Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/61078
Title: A bi-level evolutionary optimization approach for integrated production and transportation scheduling
Authors: Guo, Z
Zhang, D
Leung, SYS 
Shi, L
Keywords: Bi-level evolutionary algorithm
Bi-level programming
Production and distribution
Supply chain scheduling
Issue Date: 2016
Publisher: Elsevier
Source: Applied soft computing, 2016, v. 42, p. 215-228 How to cite?
Journal: Applied soft computing 
Abstract: This paper investigates an integrated production and transportation scheduling (IPTS) problem which is formulated as a bi-level mixed integer nonlinear program. This problem considers distinct realistic features widely existing in make-to-order supply chains, namely unrelated parallel-machine production environment and product batch-based delivery. An evolution-strategy-based bi-level evolutionary optimization approach is developed to handle the IPTS problem by integrating a memetic algorithm and heuristic rules. The efficiency and effectiveness of the proposed approach is evaluated by numerical experiments based on industrial data and industrial-size problems. Experimental results demonstrate that the proposed approach can effectively solve the problem investigated.
URI: http://hdl.handle.net/10397/61078
ISSN: 1568-4946
EISSN: 1872-9681
DOI: 10.1016/j.asoc.2016.01.052
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