Anomalies in Special Permutation Flow Shop Scheduling Problems

Gui, Lin; Gao, Liang; Li, Xinyu

doi:10.1186/s10033-020-00462-2

Cited by 9 publications

(6 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Then, the generated initial sequence was input into the SA for iteration. After each Assume that the sequence at this time is (5,4,3,6,8,7,9,2,1). Next, the neighborhood search described in Sect.…”

Section: Framework Of the Improved Saresmentioning

confidence: 99%

“…Although these meta-heuristic algorithms have some advantages, the solution quality may be poor and the computation time may be long when dealing with the large-scale and complex PFSPs [7]. Because, the previous historical data cannot be used to mine the variation rules of scheduling, especially for large-scale and complex problems, which may fail to achieve good results, and the calculation time will increase exponentially [13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An improved simulated annealing algorithm based on residual network for permutation flow shop scheduling

Wang

Gao

et al. 2020

Complex Intell. Syst.

Self Cite

View full text Add to dashboard Cite

The permutation flow shop scheduling problem (PFSP), which is one of the most important scheduling types, is widespread in the modern industries. With the increase of scheduling scale, the difficulty and computation time of solving the problem will increase exponentially. Adding the knowledge to intelligent algorithms is a good way to solve the complex and difficult scheduling problems in reasonable time. To deal with the complex PFSPs, this paper proposes an improved simulated annealing (SA) algorithm based on residual network (SARes). First, this paper defines the neighborhood of the PFSP and divides its key blocks. Second, the Residual Network (ResNet) is used to extract and train the features of key blocks. And, the trained parameters are stored in the SA algorithm to improve its performance. Afterwards, some key operators, including the initial temperature setting and temperature attenuation function of SA algorithm, are also modified. After every new solution is generated, the parameters trained by the ResNet are used for fast ergodic search until the local optimal solution found in the current neighborhood. Finally, the most famous benchmarks including part of TA benchmark are selected to verify the performance of the proposed SARes algorithm, and the comparisons with the-state-of-art methods are also conducted. The experimental results show that the proposed method has achieved good results by comparing with other algorithms. This paper also conducts experiments on network structure design, algorithm parameter selection, CPU time and other problems, and verifies the advantages of SARes algorithm from the aspects of stability and efficiency.

show abstract

Section: Framework Of the Improved Saresmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An improved simulated annealing algorithm based on residual network for permutation flow shop scheduling

Wang

Gao

et al. 2020

Complex Intell. Syst.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The jumping mechanism consists of a pair of legs, each with two equal segments mimicking the femur and tibia, joined by torsion springs. The robot can jump to a height of 3.1 m covering a distance of 3 m. In addition, one-DOF fourbar [5][6][7][8] or six-bar mechanisms [9][10] are used in the leg design of jumping robots. Given that they are plane mechanisms when the frame is fixed, this type of jumping robot can only achieve efficient jumping in a plane.…”

Section: Introductionmentioning

confidence: 99%

Realization Method of Stable Continuous Steering Jumping for a Bioinspired Jerboa Robot

Zhang,

Wang,

et al. 2023

Advcd Theory and Sims

View full text Add to dashboard Cite

The continuous jumping of bioinspired robots in 3D spaces can greatly improve its motion flexibility, which is one of the highlights of research on jumping robots. However, most existing jumping robots can only move in a plane, and achieving stable continuous steering jumping is difficult. In this study, a realization method of stable continuous steering jumping for a bioinspired jerboa robot is proposed. On the basis of the jumping mechanism of the jerboa, the robot mechanism model is established, and the factors affecting motion feasibility and performance are analyzed in detail. Then, mathematical models of the stability indices of the robot jumping on uneven ground with redundant driving are established. Based on the proposed improved bee colony algorithm, the motion parameters and driving parameters can be determined. Simulation results show that the robot can realize stable continuous steering jumping in different terrains along the expected trajectory, thus proving the feasibility of the method proposed in this study. This study provides a theoretical reference for the high‐speed flexible motion of legged robots in 3D spaces.

show abstract

“…The importance of production scheduling problem and transportation scheduling problem has been emphasized by many researchers [7][8][9][10][11]. For the literatures of production scheduling problem in hybrid flow shop (also called HFSP), most of the researchers didn't consider the transport procedure between machines or put it as fixed value into the setup time.…”

Section: Introductionmentioning

confidence: 99%

Integrated Production and Transportation Scheduling Method in Hybrid Flow Shop

Han

Gao

et al. 2022

Chin. J. Mech. Eng.

Self Cite

View full text Add to dashboard Cite

The connection between production scheduling and transportation scheduling is getting closer in smart manufacturing system, and both of those problems are summarized as NP-hard problems. However, only a few studies have considered them simultaneously. This paper solves the integrated production and transportation scheduling problem (IPTSP) in hybrid flow shops, which is an extension of the hybrid flow shop scheduling problem (HFSP). In addition to the production scheduling on machines, the transportation scheduling process on automated guided vehicles (AGVs) is considered as another optimization process. In this problem, the transfer tasks of jobs are performed by a certain number of AGVs. To solve it, we make some preparation (including the establishment of task pool, the new solution representation and the new solution evaluation), which can ensure that satisfactory solutions can be found efficiently while appropriately reducing the scale of search space. Then, an effective genetic tabu search algorithm is used to minimize the makespan. Finally, two groups of instances are designed and three types of experiments are conducted to evaluate the performance of the proposed method. The results show that the proposed method is effective to solve the integrated production and transportation scheduling problem.

show abstract

Anomalies in Special Permutation Flow Shop Scheduling Problems

Cited by 9 publications

References 32 publications

An improved simulated annealing algorithm based on residual network for permutation flow shop scheduling

An improved simulated annealing algorithm based on residual network for permutation flow shop scheduling

Realization Method of Stable Continuous Steering Jumping for a Bioinspired Jerboa Robot

Integrated Production and Transportation Scheduling Method in Hybrid Flow Shop

Contact Info

Product

Resources

About