A flower pollination algorithm for flexible job shop scheduling with fuzzy processing time

2018 ◽  
Vol 32 (34n36) ◽  
pp. 1840113 ◽  
Author(s):  
Wenhao Xu ◽  
Zhicheng Ji ◽  
Yan Wang
Keyword(s):  
Processing Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Triangular Fuzzy Number ◽  
Flower Pollination Algorithm ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Shop Scheduling ◽  
Flower Pollination ◽  
Fuzzy Processing Time

Considering the uncertainty in real manufacturing workshops, the fuzzy flexible job shop scheduling problem (fFJSP) is addressed, in which the triangular fuzzy number is used to represent the processing time. A discrete flower pollination algorithm (DFPA) is proposed in this paper to minimize the maximum fuzzy completion time. Flower pollination algorithm (FPA) is inspired by the pollination process of flowering plants, which realizes global search and local search by means of cross-pollination and self-pollination of flowers in nature. DFPA extends to FPA by introducing discrete operator during iterations. Simulation results on instances validate the effectiveness and feasibility of this algorithm compared with particle swarm optimization.

scholarly journals Flexible Job Shop Scheduling using Software

2020 ◽  
Vol 9 (3) ◽  
pp. 67-70 ◽  
Keyword(s):  
Processing Time ◽  
Job Shop ◽  
Job Shop Scheduling ◽  
Flow Time ◽  
Critical Ratio ◽  
Flexible Job Shop ◽  
Flexible Job Shop Scheduling ◽  
Priority Rules ◽  
Shop Scheduling ◽  
Programming Package

This present paper speaks about Flexible Job Shop scheduling Problem using a software. Flexible Job shop scheduling is most typical and complex manufacturing environments in production planning issues. A case study was conducted on a manufacturing business set in Vijayawada. Information collected from the producing company to get the time taken by the conventional scheduling method and gathered data for 5 jobs requiring 8 machines that arrived during the analysis period. The Project additionally speaks about the study of varied programming strategies, learning of LEKIN programming package is a software tool has a flexibility to develop new heuristic models to produce effective schedules be applied practically. Input data, taken from the manufacturing company, converted to tables and routing sequences. The LEKIN programming package [3], develops the different schedules for given data with reference to priority rules, such as First Come First Serve (FCFS), Longest Processing Time (LPT), Shortest Processing Time (SPT), Earliest Due Date (EDD), Critical Ratio (CR) [6]. The schedules obtained from priority rules analysed through performance measures like Make Span, No of late jobs, Total Flow Time, Total Tardiness, Maximum Tardiness, Total Weighted Tardiness, Total Weighted Flow Time. Our goal is to come up with a optimized schedule with in the process of flexible job shop scheduling by using LEKIN scheduling software, using various priority rules as mentioned above and to minimize the make span i.e. the time length of the schedule, during which all the operations for all jobs is completed in an engineering company

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