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Article type: Research Article
Authors: Guodong, Yua | Yu, Yanga; * | Xi, Zhaob | Aijun, Liuc
Affiliations: [a] State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China | [b] Qingdao Cigarette Factor, China Tobacco Shandong Industrial Corporation, Qingdao, China | [c] Department of Supply Chain Management, W. P. Carey School of Business, Arizona State University, Arizona, USA
Correspondence: [*] Corresponding author. Yang Yu, State Key Laboratory of Mechanical Transmission, Chongqing University, Chongqing, China. yuyang@cqu.edu.cn
Abstract: Product collaborative design scheduling problem (PCDSP) has received increasing attention in the engineering field for its popularity in manufacturing and supply chain systems. Although many scholars have achieved many useful results in Job-shop scheduling problem (JSP), the research work of PCDSP is still lacking. Moreover, the fuzziness, dynamics and multi-objective of PCD pose a great challenge for enterprises making quick response to unplanned perturbations. Thus, in this paper, multi-objective dynamic fuzzy scheduling and its solution algorithm are presented. Emergencies cases are analyzed and dynamic scheduling procedure based on event-driven and lifecycle-driven is developed firstly. The fuzziness of PCD process is studied meanwhile fuzzy triangular number and fuzzy trapezoid number are used to express the fuzziness. Based on this, a multi-objective dynamic fuzzy scheduling model aiming to minimum the makespan and tardiness penalty is constructed. As a solution, multi-objective dynamic adaptive scheduling algorithm, based on bi-layer coding strategy and self-adaptive double point crossover and self-adaptive mutation, is proposed following closely. Finally, analytic results from a case of a wind turbine are used to illustrate the model and method proposed in this paper. With the analysis, it can provide insight into ways of improving the strategic and operational decision making for enterprises.
Keywords: Product collaborative design scheduling problem, fuzziness, dynamic scheduling, emergency, multi-objective optimization, algorithm
DOI: 10.3233/IFS-141491
Journal: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 4, pp. 1355-1365, 2015
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