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Academic Journal of Engineering and Technology Science, 2020, 3(8); doi: 10.25236/AJETS.2020.030809.

Optimization of remanufacturing flexible job shop scheduling under uncertain environment


Lingqiao Chen1,*, Gengjun Gao2

Corresponding Author:
Lingqiao Chen

1 Shanghai Maritime University Logistics Research Center, Shanghai 201306, China
2 Shanghai Maritime University Logistics Research Center, Shanghai 201306, China
*Corresponding Author


Aiming at the problem of uncertain parts processing time and delivery date in the scheduling of remanufacturing flexible job shops, triangular fuzzy numbers and trapezoidal fuzzy numbers are introduced to represent the uncertain processing time and delivery date respectively, and the maximum completion time is the minimum as the goal to establish a fuzzy model of workshop scheduling with the satisfaction constraint of the average delivery time of parts, and the model is transformed and finally solved by the MSOS coding genetic algorithm. And get: the positive or negative attitude of the decision maker will affect the decision result, the more negative the decision, the worse the result, on the contrary, the more positive the decision, the better the result; as the average delivery time satisfaction threshold gradually increases, the maximum completion time gradually extend.


fuzzy operation time, fuzzy delivery date, remanufacturing, flexible job shop scheduling, MSOS coding genetic algorithm

Cite This Paper

Lingqiao Chen, Gengjun Gao. Optimization of remanufacturing flexible job shop scheduling under uncertain environment. Academic Journal of Engineering and Technology Science (2020) Vol. 3 Issue 8: 77-89. https://doi.org/10.25236/AJETS.2020.030809.


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