Design of an Intelligent Shop Scheduling System Based on Internet of Things

Article Computer Science, Interdisciplinary Applications

MLATSO: A method for task scheduling optimization in multi-load AGVs-based systems

Yishuai Lin et al.

Summary: In the context of competitive intelligent manufacturing, the scheduling optimization of multi-load AGVs-based systems is crucial for automating storage/retrieval tasks and maximizing economic benefits. Our proposed method aims to simultaneously achieve the objectives of minimizing occupied AGVs, reducing travel time, and minimizing conflicts. Experiment results demonstrate that our method can optimize task delivery using fewer AGVs, leading to win-win results for system performance and AGVs investment, thus maximizing economic benefit.

ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING (2023)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An effective self-adaptive iterated greedy algorithm for a multi-AGVs scheduling problem with charging and maintenance

Wen-qiang Zou et al.

Summary: This paper investigates the scheduling problem of multi-AGVs with charging and maintenance (MAGVSCM) in a matrix manufacturing workshop. It proposes a mixed-integer linear programming model and a self-adaptive iterated greedy (SAIG) algorithm to reduce the total cost. The experimental results show that the proposed algorithm significantly outperforms existing algorithms in solving the problem.

EXPERT SYSTEMS WITH APPLICATIONS (2023)

添加到收藏夹

Article Engineering, Industrial

An improved genetic algorithm with modified critical path-based searching for integrated process planning and scheduling problem considering automated guided vehicle transportation task

Qihao Liu et al.

Summary: Integrated process planning and scheduling (IPPS) can improve the whole performance of the manufacturing system by taking advantage of process planning and shop scheduling. Additional consideration of the shop logistics system including AGV task assignment can further enhance shop productivity and system efficiency. This paper proposes an integrated encoding method and an improved genetic algorithm (IGA) to solve the IPPS problem considering AGV transportation task (IPPS_T), and the numerical experiments confirm the effectiveness of the proposed method and strategy.

JOURNAL OF MANUFACTURING SYSTEMS (2023)

添加到收藏夹

Article Computer Science, Artificial Intelligence

A Pareto-based hybrid iterated greedy algorithm for energy-efficient scheduling of distributed hybrid flowshop

Chao Lu et al.

Summary: The distributed hybrid flowshop scheduling problem (DHFSP) with objectives of minimizing the makespan and total energy consumption (TEC) is investigated in this paper. A Pareto-based multi-objective hybrid iterated greedy algorithm (MOHIG) is designed to address this problem. The proposed MOHIG integrates the merits of genetic operator and iterated greedy heuristic and incorporates cooperative initialization, knowledge-based multi-objective local search, and energy-saving techniques. Experimental results show that the proposed MOHIG outperforms other multi-objective optimization algorithms in solving this problem. This research has practical significance in guiding production in specific environments.

EXPERT SYSTEMS WITH APPLICATIONS (2022)

添加到收藏夹

Article Mathematics

Multi-AGV Flexible Manufacturing Cell Scheduling Considering Charging

Jianxun Li et al.

Summary: Automated Guided Vehicles (AGV) have gained popularity in intelligent manufacturing due to their flexibility, controllability, and convenience. This study examines the relationship between AGV scheduling tasks, charging thresholds, and power consumption in order to address the impact of AGV charging on the scheduling of flexible manufacturing units with multiple AGVs. A scheduling model is established to minimize the maximum completion time, and a genetic algorithm is used to solve the model and improve genetic diversity. The results demonstrate the effectiveness and viability of the scheduling model in optimizing AGV utilization and reducing charging times.

MATHEMATICS (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

An effective multi-objective evolutionary algorithm for solving the AGV scheduling problem with pickup and delivery

Wen-Qiang Zou et al.

Summary: This study investigates a new automatic guided vehicle scheduling problem in a matrix manufacturing workshop, proposing a multi-objective evolutionary algorithm to maximize customer satisfaction while minimizing distribution cost. Results from comparative experiments show that the proposed algorithm outperforms existing multi-objective algorithms in solving the problem effectively.

KNOWLEDGE-BASED SYSTEMS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence