The purpose of this study is to investigate the impact that unevenly allocating buffer capacity has on throughput and average buffer level regarding unreliable lines to better understand the relevant factors in supply chain design. Results show that the best patterns for unreliable merging lines in terms of generating higher throughput rates (TR), as compared to a balanced merging line counterpart, are those where total available buffer capacity is allocated between workstations in either an inverted bowl pattern (i.e. concentrating buffer capacity towards the centre of the line), or a balanced line pattern. In contrast, when considering the trade-off between generating revenue resulting from TR and reducing cost created by average buffer levels (ABL), we found that the balanced pattern was not the best pattern. The best pattern was dependent on the length of the line and on the total buffer capacity as shorter lines with very constrained buffers were best served with an inverted bowl pattern while longer lines had the best results when applying an ascending buffer allocation pattern. Longer lines, in contrast, had the best results regarding the trade-off between TR and ABL, on average, by allocating buffer capacity evenly in one of the parallel lines while applying any other pattern in the remaining parallel line.
LINK
Aviation increasingly faces capacity challenges exposing inefficiencies and shortcomings of aviation related processes and systems. The European slot allocation system was designed in an era with little to no capacity constraints, now resulting in regulations not fitting in today’s developments.
MULTIFILE
This study examines the effect of seat assignment strategies on the transfer time of connecting passengers at a hub airport. Passenger seat allocation significantly influences disembarkation times, which can increase the risk of missed connections, particularly in tight transfer situations. We propose a novel seat assignment strategy that allocates seats to nonpaying passengers after check-in, prioritising those with tight connections. This approach diverges from traditional methods focused on airline turnaround efficiency, instead optimizing for passenger transfer times and reducing missed connections. Our simulation, based on real-world data from Paris-Charles de Gaulle airport, demonstrates that this passenger-centric model decreases missed connections by 12%, enhances service levels, reduces airline compensation costs, and improves airport operations. The model accounts for variables such as seat occupancy,luggage, and passenger type (e.g., business, leisure) and is tested under various scenarios, including air traffic delays.
MULTIFILE
