Survey on Genetic Programming and Machine Learning Techniques for Heuristic Design in Job Shop Scheduling

IEEE Transactions on Evolutionary Computation, Journal Year: 2023, Volume and Issue: 28(1), P. 147 - 167

Published: March 10, 2023

Job shop scheduling (JSS) is a process of optimizing the use limited resources to improve production efficiency. JSS has wide range applications, such as order picking in warehouse and vaccine delivery under pandemic. In real-world environment often complex due dynamic events, job arrivals over time machine breakdown. Scheduling heuristics, e.g., dispatching rules, have been popularly used prioritize candidates machines manufacturing make good schedules efficiently. Genetic programming (GP), shown its superiority learning heuristics for automatically flexible representation. This survey first provides comprehensive discussions recent designs GP algorithms on different types JSS. addition, we notice that years, techniques, feature selection multitask learning, adapted effectiveness efficiency heuristic design with GP. However, there no discuss strengths weaknesses these approaches. To fill this gap, article techniques automatic current issues challenges are discussed identify promising areas future.

Language: Английский

---

From natural language to simulations: applying AI to automate simulation modelling of logistics systems

International Journal of Production Research, Journal Year: 2023, Volume and Issue: 62(4), P. 1434 - 1457

Published: Nov. 2, 2023

Our research strives to examine how simulation models of logistics systems can be produced automatically from verbal descriptions in natural language and human experts artificial intelligence (AI)-based collaborate the domain modelling. We demonstrate that a framework constructed upon refined GPT-3 Codex is capable generating functionally valid simulations for queuing inventory management when provided with explanation. As result, model could produce process control. These results, along rapid improvement models, enable significant simplification development. study offers guidelines design processing-based on build automatically, given description. In generalised terms, our work technological underpinning human-AI collaboration development models.

Language: Английский

---

Manufacturing resource-based self-organizing scheduling using multi-agent system and deep reinforcement learning

Journal of Manufacturing Systems, Journal Year: 2025, Volume and Issue: 79, P. 179 - 198

Published: Jan. 24, 2025

Language: Английский

---

Digital twin-enabled dynamic spatial-temporal knowledge graph for production logistics resource allocation

Computers & Industrial Engineering, Journal Year: 2022, Volume and Issue: 171, P. 108454 - 108454

Published: July 14, 2022

Language: Английский

---

A Q-Learning based NSGA-II for dynamic flexible job shop scheduling with limited transportation resources

Swarm and Evolutionary Computation, Journal Year: 2024, Volume and Issue: 90, P. 101658 - 101658

Published: July 18, 2024

Language: Английский

---

Multi-objective adaptive large neighbourhood search algorithm for dynamic flexible job shop schedule problem with transportation resource

Engineering Applications of Artificial Intelligence, Journal Year: 2024, Volume and Issue: 132, P. 107917 - 107917

Published: Jan. 26, 2024

Language: Английский

---

Scheduling and Logistics Optimization for Batch Manufacturing Processes With Temperature Constraints and Alternative Thermal Devices

IEEE Transactions on Industrial Informatics, Journal Year: 2024, Volume and Issue: 20(10), P. 11930 - 11939

Published: July 4, 2024

Batch scheduling problems are NP-hard and often coupled with logistics optimization in industrial manufacturing scenarios, further increasing the challenge of decision-making. This work focuses on a stainless steel hot-rolling production process, where it is essential to maintain temperature products from previous process beyond certain threshold. Our diverges typical processes by necessitating utilization alternative thermal devices, thereby intricately linking batch resulting novel lexicographical dual-objective problem. To address this complex problem, we first introduce mathematical model formulated as mixed integer program, providing exact solutions concerned problem but taking much computation time. provide effective efficient solutions, then propose an enhanced simulated annealing algorithm, which integrates destruction construction methods inspired iterated greedy algorithms. algorithm tailored specific characteristics incorporating specialized encoding-decoding mechanisms, neighborhood search operators, Metropolis acceptance criterion. experimental results highlight effectiveness proposed approaches, demonstrating their superiority over competitive peers. Thus, research contributes valuable insights innovative challenges inherent constraints devices.

Language: Английский

---

Robust multi-equipment scheduling for U-shaped container terminals concerning double-cycling mode and uncertain operation time with cascade effects

Transportation Research Part C Emerging Technologies, Journal Year: 2023, Volume and Issue: 158, P. 104447 - 104447

Published: Dec. 6, 2023

The integrated scheduling of quay cranes, internal vehicles, and yard cranes in container terminals aims to improve port operations often requires robustness under uncertainty with cascade effects. In terminal operations, equipment operating time poses challenges effective scheduling, as even small fluctuations can create effects throughout the rendering original schedule ineffective. This research develop a new method that enables balance between optimization scheduling. Additionally, double-cycling operation mode U-shaped layout, known for their improved efficiency terminals, are gaining increasing attention hence incorporated into this study. It creates three-stage hybrid flow shop problem bi-directional flows, waiting time, uncertain time. To address complex problem, mixed integer programming model is proposed characterize an index based on network structure entropy designed evaluate anti-cascade effect well schedule. makespan serve bi-objectives, transforming bi-objective one. non-dominated sorting genetic algorithm-Ⅱ appropriate coding decoding rules utilized solve obtain set Pareto frontier solutions. feasibility verified through real case analysis. Specifically, comparative analysis basic stochastic programming, robust optimization, triangular fuzzy maximum gap used demonstrate effectiveness method. paper also provides insightful practical implications managers, genericity could contribute its values spreading wider scope beneficiaries, such manufacturing warehousing distribution management.

Language: Английский

---

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

Sustainability, Journal Year: 2022, Volume and Issue: 14(10), P. 6264 - 6264

Published: May 20, 2022

Energy efficiency has become a major concern for manufacturing companies not only due to environmental concerns and stringent regulations, but also large incremental energy costs. Energy-efficient scheduling can be effective at improving thus reducing consumption associated costs, as well pollutant emissions. This work reviews recent literature on energy-efficient in job shop systems, with particular focus metaheuristics. We review 172 papers published between 2013 2022, by analyzing the floor type, strategy, objective function(s), newly added problem feature(s), solution approach(es). report existing data sets make them available research community. The paper is concluded pointing out potential directions future research, namely developing integrated approaches interconnected problems, fast metaheuristic methods respond dynamic hybrid big cyber-physical production systems.

Language: Английский

---

Port integrated scheduling under uncertain operation time and cascade effects: A complex network structure entropy solution

Computers & Industrial Engineering, Journal Year: 2023, Volume and Issue: 182, P. 109435 - 109435

Published: July 8, 2023

Language: Английский

---