NEW HYBRID GENETIC ALGORITHM SOLVING THE ORDER-PICKING OPTIMIZATION PROBLEM OF A MULTI-CAROUSEL SYSTEM

2004 ◽  
Vol 40 (06) ◽  
pp. 34 ◽  
Author(s):  
Pan Zhang
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Order Picking

Solving a Two-stage Supply Chain Network Design Problem with Fixed Costs by a Hybrid Genetic Algorithm

2021 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C Pop ◽  
Cosmin Sabo
Keyword(s):  
Genetic Algorithm ◽  
Supply Chain ◽  
Network Design ◽  
Design Problem ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Network Design Problem ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Fixed Costs

Abstract In this paper we investigate a particular two-stage supply chain network design problem with fixed costs. In order to solve this complex optimization problem, we propose an efficient hybrid algorithm, which was obtained by incorporating a linear programming optimization problem within the framework of a genetic algorithm. In addition, we integrated within our proposed algorithm a powerful local search procedure able to perform a fine tuning of the global search. We evaluate our proposed solution approach on a set of large size instances. The achieved computational results prove the efficiency of our hybrid genetic algorithm in providing high-quality solutions within reasonable running-times and its superiority against other existing methods from the literature.

Complex Mechatronic System Reliability Optimization Using Hybrid Genetic Algorithm

2011 ◽  
Vol 138-139 ◽  
pp. 1296-1301 ◽  
Author(s):  
J. C. Wang ◽  
H. Qiu ◽  
J. M. Chen ◽  
G. D. Ji
Keyword(s):  
Genetic Algorithm ◽  
System Reliability ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Optimization Techniques ◽  
Reliability Optimization ◽  
Mechatronic System ◽  
Reliability Allocation ◽  
Highly Nonlinear ◽  
System Reliability Optimization

Reliability allocation optimization problem of a complex mechatronic system is a highly nonlinear constrained optimization problem, and hence solution to this kind of problem is of NP-hardness even with moderate scale. Due to the nonlinearity combined with multiple local extreme values, traditional optimization techniques fail to arrive at the global or nearly global optimal solution to the problem. Genetic algorithm incorporated with neighboring domain traversal searching technique is utilized in this paper to solve the complex mechatronic system reliability optimization allocation problem. Reliability allocation optimization of the life-support system in a space capsule, being a typical non serial-parallel system, is specifically demonstrated to show the satisfactory convergence performance as well as the important practical value of hybrid genetic algorithm. The simulation results show that the proposed method may gain better precision in solving the complex mechatronic system reliability optimization problem.

scholarly journals Hybrid genetic algorithm-based optimisation of the batch order picking in a dense mobile rack warehouse

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0249543
Author(s):  
Jianglong Yang ◽  
Li Zhou ◽  
Huwei Liu
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Hierarchical Clustering ◽  
Hybrid Genetic Algorithm ◽  
Order Picking ◽  
Location Information ◽  
Storage Space ◽  
Time Cost ◽  
Solution Algorithms ◽  
Multiple Orders

The utilization of a storage space can be considerably improved by using dense mobile racks. However, it is necessary to perform an optimisation study on the order picking to reduce the time cost as much as possible. According to the channel location information that needs to be sorted, the multiple orders are divided into different batches by using hierarchical clustering. On this basis, a mathematical model for the virtual order clusters formed in the batches is established to optimize the order cluster picking and rack position movement, with the minimum picking time as the objective. For this model, a hybrid genetic algorithm is designed, and the characteristics of the different examples and solution algorithms are further analysed to provide a reference for the solution of the order picking optimisation problem in a dense mobile rack warehouse.

Firepower Assignment of Ship-to-Air Missile System

2014 ◽  
Vol 905 ◽  
pp. 702-705
Author(s):  
Yong Hong Lu ◽  
Ji Hua Dou ◽  
Xing Bao Yang ◽  
Chuan Wei Zhu
Keyword(s):  
Genetic Algorithm ◽  
Global Optimization ◽  
Decision Support ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Hill Climbing ◽  
Unconstrained Optimization Problem ◽  
Provide Decision Support ◽  
Missile System ◽  
Standard Genetic Algorithm

Hybrid genetic algorithm has been proposed in this paper, which is proposed by combining standard genetic algorithm with hill climbing to solve the unconstrained optimization problem, which can get global optimization results of the firepower assignment, and provide decision support for the firepower assignment.

An optimization method of technological processes to complex products using knowledge-based genetic algorithm

2015 ◽  
Vol 19 (1) ◽  
pp. 82-94 ◽  
Author(s):  
Yuchun Yao ◽  
Yan Wang ◽  
Lining Xing ◽  
Hao Xu
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Hybrid Genetic Algorithm ◽  
Optimization Process ◽  
Neighborhood Search ◽  
Knowledge Model ◽  
Content Type ◽  
Complex Products ◽  
Technological Processes ◽  
Knowledge Based

Purpose – This paper applies the knowledge-based genetic algorithm to solve the optimization problem in complex products technological processes. Design/methodology/approach – The knowledge-based genetic algorithm (KGA) is defined as a hybrid genetic algorithm (GA) which combined the GA model with the knowledge model. The GA model searches the feasible space of optimization problem based on the “neighborhood search” mechanism. The knowledge model discovers some knowledge from the previous optimization process, and applies the obtained knowledge to guide the subsequent optimization process. Findings – The experimental results suggest that the proposed KGA is feasible and available. The effective integration of GA model and knowledge model has greatly improved the optimization performance of KGA. Originality/value – The technological innovation of complex products is one of effective approaches to establish the core competitiveness in future. For this reason, the KGA is proposed to the technological processes optimization of complex products.

scholarly journals An Approach to Ship Deck Arrangement Optimization Problem Using an Improved Multiobjective Hybrid Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-24
Author(s):  
Hao Wang ◽  
Shunhuai Chen
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problem ◽  
Early Stage ◽  
Hybrid Genetic Algorithm ◽  
Performance Tests ◽  
Problem Statement ◽  
Nsga Ii ◽  
Adaptive Crossover ◽  
Validation Tests ◽  
The Mathematical Model

Ship deck arrangement design is about determining the positions and dimensions of arranged objects. This paper presents the mathematical model for the ship deck arrangement optimization problem statement and how the individual’s objective and constraint functions are computed. Moreover, an improved multiobjective hybrid genetic algorithm is redesigned to solve this complex nondeterministic problem and generate a set of diverse and rational deck arrangements in the early stage of ship design. An adaptive crossover operator and a novel topological replace operator invoked in this algorithm are described. Finally, the proposed algorithm is tested on a main deck arrangement optimization of an underwater detection ship. In the validation tests, the proposed algorithm is compared to the standard NSGA-II to determine its ability to produce a set of diverse and rational deck arrangements. Subsequently, the performance tests are used to determine the ability of the algorithm to work with the highly constrained arrangement problems and the efficiency of the adaptive crossover and topological replace operators.

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