A Novel Design of Sharp MDFT Filter Banks with Low Complexity Based on DPSO-MFO Algorithm

Yang, Yan; Xu, Pingping

doi:10.1007/978-3-319-49568-2_60

Cited by 1 publication

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“…Qi [20] proposes an improved DPSO algorithm by combing the iterated local search. Yang and Xu [21] propose DPSO-MFO algorithm, which is able to provide excellent performances as a natureinspired heuristic algorithm. e methods mentioned above improve the performance of DPSO by enhancing the exploration and exploitation abilities, but the balance of exploration and exploitation is not controlled.…”

Section: Introductionmentioning

confidence: 99%

Fuel-Efficient on-Orbit Service Vehicle Allocation Based on an Improved Discrete Particle Swarm Optimization Algorithm

Liu

et al. 2020

Mathematical Problems in Engineering

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Given the limited fuel capacity of an on-orbit service vehicle (OSV), proper OSV allocation to satellites during each service mission is critical for economic fuel consumption. This allocation problem can be formulated as an optimization problem with many continuous and discrete design variables of wide domains. This problem can be effectively handled through the proposed approach that combines the tabu search with the discrete particle swarm optimization algorithm (DPSO-TS). First of all, Pontryagin’s minimum principle and genetic algorithm (GA) are exploited to find the most fuel-efficient transfer trajectory. This fuel efficiency maximization can then serve as the performance index of the OSV allocation optimization model problem. In particular, the maximization of the minimum residual fuel over individual OSVs is proposed as a performance index for OSV allocation optimization. The optimization problem is numerically solved through the proposed DPSO-TS algorithm. Finally, the simulation results demonstrate that the DPSO-TS algorithm has a higher accuracy compared to the DPSO, the DPSO-PDM and the DPSO-CSA algorithms in the premise that these four algorithms have the basically same computational time. The DPSO-TS algorithm can effectively solve the OSV allocation optimization problem.

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Section: Introductionmentioning

confidence: 99%

Fuel-Efficient on-Orbit Service Vehicle Allocation Based on an Improved Discrete Particle Swarm Optimization Algorithm

Liu

et al. 2020

Mathematical Problems in Engineering

View full text Add to dashboard Cite

show abstract

A Novel Design of Sharp MDFT Filter Banks with Low Complexity Based on DPSO-MFO Algorithm

Cited by 1 publication

References 5 publications

Fuel-Efficient on-Orbit Service Vehicle Allocation Based on an Improved Discrete Particle Swarm Optimization Algorithm

Fuel-Efficient on-Orbit Service Vehicle Allocation Based on an Improved Discrete Particle Swarm Optimization Algorithm

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