Bilevel mixed-integer nonlinear programming for integrated scheduling in a supply chain network
An integrated scheduling problem under a make-to-order supply chain network is addressed. This problem considers integrated production and transportation scheduling with realistic supply chain features such as unrelated parallel shop and product batch-based transportation. The mathematical model for this problem is presented, which is formulated as a bilevel mixed-integer nonlinear program. A novel bilevel evolutionary optimization model based on memetic algorithm is proposed to resolve this problem because the problem is hard-to-tackle for mathematical programming techniques and traditional intelligent techniques. The effectiveness of the proposed optimization model is validated through a series of numerical experiments. The experimental results also confirmed that the proposed optimization model is superior to other three intelligent optimization models.
KeywordsMake-to-order supply chain scheduling Mixed integer nonlinear programming Bilevel programming Memetic algorithm Bilevel evolutionary algorithms
This paper is supported partly by the National Natural Science Foundation of China under Grant Nos. 71532007, 71131006 and 71172197.
Compliance with ethical standards
The authors declare that they have no competing interests.
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