Design and verification of a transfer path optimization method for an aircraft on the aircraft carrier flight deck

2021 ◽  
Vol 22 (9) ◽  
pp. 1221-1233
Author(s):  
Weichao Si ◽  
Tao Sun ◽  
Chao Song ◽  
Jie Zhang
Keyword(s):  
Optimization Method ◽  
Path Optimization ◽  
Aircraft Carrier ◽  
Transfer Path ◽  
Flight Deck

scholarly journals A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-38 ◽  
Author(s):  
Xichao Su ◽  
Wei Han ◽  
Yu Wu ◽  
Yong Zhang ◽  
Jie Liu
Keyword(s):  
Resource Allocation ◽  
Resource Constraints ◽  
Learning Automata ◽  
Optimization Method ◽  
Neighborhood Search ◽  
Aircraft Carrier ◽  
Robust Scheduling ◽  
Baseline Schedule ◽  
Teaching Learning ◽  
Flight Deck

The operations on the aircraft carrier flight deck are carried out in a time-critical and resource-constrained environment with uncertainty, and it is of great significance to optimize the makespan and obtain a robust schedule and resource allocation plan for a greater sortie generation capacity and better operational management of an aircraft carrier. In this paper, a proactive robust optimization method for flight deck scheduling with stochastic operation durations is proposed. Firstly, an operation on node-flow (OONF) network is adopted to model the precedence relationships of multi-aircraft operations, and resource constraints categorized into personnel, support equipment, workstation space, and supply resource are taken into consideration. On this basis, a mathematical model of the robust scheduling problem for flight deck operation (RSPFDO) is established, and the goal is to maximize the probability of completing within the limitative makespan (PCLM) and minimize the weighted sum of expected makespan and variance of makespan (IRM). Then, in terms of proactive planning, both serial and parallel schedule generation schemes for baseline schedule and robust personnel allocation scheme and equipment allocation adjustment scheme for resource allocation are designed. In terms of executing schedules, an RSPFDO-oriented preconstraint scheduling policy (CPC) is proposed. To optimize the baseline schedule and resource allocation, a hybrid teaching-learning-based optimization (HTLBO) algorithm is designed which integrates differential evolution operators, peak crossover operator, and learning-automata-based adaptive variable neighborhood search strategy. Simulation results shows that the HTLBO algorithm outperforms both some other state-of-the-art algorithms for deterministic cases and some existing algorithms for stochastic project scheduling, and the robustness of the flight deck operations can be improved with the proposed resource allocation schemes and CPC policy.

Cable-path optimization method for industrial robot arms

2022 ◽  
Vol 73 ◽  
pp. 102245
Author(s):  
Shintaro Iwamura ◽  
Yoshiki Mizukami ◽  
Takahiro Endo ◽  
Fumitoshi Matsuno
Keyword(s):  
Industrial Robot ◽  
Optimization Method ◽  
Path Optimization ◽  
Robot Arms

scholarly journals An Extended Flexible Job Shop Scheduling Model for Flight Deck Scheduling with Priority, Parallel Operations, and Sequence Flexibility

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Lianfei Yu ◽  
Cheng Zhu ◽  
Jianmai Shi ◽  
Weiming Zhang
Keyword(s):  
Differential Evolution ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Time Budget ◽  
Differential Evolution Algorithm ◽  
Mixed Integer ◽  
Aircraft Carrier ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Flight Deck

Efficient scheduling for the supporting operations of aircrafts in flight deck is critical to the aircraft carrier, and even several seconds’ improvement may lead to totally converse outcome of a battle. In the paper, we ameliorate the supporting operations of carrier-based aircrafts and investigate three simultaneous operation relationships during the supporting process, including precedence constraints, parallel operations, and sequence flexibility. Furthermore, multifunctional aircrafts have to take off synergistically and participate in a combat cooperatively. However, their takeoff order must be restrictively prioritized during the scheduling period accorded by certain operational regulations. To efficiently prioritize the takeoff order while minimizing the total time budget on the whole takeoff duration, we propose a novel mixed integer liner programming formulation (MILP) for the flight deck scheduling problem. Motivated by the hardness of MILP, we design an improved differential evolution algorithm combined with typical local search strategies to improve computational efficiency. We numerically compare the performance of our algorithm with the classical genetic algorithm and normal differential evolution algorithm and the results show that our algorithm obtains better scheduling schemes that can meet both the operational relations and the takeoff priority requirements.

