A Improved Bus Timetable Scheduling Model Using Quantum Genetic Algorithm Based on Penalty Strategy

2012 ◽  
Vol 253-255 ◽  
pp. 1406-1409 ◽  
Author(s):  
Xin Lai Tang ◽  
Shu Hong Yang
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Optimal Parameters ◽  
Quantum Genetic Algorithm ◽  
Scheduling Model ◽  
Bus Scheduling ◽  
Low Efficiency ◽  
The Cost ◽  
Bus Operator ◽  
Penalty Strategy

Considering the influence that the cycles of signal lamp have on the waiting time, a bus scheduling model is presented in this paper based on the trade-off between the cost of bus operator and benefits of passengers. In order to handle with the low efficiency brought about by the refused strategy, a new fitness function is designed according to penalty strategy, and then traditional genetic algorithm is replaced by quantum genetic algorithm to accelerate the search of optimal parameters further. The results of experiment show that the presented method is effective.

Scheduling Optimization of Inter-City Bus Rapid Transit Based on M/M/C/N/∞ Queuing Model

2012 ◽  
Vol 235 ◽  
pp. 294-297
Author(s):  
Xiao Yong Tian ◽  
Hui Yuan Jiang ◽  
Jin Zha
Keyword(s):  
Genetic Algorithm ◽  
Fitness Function ◽  
Bus Rapid Transit ◽  
Rapid Transit ◽  
Queuing Model ◽  
City Bus ◽  
Maximum Profit ◽  
Scheduling Model ◽  
Bus Scheduling ◽  
Time Division

According the characteristics of inter-city bus rapid transit in urban circle, bus scheduling model of time division is established based on M/M/C/N/∞ queuing model that it can realize the maximum profit and meet the needs of passengers. The ideas of Simulated Annealing extending are introduced to Genetic Algorithm to construct variable fitness function, and Metropolis rule is adopted to guide the optimization process of the Genetic Algorithm.

The Research on Electric Bus Operation Intelligence Scheduling Model and Algorithm

2012 ◽  
Vol 253-255 ◽  
pp. 1330-1334
Author(s):  
Song Gao ◽  
Pei Pei Zhang ◽  
De Rong Tan ◽  
Xiao Lin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Discharge Time ◽  
Charging Time ◽  
Scheduling Model ◽  
Bus Scheduling ◽  
Electric Bus ◽  
Driving Range ◽  
Operation Scheduling ◽  
Full Consideration

Electric bus is different from traditional bus. Its operation scheduling is constrained by the charge time, discharge time and driving range. On the base of full consideration of the electric bus driving range and charging time, the electric bus scheduling model is built. Then a genetic algorithm is selected to solve the model. Finally, an electric bus route in Zibo City is taken as an example, to adopt modeling and solving. The results verify the applicability of the model and algorithm.

scholarly journals Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Ariel Masuri ◽  
Oded Medina ◽  
Shlomi Hacohen ◽  
Nir Shvalb
Keyword(s):  
Experimental Data ◽  
Genetic Algorithm ◽  
Trajectory Optimization ◽  
Simple Technique ◽  
Fitness Function ◽  
Step Length ◽  
Small Animals ◽  
The Cost ◽  
Self Learning ◽  
Real Experimental Data

This paper presents an efficient technique for a self-learning dynamic walk for a quadrupedal robot. The cost function for such a task is typically complicated, and the number of parameters to be optimized is high. Therefore, a simple technique for optimization is of importance. We apply a genetic algorithm (GA) which uses real experimental data rather than simulations to evaluate the fitness of a tested gait. The algorithm actively optimizes 12 of the robot’s dynamic walking parameters. These include the step length and duration and the bending of an active back. For this end, a simple quadrupedal robot was designed and fabricated in a structure inspired by small animals. The fitness function was then computed based on experimental data collected from a camera located above the scene coupled with data collected from the actuators’ sensors. The experimental results demonstrate how walking abilities are improved in the course of learning, while including an active back should be considered to improve walking performances.

scholarly journals Optimasi Beban Mengajar Dosen Pendidikan Informatika di STKIP Bumi Persada Menggunakan Algoritme Genetika

2019 ◽  
Vol 1 ◽  
pp. 972
Author(s):  
Teuku Afriliansyah
Keyword(s):  
Genetic Algorithm ◽  
Fixed Number ◽  
Routine Activity ◽  
Test Results ◽  
Optimal Parameters ◽  
Study Program ◽  
Random Mutation ◽  
Fitness Value ◽  
Selection Test ◽  
The Cost

