Journal
APPLIED SOFT COMPUTING
Volume 131, Issue -, Pages -Publisher
ELSEVIER
DOI: 10.1016/j.asoc.2022.109783
Keywords
Flexible job shop scheduling problem; Grey processing time; Processing time extraction; Grey number; Elite genetic algorithm
Categories
Funding
- National Natural Science Foundation of China [72171116]
- Fundamental Research Funds for the Central Universities, China [NP2020022]
Ask authors/readers for more resources
This paper investigates a flexible job shop scheduling problem with uncertain processing time using generalized grey numbers. An elite genetic algorithm is developed to find excellent solutions and the experiments demonstrate the effectiveness and competitiveness of the proposed algorithm.
This paper investigates a flexible job shop scheduling problem with uncertain processing time. The uncertainty of the processing time is characterized by a generalized grey number. We extract general-ized grey numbers from limited information in real-world production, and then extend their operations for scheduling. With generalized grey numbers, the problem is formulated by a mathematical model to minimize the makespan. We develop an elite genetic algorithm for finding excellent solutions. The algorithm employs an elite strategy and neighborhood search method to search for promising individuals on the premise of ensuring population diversity. To assess the performance of the suggested methods, we construct 10 benchmark instances using generalized grey numbers. The results of the experiments demonstrate the effectiveness and competitiveness of the proposed algorithm and characterization. (c) 2022 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available