A Tabu-Bi-label hybridized branch and price algorithm for just-in-time material handling scheduling problems of mixed-model assembly lines with electric vehicle recharging requirements

Driven by the highly-diversified customer demand, mixed-model automobile assembly lines (MMAALs) have been widely applied to enable the mass production of customized automobiles. Meanwhile, an inexorable trend in the green and sustainable production has promoted the optimization of material handling scheduling, which constitutes a large proportion of the energy consumption in the automobile production. Therefore, to deal with both manufacturing and energy issues, this article employed electric vehicles (EVs) and proposed a supermarket integrated MMAAL material handling scheduling problem under JIT settings with EV recharging requirements. A mixed integer linear programming model is consequently established, aiming to minimize the number of EVs for reducing cost as well as saving energy. In order to obtain the global optimal solution, a Tabu-Bi-Label Hybridized Branch and Price Algorithm (TBHBP) algorithm is developed, a heuristic Tabu Search algorithm is combined with a modified Bidirectional Labeling for achieving much faster speed while maintaining a high solution quality. Computational experiments on TBHBP along with a case study are carried out and compared with benchmark algorithms, the results of which verified the efficiency and effectiveness of TBHBP in dealing with the proposed problem.