The cost of teaching lecturers is a routine activity conducted by all universities, especially the maintainers of departments in each faculty. This is done because the number of courses planned students are in every semester is always different and faced with a relatively fixed number of lecturers. Determining the teaching burden of lecturers must be done so that the teaching burden of lecturers does not exceed the maximum possible limit and the teaching process is done in accordance with the interest of lecturer study. Study Program of informatics Education High School and Educational Sciences Earth Persada Lhokseumawe still do the process of determining the teaching burden of the lecturer with the manual so that it takes a little time because it must adjust the infirmity Courses with a lecturer study interest. One of the methods of optimization that is able to solve the problem is genetic algorithm. The genetic algorithm process in this research includes representation with integer numbers, crossover methods with one cut point crossover, mutation methods with Reciprocalexchange mutation and random mutation, as well as selection methods with elitism Selection. Test results that have been tested show optimal parameters i.e. population size 60, combination of CR and Mr Value respectively 0.4, Sertta generation of 3576 with the largest fitness value produced is 0.082846.

scholarly journals Controller design of isolated power-electricity island using genetic algorithm

2019 ◽  
Vol 70 (1) ◽  
pp. 46-51
Author(s):  
Ivan Sekaj ◽  
Martin Ernek
Keyword(s):  
Genetic Algorithm ◽  
Cost Function ◽  
Controller Design ◽  
Control Design ◽  
Optimal Parameters ◽  
Control Error ◽  
Pi Controllers ◽  
The Cost

Abstract The contribution presents the use of Genetic Algorithm for searching of the optimal parameters of a set of speed controllers of an isolated power-electricity island. Nine PI-controllers are designed. The cost function which is minimised using the Genetic Algorithm represents the integral of the control error area. Robustness aspects of the control design are considered as well.

scholarly journals Improved Quantum Genetic Algorithm in Application of Scheduling Engineering Personnel

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Huaixiao Wang ◽  
Ling Li ◽  
Jianyong Liu ◽  
Yong Wang ◽  
Chengqun Fu
Keyword(s):  
Genetic Algorithm ◽  
Quantum Genetic Algorithm ◽  
Low Efficiency ◽  
Encoding Method ◽  
Engineering Personnel

To verify the availability of the improved quantum genetic algorithm in solving the scheduling engineering personnel problem, the following work has been carried out: the characteristics of the scheduling engineering personnel problem are analyzed, the quantum encoding method is proposed, and an improved quantum genetic algorithm is applied to address the issue. Taking the low efficiency and the bad performance of the conventional quantum genetic algorithm into account, a universal improved quantum genetic algorithm is introduced to solve the scheduling engineering personnel problem. Finally, the examples are applied to verify the effectiveness and superiority of the improved quantum genetic algorithm and the rationality of the encoding method.

scholarly journals Inverse Analysis of the Partitioning Deformation Modulusof High-Arch Dams Based on Quantum Genetic Algorithm

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yantao Zhu ◽  
Xinqiang Niu ◽  
Jimin Wang ◽  
Chongshi Gu ◽  
Erfeng Zhao ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Inverse Analysis ◽  
Fitness Function ◽  
Deformation Modulus ◽  
Operating Conditions ◽  
Hydraulic Structures ◽  
Arch Dams ◽  
Quantum Genetic Algorithm ◽  
Reservoir Basin ◽  
High Arch Dams

The physical and mechanical parameters of hydraulic structures in complicated operating conditions often change over time. Updating these parameters in a timely manner is important to comprehend the operating behaviors and monitor the safety of hydraulic structures. Conventional inverse analysis methods can only generate inversions on the comprehensive deformation modulus of concrete dam structures, which contradict practical conditions. Based on the researches on conventional reversion methods of the deformation modulus of the dam body, foundation, and reservoir basin, the objective fitness function is established in this paper according to engineering-measured data and finite element simulation results. The quantum genetic algorithm has high global search efficiency and population diversity. A mechanical parameter inversion of high-arch dams is built from the intelligent optimization of an established algorithm by applying the quantum genetic algorithm. The proposed algorithm is tested to be feasible and valid for practical engineering projects and therefore shows scientific and practical application values.

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