A feedback learning-based selection hyper-heuristic for distributed heterogeneous hybrid blocking flow-shop scheduling problem with flexible assembly and setup time

Engineering Applications of Artificial Intelligence, Год журнала: 2024, Номер 131, С. 107818 - 107818

Опубликована: Янв. 9, 2024

Язык: Английский

---

A cooperative grey wolf optimizer for the joint flowshop scheduling problem with sequence-dependent set-up time

Engineering Optimization, Год журнала: 2024, Номер unknown, С. 1 - 23

Опубликована: Апрель 12, 2024

With the complexity involved in manufacturing products, many companies use multiple processes to complete product processing. Most studies have been concerned with single production but neglected widespread joint flowshop scheduling problem (JFSP). In this article, a cooperative grey wolf optimizer (CGWO) is developed solve JFSP. First, according features of JFSP, corresponding mathematical model constructed, and three collaborative strategies random generation are proposed initialize population. process searching for prey, discretized search prey update mechanism proposed, which conducive balancing exploration exploitation. An energy-saving strategy decrease energy consumption. Moreover, four local mechanisms different optimization objectives enhance performance method attacking prey. The results show that CGWO effective solving

Язык: Английский

---

Joint scheduling of AGVs and parallel machines in an automated electrode foil production factory

Expert Systems with Applications, Год журнала: 2023, Номер 238, С. 122197 - 122197

Опубликована: Окт. 17, 2023

Язык: Английский

---

Scheduling optimization for laminated door machining shop based on improved genetic algorithm

Computers & Operations Research, Год журнала: 2025, Номер unknown, С. 107078 - 107078

Опубликована: Март 1, 2025

Язык: Английский

---

Q-Learning-Driven Accelerated Iterated Greedy Algorithm for Multi-Scenario Group Scheduling in Distributed Blocking Flowshops

Knowledge-Based Systems, Год журнала: 2025, Номер unknown, С. 113424 - 113424

Опубликована: Март 1, 2025

Язык: Английский

---

Numerical optimal control for nonlinear dynamical systems involving mixed-valued inputs and joint probability path-constraints

Nonlinear Dynamics, Год журнала: 2024, Номер unknown

Опубликована: Окт. 19, 2024

Язык: Английский

---

Streamlined Supply Chain Operations: Leveraging Permutation-Based Genetic Algorithms for Production and Distribution

WSEAS TRANSACTIONS ON INFORMATION SCIENCE AND APPLICATIONS, Год журнала: 2023, Номер 21, С. 23 - 32

Опубликована: Дек. 27, 2023

Minimizing production and distribution costs by using resources in the most efficient way supply chain management is among fundamental objectives. In increasingly competitive conditions, companies can act more strongly market share with improvements cost efficiency factors. With proposed Permutation Based Genetic Algorithm (PBGA) approach, problem of optimizing line addressed. The algorithm uses processes selection, crossover, mutation to evolve population a permuted manner, taking into account multiple iterations, i.e. generation states. results from case studies also showed that resource utilization was realized efficiently reductions lead times. this study, savings were achieved applying PBGA method, especially information flow process optimization between production. This provide an advantage environment.

Язык: Английский

---

Intelligent optimisation for multi-objectives flexible manufacturing cells formation

Jurnal Sistem dan Manajemen Industri, Год журнала: 2024, Номер 8(1), С. 11 - 21

Опубликована: Июнь 4, 2024

The primary objective of conventional manufacturing cell formation typically uses grouping efficiency and efficacy measurement to reduce voids exceptional parts. This frequently leads extreme solutions, such as the persistently significant workload disparity among manu­facturing cells. It will have a detrimental psychological impact on operators who work in each formed cell. complexity problem increases when there is requirement finish all parts before midday break, at which point cells can proceed with following production batch after break. research examines using two widely recognized intelligent optimization techniques: genetic algorithm (G.A.) particle swarm optimisation (PSO). discussed system has flexible machines, allowing part multiple routing options. process involved addressing four simultaneous objectives: enhancing cells, minimizing deviation working time allocated hours, prior ensuring balanced for results demonstrate that G.A. outperforms PSO method capable providing solutions an level 0.86, high 0.64, achieving minimum lateness only 24 minutes from completion target break maximum difference low 49 minutes.

Язык: Английский

---

Optimization of Multibeam Survey Measurement Based on Greedy Algorithm

Highlights in Science Engineering and Technology, Год журнала: 2024, Номер 100, С. 95 - 101

Опубликована: Май 22, 2024

The effectiveness of multibeam bathymetric technology is widely recognized in marine depth measurements, especially areas with complex and variable seafloor topography. This study aims to design a survey plan for specific maritime region, the objectives minimizing total line length, ensuring comprehensive coverage target area, controlling overlap between adjacent lines, fully considering variations An optimization model was developed determine optimal route measurements within specified area.The initially considers influence slope, establishing single objective goal length. decision variables primarily include spacing lines. function reduce number thereby achieving minimization Constraints encompass limitations on range, calculations width, relationships solved using greedy algorithm-based approach, iteratively updating positions lines while determining based relationship width. Ultimately, layout shortest totaling 64 nautical miles configuration 32 obtained assumed area. Multibeam holds broad prospects field particularly characterized by study, designing not only contributes improving measurement efficiency accuracy but also reduces costs resource consumption. outcomes this research have significant practical implications development, engineering construction, environmental protection, providing professionals related fields an effective method strategy.

Язык: Английский

---

Optimization of task assignment for multi-farm multi-weeding robots based on discrete artificial bee colony algorithm

Expert Systems with Applications, Год журнала: 2024, Номер unknown, С. 126182 - 126182

Опубликована: Дек. 1, 2024

Язык: Английский

---