MOEA/D Using Dynamic Weight Vectors and Stable Matching Schemes for the Deployment of Multiple Airships in the Earth Observing System

Xu, Zhouwu; Jing, Liu; Qiao, Baihao; Cao, Yating

doi:10.1109/cec45853.2021.9504918

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…Similarly, the same group carried out a further study [14], in which the authors proposed an energy-aware optimization strategy that optimizes task benefits and energy consumption simultaneously. A recent study conducted by Xu et al [27] developed a decompositionbased multi-objective optimization algorithm using dynamic weight vectors and stable matching schemes to address the deployment problem of airships. Several studies also consider the observation scheduling of airships coordinated with other observation platforms.…”

Section: Related Workmentioning

confidence: 99%

An Observation Scheduling Approach Based on Task Clustering for High-Altitude Airship

Chen

Luo

2022

Sensors

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Airship-based Earth observation is of great significance in many fields such as disaster rescue and environment monitoring. To facilitate efficient observation of high-altitude airships (HAA), a high-quality observation scheduling approach is crucial. This paper considers the scheduling of the imaging sensor and proposes a hierarchical observation scheduling approach based on task clustering (SA-TC). The original observation scheduling problem of HAA is transformed into three sub-problems (i.e., task clustering, sensor scheduling, and cruise path planning) and these sub-problems are respectively solved by three stages of the proposed SA-TC. Specifically, a novel heuristic algorithm integrating an improved ant colony optimization and the backtracking strategy is proposed to address the task clustering problem. The 2-opt local search is embedded into a heuristic algorithm to solve the sensor scheduling problem and the improved ant colony optimization is also implemented to solve the cruise path planning problem. Finally, extensive simulation experiments are conducted to verify the superiority of the proposed approach. Besides, the performance of the three algorithms for solving the three sub-problems are further analyzed on instances with different scales.

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Section: Related Workmentioning

confidence: 99%

An Observation Scheduling Approach Based on Task Clustering for High-Altitude Airship

Chen

Luo

2022

Sensors

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“…The EAs are stochastic search algorithms that deal with discontinuous or multimodal functions. The Xu et al 24 designed a multiobjective model for the deployment problem of multiple airships in the earth observing system, considering the number of covered tasks and the total profits of the observable tasks. Jing et al 25 proposed an Earth‐observation model with considerations of loading devices side‐swing characteristics field of view and established a collaborative deployment model of Multi‐airship Earth‐observation Coverage Network to realize objectives of observation coverage, target point statistics, observation resolution, multi‐airship community profit.…”

Section: Introductionmentioning

confidence: 99%

Optimal deployment strategy of airships for near‐space communication system using multiobjective advanced evolutionary algorithm

Alam,

Mondal

2023

Int J Communication

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SummaryThis paper presents a near‐space communication system (NSCS) using advanced deployment strategies to gain high throughput. The airships are deployed according to the user's location, assuming robust backbone network characteristics such as signal path loss, fading factor, routing efficiency, and safety issues among bi‐connected airships. Due to the independent flying nature of airships, it is very attractive to deploy them as aerial base stations and construct airborne networks to provide service for on‐ground users. However, it is quite challenging to optimally deploy multiple airships for on‐demand coverage while maintaining the connectivity among airships. A balance between the network parameters, i.e., capacity and coverage area, should be maintained for optimal deployment of the airships. We have derived the maximum throughput of NSCS, including system parameters, as a multiobjective optimization problem subjected to efficient routing protocol and safety constraints. A decomposition‐based advanced multiobjective evolutionary algorithm (AMOEA/D) is adopted to solve the deployment optimization problem. The proposed algorithm is motivated by the non‐dominated solutions that maintain population diversity over the variable space. Two designed test problems, that is, the L‐shaped hotspot problem and nine hotspot problems, are also investigated. Numerical results show that the proposed method improves the system performance compared with benchmark external archive‐guided MOEA/D (EGA‐MOEA/D) and non‐dominated sorted genetic algorithms (NSGA‐II) by 10.46% and 3.84%, respectively.

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Multi-objective economic emission dispatch of thermal power-electric vehicles considering user’s revenue

2022

Self Cite

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In recent years, the rapid development of electric vehicles has increased the load power system and brought new challenges to the safe and stable operation of the gird. Although the vehicle-to-grid technology can reduce the load that electric vehicles put on the grid, without any incentives, electric vehicle owners are more inclined not to use vehicle-to-grid services. In this paper, therefore, a new dynamic economic emission model based on electric vehicles (DEED_EV) is proposed to maximize the electric vehicle user’s revenue, as well as minimize the fuel cost and emission of the thermal power unit. In the DEED_EV model, the stochastic of electric vehicles user’s travel and wear of the battery, as well as some constraints such as electric vehicles charging/discharging rate and status, electric vehicles remain power, electric vehicles travel power capacity, ramp limits, up and down reserves, and the system balance are considered. To solve the DEED_EV model, a multi-objective evolutionary algorithm based on decomposition with a step-by-step constraint handling strategy is developed. Different test cases based on the 10-unit are simulated to verify the proposed model and method. The results show that the DEED_EV model not only encourages more electric vehicles to plug into the grid but also reduces the fuel cost and emission of the thermal power unit. Besides, the electric vehicles in the DEED_EV completely realizes the peak shaving and valley filling of the load.

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MOEA/D Using Dynamic Weight Vectors and Stable Matching Schemes for the Deployment of Multiple Airships in the Earth Observing System

Cited by 6 publications

References 28 publications

An Observation Scheduling Approach Based on Task Clustering for High-Altitude Airship

An Observation Scheduling Approach Based on Task Clustering for High-Altitude Airship

Optimal deployment strategy of airships for near‐space communication system using multiobjective advanced evolutionary algorithm

Multi-objective economic emission dispatch of thermal power-electric vehicles considering user’s revenue

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