. Their application in harsh environments for high-demanded accuracy applications is allowing the development of technological activities such as autonomous navigation, indoor localization, or low-level flights in restricted environments. LPS consists of ad-hoc deployments of sensors which meets the design requirements of each activity. Among LPS, those based on temporal measurements are attracting higher interest due to their trade-off among accuracy, robustness, availability, and costs. The Time Difference of Arrival (TDOA) is extended in the literature for LPS applications and consequently we perform, in this paper, an analysis of the optimal sensor deployment of this architecture for achieving practical results. This is known as the Node Location Problem (NLP) and has been categorized as NP-Hard. Therefore, heuristic solutions such as Genetic Algorithms (GA) or Memetic Algorithms (MA) have been applied in the literature for the NLP. In this paper, we introduce an adaptation of the so-called MA-Solis Wets-Chains (MA-SW-Chains) for its application in the large-scale discrete discontinuous optimization of the NLP in urban scenarios. Our proposed algorithm MA-Variable Neighborhood Descent-Chains (MA-VND-Chains) outperforms the GA and the MA of previous proposals for the NLP, improving the accuracy achieved by 17% and by 10% respectively for the TDOA architecture in the urban scenario introduced.

show abstract

Optimized Cost-Effective Node Deployments in Asynchronous Time Local Positioning Systems

Cited by 16 publications

References 46 publications

Optimal COVID-19 Adapted Table Disposition in Hostelry for Guaranteeing the Social Distance through Memetic Algorithms

Optimal COVID-19 Adapted Table Disposition in Hostelry for Guaranteeing the Social Distance through Memetic Algorithms

Table Organization Optimization in Schools for Preserving the Social Distance during the COVID-19 Pandemic

Memetic Chains for Improving the Local Wireless Sensor Networks Localization in Urban Scenarios

Contact Info

Product

Resources

About