Nondominated Sorting Differential Evolution Algorithm to Solve the Biobjective Multi-AGV Routing Problem in Hazardous Chemicals Warehouse

Duan, Lini; Liu, Yuanyuan; Li, Haiyan; Park, Kyung-Hye; Cao, Kerang

doi:10.1155/2022/3785039

Cited by 2 publications

(2 citation statements)

References 47 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The two optimizers have two limitations: 1) They cannot directly obtain a real Pareto front for the multi-objective optimization problem [41], [42]. To achieve non-dominated solutions, the commonly used method is to reconstruct objective functions using the weight-sum method:…”

Section: Case 4: Comparison and Simulation With Gurobi And Cplex Opti...mentioning

confidence: 99%

Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch

Lin,

Liang,

Pang

et al. 2024

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

Multi-area combined economic/emission dispatch (MACEED) problems are generally studied using analytical functions. However, as the scale of power systems increases, existing solutions become time-consuming and may not meet operational constraints. To overcome excessive computational expense in high-dimensional MACEED problems, a novel datadriven surrogate-assisted method is proposed. First, a cosinesimilarity-based deep belief network combined with a backpropagation (DBN + BP) neural network is utilized to replace cost and emission functions. Second, transfer learning is applied with a pretraining and fine-tuning method to improve DBN + BP regression surrogate models, thus realizing fast construction of surrogate models between different regional power systems. Third, a multi-objective antlion optimizer with a novel general single-dimension retention bi-objective optimization policy is proposed to execute MACEED optimization to obtain scheduling decisions. The proposed method not only ensures the convergence, uniformity, and extensibility of the Pareto front, but also greatly reduces the computational time. Finally, a 4-area 40-unit test system with different constraints is employed to demonstrate the effectiveness of the proposed method.Index Terms--Multi-area combined economic/emission dispatch, high-dimensional power system, deep belief network, data driven, transfer learning.Huijun Liang received the B.E. degree in industrial automation from Wuhan University of Hydraulic and Electric Engineering, Wuhan, China, in 2000, the M.E. degree in control theory and control engineering from Wuhan University, Wuhan, China, in 2004, the Ph.D. degree in control theory and control engineering from Shandong University, Jinan, China, in 2020. He is currently working as a Lecturer in Hubei Minzu University, Enshi, China. His research interests include computational intelligence and optimization in power systems.Aokang Pang received the B.E. degree in electrical engineering and its automation from Xi'an Kedagaoxin University, Xi'an, China, in 2021. is currently pursuing the M.E. degree in electrical engineering in Hubei Minzu University, Enshi, China. His current research interests include computational intelligence and its application to economic dispatch of power systems.

show abstract

Section: Case 4: Comparison and Simulation With Gurobi And Cplex Opti...mentioning

confidence: 99%

Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch

Lin,

Liang,

Pang

et al. 2024

Journal of Modern Power Systems and Clean Energy

View full text Add to dashboard Cite

show abstract

“…Chen Yun [8] established a warehouse shelf model, introduced the Poisson distribution to simulate the influence of unknown factors; and established a three-color grid map, which can safely and effectively design the optimal path in the storage environment under the influence of unknown factors and solve the problem of blind search and deadlock. Aiming to solve the multi-automatic guided vehicle (multi-AGV) path problem in logistics and warehousing, a non-dominated sorting differential evolution (NSDE) algorithm was advocated by Duan and Liu [9] to minimize the number of AGVs and the maximum pickup time. It can adjust the picking points in the area, optimize the picking path, and improve the picking efficiency.…”

Section: Introductionmentioning

confidence: 99%

Cognitive Enhancement of Robot Path Planning and Environmental Perception Based on Gmapping Algorithm Optimization

Liu,

Gong,

et al. 2024

Electronics

View full text Add to dashboard Cite

In the logistics warehouse environment, the autonomous navigation and environment perception of the logistics sorting robot are two key challenges. To deal with the complex obstacles and cargo layout in a warehouse, this study focuses on improving the robot perception and navigation system to achieve efficient path planning and safe motion control. For this purpose, a scheme based on an improved Gmapping algorithm is proposed to construct a high-precision map inside a warehouse through the efficient scanning and processing of environmental data by robots. While the improved algorithm effectively integrates sensor data with robot position information to realize the real-time modeling and analysis of warehouse environments. Consequently, the precise mapping results provide a reliable navigation basis for the robot, enabling it to make intelligent path planning and obstacle avoidance decisions in unknown or dynamic environments. The experimental results show that the robot using the improved Gmapping algorithm has high accuracy and robustness in identifying obstacles and an effectively reduced navigation error, thus improving the intelligence level and efficiency of logistics operations. The improved algorithm significantly enhances obstacle detection rates, increasing them by 4.05%. Simultaneously, it successfully reduces map size accuracy errors by 1.4% and angle accuracy errors by 0.5%. Additionally, the accuracy of the robot’s travel distance improves by 2.4%, and the mapping time is reduced by nine seconds. Significant progress has been made in achieving high-precision environmental perception and intelligent navigation, providing reliable technical support and solutions for autonomous operations in logistics warehouses.

show abstract

Nondominated Sorting Differential Evolution Algorithm to Solve the Biobjective Multi-AGV Routing Problem in Hazardous Chemicals Warehouse

Cited by 2 publications

References 47 publications

Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch

Data-driven Surrogate-assisted Method for High-dimensional Multi-area Combined Economic/Emission Dispatch

Cognitive Enhancement of Robot Path Planning and Environmental Perception Based on Gmapping Algorithm Optimization

Contact Info

Product

Resources

About