A progressive hybrid set covering based algorithm for the traffic counting location problem

Vieira, Bruno Salezze; Ferrari, Thayse; Ribeiro, Glaydston Mattos; Bahiense, Laura; Filho, Rômulo Dante Orrico; Abramides, Carlos Alberto; Júnior, Nilo Flavio Rosa Campos

doi:10.1016/j.eswa.2020.113641

Cited by 8 publications

(5 citation statements)

References 22 publications

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“…In order to achieve the purpose of monitoring key areas, it is necessary to further refine the monitoring areas, calculate the importance of the refined areas according to the scientific quantitative model of the importance ranking of chemical hazard monitoring areas, and select the most important areas in the monitoring area to cover the monitoring points and choose the site of the monitoring points, so as to efficiently and accurately detect the gas leakage information of the chemical hazard area. Coverage location problems [29] include location set covering problem (LSCP) [30][31][32][33][34] and maximum coverage location problem (MCLP) [35,36]. Among them, LSCP is committed to establishing the fewest site selection points to cover all demand points under the premise of covering the specified requirements, and transforming the location problem into a problem of minimizing the number of required site selection points.…”

Section: Related Workmentioning

confidence: 99%

A Study on the Deployment of Mesoscale Chemical Hazard Area Monitoring Points by Combining Weighting and Fireworks Algorithms

Shi¹,

Zhang²,

Chen³

et al. 2023

Sustainability

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In order to address the problems of redundancy and waste of resources in the deployment of monitoring points in mesoscale chemical hazard areas, we propose a method for the deployment of monitoring points in mesoscale chemical hazard areas by combining weight and fireworks algorithms. Taking the mesoscale chemical hazard monitoring area as the research background, we take the probabilistic sensing model of telemetry sensor nodes as the research object, make a reasonable grid division of the mesoscale monitoring area, calculate the importance of each grid and perform clustering, utilize the diversity of the fireworks algorithm and the rapidity of the solution to solve the monitoring point deployment model and discuss the relevant factors affecting the deployment scheme. The simulation results show that the proposed algorithm can achieve the optimal coverage monitoring for monitoring areas with different importance and reduce the number of monitoring nodes and redundancy; meanwhile, the relevant factors such as the grid edge length, the number of clusters, and the average importance of monitoring areas have different degrees of influence on the complexity of the algorithm and the deployment scheme.

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Section: Related Workmentioning

confidence: 99%

A Study on the Deployment of Mesoscale Chemical Hazard Area Monitoring Points by Combining Weighting and Fireworks Algorithms

Shi¹,

Zhang²,

Chen³

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…The SCP allows the modeling of real-life optimization problems such as the location of gas detectors for industrial plants [24], the location of electric vehicle charging points in California [25], the optimal UAV locations for the purpose of generating wireless communication networks in disaster areas [26], the optimal location of first aid centers in Japan [27] and the location of stations to cover a network of reels [28]. These studies allow us to appreciate the importance of solving this problem with optimization techniques that guarantee good results.…”

Section: Set Covering Problemmentioning

confidence: 99%

Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems

et al. 2022

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When we face real problems using computational resources, we understand that it is common to find combinatorial problems in binary domains. Moreover, we have to take into account a large number of possible candidate solutions, since these can be numerous and make it complicated for classical algorithmic techniques to address them. When this happens, in most cases, it becomes a problem due to the high resource cost they generate, so it is of utmost importance to solve these problems efficiently. To cope with this problem, we can apply other methods, such as metaheuristics. There are some metaheuristics that allow operation in discrete search spaces; however, in the case of continuous swarm intelligence metaheuristics, it is necessary to adapt them to operate in discrete domains. To perform this adaptation, it is necessary to use a binary scheme to take advantage of the original moves of the metaheuristics designed for continuous problems. In this work, we propose to hybridize the whale optimization algorithm metaheuristic with the Q-learning reinforcement learning technique, which we call (the QBWOA). By using this technique, we are able to realize an smart and fully online binarization scheme selector, the results have been statistically promising thanks to the respective tables and graphs.

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“…To optimize the location of the three levels of maternity hospitals found in France, Baray and Cliquet [35] provide a hierarchical location-allocation model that combines a maximum covering model and p-center models. Based on the set covering model, Vieira, Ferrari, and Ribeiro, et al [36] determined the appropriate number and position of counting stations to cover a road network to obtain traffic flows. A variety of calculating methods and algorithms have been developed to solve the models mentioned above.…”

Section: Related Workmentioning

confidence: 99%

Location Optimization of VTS Radar Stations Considering Environmental Occlusion and Radar Attenuation

Huang

2022

IJGI

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Waterway traffic monitoring is an important content in waterway traffic management. Taking into account that the number of monitored water areas is growing and that waterway traffic management capabilities are insufficient in the current situation in China, this paper investigates the location optimization of the vessel traffic service (VTS) radar station. During the research process, radar attenuation and environmental occlusion, as well as variable coverage radius and multiple covering are all considered. In terms of the radar attenuation phenomenon in the propagation process and obstacles such as mountains and islands in the real world, judgment and evaluation methods in a three-dimensional space are proposed. Moreover, a bi-objective mathematical model is then developed, as well as a modified adaptive strategy particle swarm optimization algorithm. Finally, a numerical example and a case are given to verify the effectiveness of the proposed methods, model, and algorithm. The results show the methods, model, and algorithm proposed in this paper can solve the model efficiently and provide a method to optimize the VTS radar station location in practice.

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A progressive hybrid set covering based algorithm for the traffic counting location problem

Cited by 8 publications

References 22 publications

A Study on the Deployment of Mesoscale Chemical Hazard Area Monitoring Points by Combining Weighting and Fireworks Algorithms

A Study on the Deployment of Mesoscale Chemical Hazard Area Monitoring Points by Combining Weighting and Fireworks Algorithms

Embedded Learning Approaches in the Whale Optimizer to Solve Coverage Combinatorial Problems

Location Optimization of VTS Radar Stations Considering Environmental Occlusion and Radar Attenuation

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