scholarly journals MATHEMATICAL MODEL AND OPTIMIZATION ALGORITHM BY MASS FOR TRANSMISSION OF TRACKED LOAD-CARRIER/PRIME MOVER MT-LB

2020 ◽  
Vol 3 (2-2) ◽  
pp. 16-23
Author(s):  
S.V. ANDRIENKO ◽  
O.V. USTYNENKO ◽  
O.V. BONDARENKO ◽  
I.E. KLOCHKOV
Keyword(s):  
Mathematical Model ◽  
Optimization Algorithm ◽  
Prime Mover ◽  
Load Carrier

scholarly journals An Improved Whale Algorithm for Setting Standard Scheduled Block Time Based on the Airline Fairness

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Qian Wang ◽  
Yong Tian ◽  
Lili Lin ◽  
Ratnaji Vanga ◽  
Lina Ma
Keyword(s):  
Mathematical Model ◽  
Mathematical Models ◽  
Optimization Algorithm ◽  
Whale Optimization Algorithm ◽  
Civil Aviation ◽  
Convergence Factor ◽  
Suggested Approach ◽  
Whale Optimization ◽  
Block Time ◽  
Better Than

Standard scheduled flight block time (SBT) setting is of great concern for Civil Aviation Administration of China (CAAC) and airlines in China. However, the standard scheduled flight block times are set in the form of on-site meetings in practice and current literature has not provided any efficient mathematical models to calculate the flight block times fairly among the airlines. The objective of this paper is to develop and solve a mathematical model for standard SBT setting with consideration of both fairness and reliability. We use whale optimization algorithm (WOA) and an improved version of the whale optimization algorithm (IWOA) to solve the SBT setting problem. A novel nonlinear update equation of convergence factor for random iterations is used in place of the original linear one in the proposed IWOA algorithm. Experimental results show that the suggested approach is effective, and IWOA performs better than WOA in the concerned problem, whose solutions are better compared to the flight block times released by CAAC. In particular, it is interesting to find that MSE, RMSE, MAE, MAPE and Theil of the reliability in 60%–70% range are always the smallest and the average fairness of airlines is better than that of 60%–75% range. The model and solving approach presented in this article have great potential to be applied by CAAC to determine the standard SBTs strategically.

Performance Evaluation of Hybrid Photovoltaic Thermal Thermoelectric Collector Using Grasshopper Optimization Algorithm With Simulated Annealing

2020 ◽  
Vol 142 (6) ◽  
Author(s):  
Anmol Gupta ◽  
Sanjay Agrawal ◽  
Yash Pal
Keyword(s):  
Mathematical Model ◽  
Performance Evaluation ◽  
Simulated Annealing ◽  
Optimization Algorithm ◽  
Single Channel ◽  
Electrical Energy ◽  
Average Value ◽  
Grasshopper Optimization Algorithm ◽  
Mass Flowrate ◽  
Grasshopper Optimization

Abstract In this paper, a mathematical model of a single-channel photovoltaic thermal (PVT) air collector incorporated with a thermoelectric (TE) module has been presented. The overall electrical energy obtained from the photovoltaic thermal-thermoelectric (PVT-TE) collector is 5.78% higher than the PVT collector. Further, the grasshopper optimization algorithm (GOA) and hybrid grasshopper optimization algorithm with simulated annealing (GOA-SA) have been proposed and implemented to optimize the parameters of opaque PVT-TE collector. Although there are different parameters that influence the performance of PVT-TE system, yet in this study only four parameters, viz., length of the channel (L), width of the channel (b), mass flowrate of air in the channel (mair), and temperature of air at the inlet of channel (Tair,i) are considered for optimization. The simulation result demonstrates that the hybrid GOA-SA algorithm turned out to be an exceptionally effective method for optimal tuning of the parameters of the PVT-TE system. The result explicitly shows that the average value of overall electrical efficiency and exergy gain are 15.27% and 27.0565 W, respectively, when the parameters are optimized by the suggested GOA-SA algorithm which is way ahead with respect to the outcomes obtained with that of the calculated values or using GOA algorithm alone.

scholarly journals Solving the Traveling Salesman’s Problem Using the African Buffalo Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-12 ◽  
Author(s):  
Julius Beneoluchi Odili ◽  
Mohd Nizam Mohmad Kahar
Keyword(s):  
Mathematical Model ◽  
Optimization Algorithm ◽  
Search Space ◽  
Metaheuristic Algorithm ◽  
African Buffalo ◽  
Exploration And Exploitation ◽  
Organizational Skills ◽  
Careful Observation ◽  
Good Memory

This paper proposes the African Buffalo Optimization (ABO) which is a new metaheuristic algorithm that is derived from careful observation of the African buffalos, a species of wild cows, in the African forests and savannahs. This animal displays uncommon intelligence, strategic organizational skills, and exceptional navigational ingenuity in its traversal of the African landscape in search for food. The African Buffalo Optimization builds a mathematical model from the behavior of this animal and uses the model to solve 33 benchmark symmetric Traveling Salesman’s Problem and six difficult asymmetric instances from the TSPLIB. This study shows that buffalos are able to ensure excellent exploration and exploitation of the search space through regular communication, cooperation, and good memory of its previous personal exploits as well as tapping from the herd’s collective exploits. The results obtained by using the ABO to solve these TSP cases were benchmarked against the results obtained by using other popular algorithms. The results obtained using the African Buffalo Optimization algorithm are very competitive.

