Freight Forwarder Selection And Capacity Management For Air Cargo Capacity

In the context of the growing global supply chain and the increasing world trade,the air freight industry has become one of the most important industries to support the development of economic globalization.As one main part of air cargo industry,airlines have formulated operational management strategies to enhance the utilization efficiency of freight capacity and optimize the operation structure of freight capacity.However,due to the complex international environment and the operational risk,designing a more stable capacity management strategy and cooperation mechanism for airlines is of great research value.Specifically,due to the competition between the other airlines and the collusion within freight forwarders,airlines often fail to get stable freight transport demand,resulting in inefficient utilization of freight capacity and potential loss.Therefore,it is necessary for the airline to design a strategy to choose forwarders as long-term partners to improve a stable long-term profit.On the other hand,because of the uncertainty of demand,fast updating of information and diverse sales means,airlines need to develop effective capacity management strategies to enhance efficiency to utilize cargo capacity and balance the benefits of different sales ways.This paper mainly launches the following three aspects of research work:Firstly,this paper proposes a decision-making method of selection of freight forwarders considering correlated cargo disruption.We formulate the freight forwarders selection problem as a two-stage stochastic program based on distributionally robust frame.Then we obtain the distribution of freight disruption in the worst case and simplify model.Then we propose an effective benders decomposition algorithm to solve this model.We also use a real case to select forwarders for airline.Secondly,this paper proposes a decision-making method of long-term capacity planning and spot sales for airlines.We first formulate the long-term capacity planning and spot sales problem as a two-stage stochastic program.For generalized price-demand function,we prove the optimality of spot sales model.For addictive demand function,we simplify the spot sales model and reformulate it as a convex program.In numerical experiment,we verify our conclusion and analyze optimal strategies.Last,this paper studies on decision method of air freight dynamic pricing strategy which using optimal regret value as objective function.We build a two stage robust pricing model to optimize the regret value.Then we prove that objective function is piece-wise linear function on each divided domain when support,quantile or mean of random factor in demand function is known.Based on that conclusion,we propose a polynomial time algorithm to solve dynamic pricing model and show its reliability and applicability in numerical experiments.