scholarly journals Toward solving the sign problem with path optimization method

2017 ◽  
Vol 96 (11) ◽  
Author(s):  
Yuto Mori ◽  
Kouji Kashiwa ◽  
Akira Ohnishi
Keyword(s):  
Optimization Method ◽  
Path Optimization ◽  
Sign Problem

Flight Deck Design of the Next Generation Aircraft Carrier

2000 ◽  
Vol 112 (3) ◽  
pp. 69-75 ◽  
Author(s):  
W. Baker ◽  
S. D. Brennan ◽  
M. Husni
Keyword(s):  
Next Generation ◽  
Aircraft Carrier ◽  
Flight Deck Design ◽  
Flight Deck

A general trajectory optimization method for aircraft taxiing on flight deck of carrier

2018 ◽  
Vol 233 (4) ◽  
pp. 1340-1353 ◽  
Author(s):  
Yu Wu ◽  
Ning Hu ◽  
Xiangju Qu
Keyword(s):  
Optimization Algorithm ◽  
Trajectory Optimization ◽  
Fitness Function ◽  
Control Variable ◽  
Optimization Method ◽  
Operation Efficiency ◽  
Ground Motion Model ◽  
Aircraft System ◽  
Chicken Swarm Optimization ◽  
Flight Deck

Enhancing operation efficiency of flight deck has become a hotspot because it has an important impact on the fighting capacity of the carrier–aircraft system. To improve the operation efficiency, aircraft need taxi to the destination on deck with the optimal trajectory. In this paper, a general method is proposed to solve the trajectory optimization problem for aircraft taxiing on flight deck considering that the existing methods can only deal with the problem in some specific cases. Firstly, the ground motion model of aircraft, the collision detection strategy and the constraints are included in the mathematical model. Then the principles of the chicken swarm optimization algorithm and the generality of the proposed method are explained. In the trajectory optimization algorithm, several strategies, i.e. generation of collocation points, transformation of control variable, and setting of segmented fitness function, are developed to meet the terminal constraints easier and make the search efficient. Three groups of experiments with different environments are conducted. Aircraft with different initial states can reach the targets with the minimum taxiing time, and the taxiing trajectories meet all the constraints. The reason why the general trajectory optimization method is validated in all kinds of situations is also explained.

scholarly journals Picking Path Optimization of Agaricus bisporus Picking Robot

2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Xiaomei Hu ◽  
Zhaoren Pan ◽  
Shunke Lv
Keyword(s):  
Field Experiments ◽  
Search Algorithm ◽  
Optimal Path ◽  
Temperature Drop ◽  
Optimization Method ◽  
Labor Cost ◽  
Path Optimization ◽  
Parallel Optimization ◽  
Storage Location ◽  
Short Time

The design and application of the mushroom picking robot will greatly reduce the labor cost, and it has become one of the research hotspots in the world. Therefore, we independently developed an A. bisporus (a kind of mushroom) picking robot and introduced its functional principle in this paper. At the same time, in order to improve the picking efficiency of the picking robot, a picking path optimization algorithm based on TSP model is proposed. Firstly, based on the TSP model, a picking route model for A. bisporus was established to determine the storage location of each A. bisporus. Then, an improved simulated annealing (I-SA) search algorithm is proposed to find the optimal path sequence. By improving the path initialization module, path generation module, and temperature drop module, the I-SA search algorithm can optimize the picking path in a short time. Finally, in order to improve the stability and reduce the running time of the I-SA search algorithm, a parallel optimization method for global search (“rough exploration”) and local search (“precision exploration”) is proposed. Through simulation experiments, the I-SA search algorithm can search stable and excellent path solution in a relatively short time. Through field experiments on mushroom base, the efficiency of picking A. bisporus can be improved by 14% to 18%, which verifies the effectiveness of the I-SA search algorithm.

Sign in / Sign up

Export Citation Format

Share Document