Task dependent synthesis of some geometrical parameters of a robot mechanism

Robotica ◽  
1993 ◽  
Vol 11 (2) ◽  
pp. 167-171 ◽  
Author(s):  
Maks Oblak ◽  
Karl Gotlih
Keyword(s):  
Mathematical Model ◽  
Nonlinear Optimization ◽  
Optimization Algorithm ◽  
Kinematic Chain ◽  
Chain Structure ◽  
Geometrical Parameters ◽  
Task Space ◽  
End Effector ◽  
Optimal Mechanism ◽  
Nonlinear Optimization Algorithm

SUMMARYThis paper deals with the synthesis of a robot mechanism, which has an open kinematic chain structure. The aim of the synthesis is to find optimal mechanism link lengths and the elevation of the robot mechanism base, with respect to the arbitrary chosen task which is described in a task space.A mathematical model, which describes the problem and enables one to use a nonlinear optimization algorithm, was developed. The usefulness of the approach is demonstrated by the example of the Manutec r3 mechanism with a prescribed task for the robot's end-effector.

scholarly journals Minimization of Torque Ripple in the Brushless DC Motor Using Constrained Cuckoo Search Algorithm

Electronics ◽  
2021 ◽  
Vol 10 (18) ◽  
pp. 2299
Author(s):  
Łukasz Knypiński ◽  
Sebastian Kuroczycki ◽  
Fausto Pedro García Márquez
Keyword(s):  
Mathematical Model ◽  
Optimization Algorithm ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Torque Ripple ◽  
Dc Motor ◽  
Cuckoo Search Algorithm ◽  
Brushless Dc Motor ◽  
Brushless Dc ◽  
Commutation Torque Ripple

This paper presents the application of the cuckoo search (CS) algorithm in attempts to the minimization of the commutation torque ripple in the brushless DC motor (BLDC). The optimization algorithm was created based on the cuckoo’s reproductive behavior. The lumped-parameters mathematical model of the BLDC motor was developed. The values of self-inductances, mutual inductances, and back-electromotive force waveforms applied in the mathematical model were calculated by the use of the finite element method. The optimization algorithm was developed in Python 3.8. The CS algorithm was coupled with the static penalty function. During the optimization process, the shape of the voltage supplying the stator windings was determined to minimize the commutation torque ripple. Selected results of computer simulation are presented and discussed.

Research on Path Optimization of Automated Warehouse Based on Ant Colony Algorithm

2011 ◽  
Vol 201-203 ◽  
pp. 1112-1115
Author(s):  
Hao Ping Li ◽  
Zi Fan Fang ◽  
Ying Wang
Keyword(s):  
Mathematical Model ◽  
Energy Consumption ◽  
Optimization Algorithm ◽  
Ant Colony Algorithm ◽  
Operation Time ◽  
Optimization Method ◽  
Ant Colony ◽  
Path Optimization ◽  
Operating Costs ◽  
Reduce Energy Consumption

Based on analysis of the cargo selecting strategy of fixed shelf automated warehouse, the idea of path optimization is put forward and the stacker path optimization method is studied. A mathematical model of stacker operation path optimization is built to minimize the length of operation path and the operation time. The model is solved by using the ant colony optimization method. Simulation shows that chosen stacker operation path by using the optimization model and optimization algorithm, can not only reduce energy consumption and warehouse operating costs, but also improve the efficiency of goods storage.

Cooperative Target Allocation for UCAV Team Air-to-Ground Attack Based on Decision Graph Bayesian Optimization Algorithm

2012 ◽  
Vol 457-458 ◽  
pp. 655-662
Author(s):  
Lu Cao ◽  
An Zhang ◽  
Feng Juan Guo
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Optimization Algorithm ◽  
Optimal Solution ◽  
Bayesian Optimization ◽  
Bayesian Optimization Algorithm ◽  
Decision Graph ◽  
Target Allocation ◽  
Cooperative Decision Making ◽  
The Mathematical Model

In order to control and optimize cooperative air-to-ground attack decision-making of the unmanned combat aerial vehicle (UCAV) team, the principle of income maximum and loss minimum of UCAV team is built firstly. Accordingly, the mathematical model of cooperative target allocation is built based on the decision variables and constraints. Then Bayesian optimization algorithm (BOA) is introduced which is one kind of the evolution algorithm. For improving the ability of the BOA, decision graph is introduced to enhance the represent and learn of Bayesian network and compress the parameter saving. Finally decision graph Bayesian optimization algorithm (DBOA) is utilized to optimize and analyze the model. The simulation results verify that the mathematical model of cooperative target allocation can reflect the importance of cooperative decision-making, the DBOA can converge quickly to the global optimal solution and can effectively solve the cooperative target allocation problem of UCAV team air-to-ground attack.

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