An Improved Genetic Algorithm for Locations Allocation Optimization Problem of Automated Warehouse

2009 ◽  
pp. 1549-1560 ◽  
Author(s):  
Mei-juan Li ◽  
Hai-yan Tang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Improved Genetic Algorithm

scholarly journals Prototype Filter Design Based on Channel Estimation for FBMC/OQAM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongjin Liu ◽  
Xihong Chen ◽  
Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Channel Estimation ◽  
Optimization Problem ◽  
Filter Design ◽  
Stop Band ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Global Optimal Solution ◽  
Prototype Filter ◽  
Global Optimal

A prototype filter design for FBMC/OQAM systems is proposed in this study. The influence of both the channel estimation and the stop-band energy is taken into account in this method. An efficient preamble structure is proposed to improve the performance of channel estimation and save the frequency spectral efficiency. The reciprocal of the signal-to-interference plus noise ratio (RSINR) is derived to measure the influence of the prototype filter on channel estimation. After that, the process of prototype filter design is formulated as an optimization problem with constraint on the RSINR. To accelerate the convergence and obtain global optimal solution, an improved genetic algorithm is proposed. Especially, the History Network and pruning operator are adopted in this improved genetic algorithm. Simulation results demonstrate the validity and efficiency of the prototype filter designed in this study.

scholarly journals An Improved Genetic Algorithm with Initial Population Strategy for Symmetric TSP

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Yong Deng ◽  
Yang Liu ◽  
Deyun Zhou
Keyword(s):  
Genetic Algorithm ◽  
Combinatorial Optimization ◽  
Optimization Problem ◽  
Combinatorial Optimization Problem ◽  
Traveling Salesman ◽  
Average Error ◽  
Initial Population ◽  
Improved Genetic Algorithm ◽  
Population Strategy ◽  
Series Of Experiments

A new initial population strategy has been developed to improve the genetic algorithm for solving the well-known combinatorial optimization problem, traveling salesman problem. Based on thek-means algorithm, we propose a strategy to restructure the traveling route by reconnecting each cluster. The clusters, which randomly disconnect a link to connect its neighbors, have been ranked in advance according to the distance among cluster centers, so that the initial population can be composed of the random traveling routes. This process isk-means initial population strategy. To test the performance of our strategy, a series of experiments on 14 different TSP examples selected from TSPLIB have been carried out. The results show that KIP can decrease best error value of random initial population strategy and greedy initial population strategy with the ratio of approximately between 29.15% and 37.87%, average error value between 25.16% and 34.39% in the same running time.

The Attacking Dispersion Optimization in Multi Launch Rocket System Base-On Improved Genetic Algorithm

2014 ◽  
Vol 670-671 ◽  
pp. 1499-1502
Author(s):  
Wei Wang ◽  
Wei Dong Chen ◽  
Shu Qiang Zhang ◽  
Jiang Long Li ◽  
Ya En Xie
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Fitness Function ◽  
Reference Value ◽  
Weapon System ◽  
Improved Genetic Algorithm ◽  
Optimal Model ◽  
Overall Design ◽  
Mixed Coding ◽  
Rocket System

Firing dispersion of multi-launch rocket system is affected by launch sequence and firing interval significantly. Firing order and firing interval of the existing multi launch rocket system (MLRS) are optimized to improve the firing performance of the existing weapon system without changing the overall design of the weapon system. On one hand, based on optimization problem, the firing dispersion optimal model is established and the genetic algorithm is improved therefore, a sequence of mixed coding genetic algorithm is designed. On the other hand, simulation optimization of firing dispersion has been finished by the aid of fitness function which is based on the optimal model. Meanwhile, it testifies this algorithm’s validity and the simulation results can provide a certain reference value for engineering experiment.

