## 2 Literature Review  
In mixed-model assembly lines, planning problems can be grouped into two main categories: medium-long-term problems and short-term problems. The former category includes the design of the assembly line, line balancing, production planning, or materials procurement. The latter category can be further divided into three other sub-problems [10]:  
* Production sequencing: defining the best sequence of models for each production interval. * Material flow control: ensuring the timely release of parts from suppliers as well as the timely delivery of parts to the right assembly stations. * Resequencing: applying changes to the production sequence in case of disruptions. The parts feeding problem theoretically belongs to the material flow control sub-category. However, according to [11], the parts feeding problem ends up being strongly related also with the production sequencing and resequencing sub-categories. Moreover, all three short-term problems sub-categories show a clear dynamic time-dependence, which becomes even more critical when the adopted parts feeding policy is the station sequence, as shown in the Introduction. However, the literature has addressed the parts feeding problem in mixed model assembly lines mainly from a static perspective, neglecting the dynamic aspects and focusing instead on variables and parameters such as parts attributes, frequency of parts consumption, or parts cost. In practice, many contributions have adopted this perspective, starting from [12]. For a comprehensive literature review of parts feeding policy selection, it is possible to look at [13] as well as [14]. Qualitative factors, such as product and component volume, variety, and size, were adopted as policy selection criteria in [15]. Conversely, many other works adopted quantitative comparison models for the selection of the most appropriate parts feeding policy ([4; 6; 16; 17]). More recent examples include [18], which focused on the development of a cost model for kitting, Kanban, and line stocking, that was based on qualitative parts features: unit size and cost. Reference [19] developed a combined methodology, which starts with a hierarchical cluster analysis that is followed by an activity-based costing methodology, able to select the best-performing parts feeding system. Fewer works have attempted to integrate the study of parts feeding policies in mixed-model assembly lines with the inclusion of dynamic elements. The first contribution of this kind is [20], which proposed a two-stage heuristic procedure; in the first of the two stages,transportation orders were determined according to the expected part consumption rates. Reference [21] explored the optimal loading of tow trains from a Just-In-Time perspective. A mathematical model was developed with two objective functions, aimed at minimizing the number of bins at the stations and the number of surplus bins. A computational study was also conducted, introducing variability into elements such as parts demand or bin capacity. The results showed that increasing the delivery frequency reduces inventory or requires fewer wagons per train. This effect diminishes when delivery schedules become denser. Reference [10] focused on a paced mixed-model line. A mixed integer model was developed, and it was tested in a simulation scenario that included various dynamic elements of variability: three levels of problem instances (number of stations, models, and line sections), three degrees of parts variability, and two levels of load length of bins, buffer storage at the stations, size of unit loads and initial inventory at the stations. The results showed that the high variability of parts demand at the line stations, derived from the continuous changes in the daily production sequences, represents an additional difficulty in the management of station-sequence assembly lines. As a consequence, the exact timing of the material supply acquires even more importance.