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Coordinated scheduling of production and transportation in a two-stage assembly flowshop

Author:  WANG Kai(Department of Management Science and Engineering)¡¢ MA Wenqiong¡¢HaoLuo¡¢HuQin
Publication:  International Journal of Production Research, 54(22), 6891-6911
Abstract:  To enhance the overall performance of supply chains, coordination among production and distribution stages has recently received an increasing interest. This paper considers the coordinated scheduling of production and transportation in a two-stage assembly flowshop environment. In this problem, product components are first produced and assembled in a two-stage assembly flowshop, and then completed final products are delivered to a customer in batches. Considering the NP-hard nature of this scheduling problem, two fast heuristics (SPT-based heuristic and LPT-based heuristic) and a new hybrid meta-heuristic (HGA-OVNS) are presented to minimise the weighted sum of average arrival time at the customer and total delivery cost. To guide the search process to more promising areas, the proposed HGA-OVNS integrates genetic algorithm with variable neighbourhood search (VNS) to generate the offspring individuals. Furthermore, to enhance the effectiveness of VNS, the opposition-based learning (OBL) is applied to establish some novel opposite neighbourhood structures. The proposed algorithms are validated on a set of randomly generated instances, and the computation results indicate the superiority of HGA-OVNS in quality of solutions.

¡¡¡¡¡¾Keywords¡¿scheduling; assembly flowshop; genetic algorithms; variable neighbourhood search; opposition-based learning