scholarly journals Research on the Path Optimization Problem of Multi-Centre Distribution System

2018 ◽  
Vol 232 ◽  
pp. 04034
Author(s):  
Kai-lun HE ◽  
Yi DING ◽  
Hui-long SUN
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Optimization Problem ◽  
Path Optimization ◽  
Routing Problem ◽  
Actual Environment ◽  
Distribution Cost

Based on the actual environment, the routing problem of multi centre distribution system is theoretically described and analyzed, and a genetic algorithm for solving the problem is proposed and verified by an example. The research shows that the genetic algorithm can be used effectively to optimize the distribution path and reduce the distribution cost. At the same time, the program is easy to operate and is convenient for the enterprise to apply.

GA Implementation Path Optimization of Pneumatic Marking System

2013 ◽  
Vol 391 ◽  
pp. 390-393
Author(s):  
Lei Shao ◽  
Hai Bin Zuo ◽  
Nan Liu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Algorithm ◽  
Optimization Problem ◽  
Path Optimization ◽  
Matlab Simulation

According to the characteristics of pneumatic marking system, and the typing path was seen as a TSP problem. After comparing the Dijkstra optimization algorithm of marking path results, and applying the genetic algorithm (GA) to analysis, research, and solve the optimization problem, reasonable to get print needle typing path. In this case, printing mark time was shorten as much as possible. It was proved by MATLAB simulation that the study can solve the problem of path optimization and improve the efficiency of marking greatly.

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.

Study on Coordinated Control of Multi-Distribution Static Var Compensator

2014 ◽  
Vol 672-674 ◽  
pp. 1127-1131
Author(s):  
Ming Jiang Zhang ◽  
Xi Lin Zhang ◽  
Zhen Hao Wang ◽  
Ling Wang
Keyword(s):  
Genetic Algorithm ◽  
Power Quality ◽  
Distribution System ◽  
Optimization Problem ◽  
Coordinated Control ◽  
Parameters Optimization ◽  
Static Var Compensator ◽  
Multi Objective Optimization ◽  
Nsga Ii ◽  
Simulation Results

DFACTS devices can synthetically manage power quality problems. As one of the most DFACTS devices, the coordinated control of multi-distribution static var compensator should be considered. Controllers are separately designed aiming at different functions, that means the controllers are isolated even contradictory. In allusion to the problem that the separately designed DFACTS controllers exist interactions, the paper turns the coordination of the DFACTS controller into multi-objective optimization problem, takes the single-load infinite-bus distribution system with two DSVC as the research object, using the Non-dominated Sorting Genetic Algorithm with elitism approach (NSGA-II) for DFACTS controller parameters optimization, and the simulation results show the effectiveness of the algorithm.

scholarly journals A two-level based genetic algorithm for solving the soft-clustered vehicle routing problem

2021 ◽  
Vol 38 (1) ◽  
pp. 117-128
Author(s):  
OVIDIU COSMA ◽  
◽  
PETRICĂ C. POP ◽  
CORINA POP SITAR ◽  
◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Optimization Problem ◽  
A Priori ◽  
Minimum Cost ◽  
Routing Problem ◽  
Solution Approach ◽  
Benchmark Instances ◽  
Generalized Vehicle Routing Problem

The soft-clustered vehicle routing problem (Soft-CluVRP) is a relaxation of the clustered vehicle routing problem (CluVRP), which in turn is a variant of the generalized vehicle routing problem (GVRP). The aim of the Soft-CluVRP is to look for a minimum cost group of routes starting and ending at a given depot to a set of customers partitioned into a priori defined, mutually exclusive and exhaustive clusters, satisfying the capacity constraints of the vehicles and with the supplementary property that all the customers from the same cluster have to be supplied by the same vehicle. The considered optimization problem is NP-hard, that is why we proposed a two-level based genetic algorithm in order to solve it. The computational results reported on a set of existing benchmark instances from the literature, prove that our novel solution approach provides high-quality solutions within acceptable running times.

Route Optimization of DGT Based on Improved Genetic Algorithm

2014 ◽  
Vol 536-537 ◽  
pp. 845-848
Author(s):  
Tong Jie Zhang ◽  
Yan Cao ◽  
Xiang Wei Mu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Route Optimization ◽  
Path Optimization ◽  
Initial Population ◽  
Local Optimum ◽  
Search Efficiency ◽  
Improved Genetic Algorithm ◽  
Adaptive Adjustment ◽  
Dynamic Operator

An improved genetic algorithm for route optimization in DGT is proposed in this paper. In which, method of initial population, cross and mutation are improved to make it more suitable for DGT. It uses a dynamic operator to realize the adaptive adjustment of the parameters. The experimental results show that the improved algorithm overcomes the shortcomings of local optimum and "premature convergence" and improves the search efficiency and adaptability. The proposed algorithm can effectively solve the path optimization problem in DGT in time.

scholarly journals Optimization of Distribution Path considering Cost and Customer Satisfaction under New Retail Modes

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Dengqing Wang ◽  
Yuting Yang ◽  
Yanhu Wang
Keyword(s):  
Genetic Algorithm ◽  
Distribution System ◽  
Consumer Satisfaction ◽  
Distribution Patterns ◽  
Immune Algorithm ◽  
Online Retail ◽  
Weak Points ◽  
The Cost ◽  
Distribution Cost ◽  
Retail Enterprise

One of the top issues in logistics management and related research is to establish an effective distribution system that is adaptive to new retail and capable of lowering the cost of logistics while enhancing consumer satisfaction. Aimed at reversing the weak points of current logistics distribution patterns, a dual-objective bipolar model with optimal logistics cost and consumer satisfaction by restraining distribution time and load is tested in this paper to figure out the proper nodes and vehicle routes. Data from general and front warehouses of PuPu mall, a Fuzhou-based online retail enterprise, are made into a case study. Moreover, the immune algorithm and genetic algorithm are adopted to achieve the model solution. It is found that the immune algorithm is more efficient than the genetic algorithm in searching solutions, thus having better adaptivity and effectiveness, and also that the type of distribution vehicle plays a significant role in determining the total distribution cost.

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