scholarly journals Research on Logistics Distribution Vehicle Scheduling Based on Heuristic Genetic Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Chun-Li Wang ◽  
Yang Wang ◽  
Ze-Yu Zeng ◽  
Cheng-Yu Lin ◽  
Qiu-Li Yu
Keyword(s):  
Genetic Algorithm ◽  
Double Layer ◽  
Vehicle Scheduling ◽  
Genetic Operators ◽  
Logistics Distribution ◽  
Shop Scheduling ◽  
Calculation Process ◽  
The Stability ◽  
The Cost

To study the genetic algorithm, this paper solves the problem of shop scheduling under the premise of layout Flying − V . Firstly, double-layer coding is used for optimization. When calculating fitness, the time to return to the mouth P & D approaches the optimum through the greedy idea. Individual screening is carried out through the roulette method. Different crossover and genetic operators are used for different coding layers. Through thinking of elitism and catastrophe and the immigration operator to ensure the diversity of the algorithm in the calculation process, it can achieve the recommendation of the number of cars to control the cost. The stability of the algorithm is good. It can recommend a better picking sequence and number of carts for various types of picking problems.

scholarly journals Research on Logistics Distribution Path Planning Based on Genetic Algorithm

2021 ◽  
Vol 2083 (3) ◽  
pp. 032013
Author(s):  
Shaokun Liu
Keyword(s):  
Genetic Algorithm ◽  
Simulation Experiment ◽  
Time Window ◽  
Planning Model ◽  
Genetic Operators ◽  
Intelligent Algorithm ◽  
Total Cost ◽  
Logistics Distribution ◽  
Survey Results ◽  
Distribution Cost

Abstract In this paper, SF express company Jinzhou Guta District Pinganli business point as an example, to investigate its distribution, statistical analysis of the survey results, summed up the problems in logistics and distribution. Through the systematic study of the problem, a planning model with time window and with the objective of minimizing the total cost of distribution is established. At the same time, an intelligent algorithm for distribution path optimization - Genetic Algorithm (GA) is designed. Genetic algorithm is used to design chromosome coding methods and genetic operators for solving the planning model with the objective of minimizing the total cost of distribution. Finally, the simulation experiment is carried out. MATLAB software is used to solve the distribution route and the total driving distance of vehicles, and the distribution route with the goal of minimizing the total distribution cost is obtained.

Genetic Algorithm and Fuzzy Logic Based Optimal Location of Facts Device in a Power System Network

2006 ◽  
Vol 5 (2) ◽  
Author(s):  
Baskaran Jeevarathinam
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Power System ◽  
Optimization Technique ◽  
Flexible Ac Transmission ◽  
Flexible Ac Transmission System ◽  
Facts Controllers ◽  
The Stability ◽  
Ac Transmission ◽  
The Cost

The flexible AC transmission system (FACTS) in a power system improves the stability, reduces the losses, reduces the cost of generation and also improves the loadability of the system. In the proposed work, a non-traditional optimization technique, a Genetic Algorithm (GA) is conjunction with Fuzzy logic (FL) is used to optimize the various process parameters involved in introduction of FACTS devices in a power system. The various parameters taken into consideration were the location of the device, their type, and their rated value of the devices. The simulation was performed on a 30-bus power system with various types of FACTS controllers, modeled for steady state studies. The optimization results are compared to the solution given by another search method. This comparison confirms the efficiency of the proposed method which makes it promising to solve combinorial problem of FACTS device location in a power system network.

An effective genetic algorithm for job shop scheduling

2000 ◽  
Vol 214 (4) ◽  
pp. 293-300 ◽  
Author(s):  
W Wang ◽  
P Brunn
Keyword(s):  
Genetic Algorithm ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Scheduling Problems ◽  
Genetic Operators ◽  
Gene Encoding ◽  
Encoding Scheme ◽  
Shop Scheduling ◽  
Sequencing And Scheduling

This paper presents an effective genetic algorithm (GA) for job shop sequencing and scheduling. A simple and universal gene encoding scheme for both single machine and multiple machine models and their corresponding genetic operators, selection, sequence-extracting crossover and neighbour-swap mutation are described in detail. A simple heuristic rule is adapted and embedded into the GA to avoid the production of unfeasible solutions. The results of computing experiments for a number of scheduling problems have demonstrated that the GA described in the paper is effective and efficient in terms of the quality of solution and the computing cost.

scholarly journals Black Hole Algorithm for Sustainable Design of Counterfort Retaining Walls

2020 ◽  
Vol 12 (7) ◽  
pp. 2767 ◽  
Author(s):  
Víctor Yepes ◽  
José V. Martí ◽  
José García
Keyword(s):  
Black Hole ◽  
Sustainable Design ◽  
Retaining Walls ◽  
The Other ◽  
Trade Off ◽  
Construction Company ◽  
Geometric Variables ◽  
The Stability ◽  
The Cost ◽  
Black Hole Algorithm

The optimization of the cost and CO 2 emissions in earth-retaining walls is of relevance, since these structures are often used in civil engineering. The optimization of costs is essential for the competitiveness of the construction company, and the optimization of emissions is relevant in the environmental impact of construction. To address the optimization, black hole metaheuristics were used, along with a discretization mechanism based on min–max normalization. The stability of the algorithm was evaluated with respect to the solutions obtained; the steel and concrete values obtained in both optimizations were analyzed. Additionally, the geometric variables of the structure were compared. Finally, the results obtained were compared with another algorithm that solved the problem. The results show that there is a trade-off between the use of steel and concrete. The solutions that minimize CO 2 emissions prefer the use of concrete instead of those that optimize the cost. On the other hand, when comparing the geometric variables, it is seen that most remain similar in both optimizations except for the distance between buttresses. When comparing with another algorithm, the results show a good performance in optimization using the black hole algorithm.

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