An Optimization Algorithm Based on Job Shop Scheduling with Fuzzy Goals

2014 ◽  
Vol 912-914 ◽  
pp. 1156-1159
Author(s):  
Qing Ling Dai ◽  
Sheng Bo Zhang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Operating Mode ◽  
Problem Solution ◽  
Improved Genetic Algorithm ◽  
Shop Scheduling ◽  
Delivery Date ◽  
Scheduling Method

The mathematical model was built up for the job shop scheduling problem at first. With following the fuzzy submit time of customer requirement an improved genetic algorithm of fuzzy objective scheduling method was put forward which took the minimum production cost as the objective function. It solved the faults of the chromosomes in genetic algorithm is difficult to accurately express the complex optimization problem solution and determined the more suitable multilayer encoding and operating mode. The simulation results show that this algorithm can be applied to fuzzy object shop scheduling optimization problem, which can ensure the machine's load balance and meet the requirements of the customer delivery date.

Based on Genetic Algorithm Research of Stocker Picking Shortest Path

2012 ◽  
Vol 155-156 ◽  
pp. 186-190
Author(s):  
Fu Cai Wan ◽  
Duo Chen ◽  
Yong Qiang Wu
Keyword(s):  
Genetic Algorithm ◽  
Shortest Path ◽  
Optimization Problem ◽  
Traveling Salesman ◽  
Path Optimization ◽  
Improved Genetic Algorithm ◽  
Operating Process ◽  
Path Distance ◽  
Simulation Results ◽  
The Mathematical Model

This paper analyzes characteristics of automated warehouse stocker picking operating process. Path optimization problem is considered as traveling salesman problem. The coordinates of picking points by calculating determine a stocker running route. The mathematical model of a path distance is built. And using the improved genetic algorithm solves the above problem. Finally, M-file program of stocker running path optimization is written and run in MATLAB. The simulation results that, in solving stocker path optimization problem, it can search for a shortest path by genetic algorithm. Thereby enhance the efficiency of automated warehouse system, increase greater benefits of the enterprise.

The Research on the Improved Genetic Algorithm and Optimized Based on the Random Functional Analysis

2012 ◽  
Vol 166-169 ◽  
pp. 819-823
Author(s):  
Zheng Bing Xia ◽  
Zhi Xiang Cao ◽  
Ke Feng Zhang
Keyword(s):  
Genetic Algorithm ◽  
Functional Analysis ◽  
Optimization Problem ◽  
Technical Problem ◽  
Optimized Design ◽  
Engineering Optimization ◽  
Building Structure ◽  
Improved Genetic Algorithm ◽  
Traditional Algorithm ◽  
Practical Engineering

The optimization problem of building structure has the technical difficulties of nonlinear, discrete, indifferentiable and nonconvexity character, the traditional algorithm based on MATLAB can not solve practical engineering optimization problem accurately. Based on general genetic algorithm is as the foundation in this paper, the theory basis of modified algorithm is applied based on the application of functional analysis and analyses the genetic algorithm for the iterative characteristics is analyzed, and the three stem rod calculation is verified based on application of functional analysis improved genetic algorithm, which solves the optimized design of common rod technical problem and achieves good calculation accuracy and efficiency.

Application of Improved Genetic Algorithm in Optimum Configuration of Viscous Dampers in Tall Buildings

2014 ◽  
Vol 1006-1007 ◽  
pp. 423-426
Author(s):  
Le Wei Yan ◽  
Long Wang ◽  
Cheng Jun Huang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Design Space ◽  
Tall Buildings ◽  
Relative Fitness ◽  
Viscous Damper ◽  
Improved Genetic Algorithm ◽  
Viscous Dampers ◽  
Optimum Configuration ◽  
Testing Method

In this paper, genetic algorithm is improved by relative fitness, offspring testing method and optimum reserve strategy. An optimum configuration method of viscous damper in tall buildings was presented. This method has strongly practicable in complicated optimization problem of viscous dampers involving many dampers and stories, large design space and lots of optional configuration schema which cannot be solved by exhaustive method. It is used to optimize the configuration of viscous damper in a 30 layers building. Numerical examples demonstrated the efficiency and applicability of the proposed method.

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