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• We formulate the integer programming models for the stochastic dairy transportation problem. • We develop a heuristic algorithm based on the set-covering formulation. • We perform the numerical experiment to affirm that the solution algorithm is helpful for the dairy cooperatives. Based on the dairy cooperatives in Indonesia, this study formulates a stochastic programming model to handle the milk collection and delivery process with the maximum route duration limitation, the external cooling facility option, and travel time uncertainty. Besides, the local practice of sharing the fleet for both collection and delivery further complicates the decision. A set covering-based solution approach is used, due to its flexibility in handling complicated operational requirements and alignment with the decision environment. According to the numerical experiment, the proposed solution algorithm can provide quality solutions with a reasonable computational time for the cooperative operators. [ABSTRACT FROM AUTHOR]

For the airline fleet planning problem, this paper formulates a mathematical programming model specifically also taking into account of the increasingly popular capital lease, which has some mixed features of the two traditional aircraft acquirement methods: operating lease and purchase. Given the aircraft requirements, budget, and debt-ratio limit, the objective is to minimize the total cost within the planning horizon. Numerical experiments were conducted to compare the optimal solutions for the airlines with different business models, scales, and experiences. This paper further simulates a scenario under the new standards which will be applied in 2019. The results of sensitivity analysis show that when the debt-ratio constraint is relaxed, capital leases would be helpful for reducing the cost of airlines. [ABSTRACT FROM AUTHOR]

Abstract: The classic dynamic programming approach is not applicable to the airline network revenue management (RM) problem of a practical size due to the curse of dimensionality. Many heuristic methods, including the most popular bid-price control approach, generate the approximate control decisions based on various static formulations, which need to be re-solved to take into account the dynamic features of the problem. By a simulation experiment, this study examines the re-solving issue of the bid-price method and tests a new method, the parameterized function approach, in which no problem-resolving is required. Based on the results, the parameterized function approach is found to be a promising alternative. As for the bid-price control approach, a high re-solving frequency is needed for a good result. [Copyright &y& Elsevier]

Highlights: [•] We propose a transportation programming model considering various types of project interdependency. [•] We address the issue of regional balance with an approach based on set-covering formulation. [•] We develop an efficient solution algorithm employing the techniques of Lagrangian Relaxation. [ABSTRACT FROM AUTHOR]

Abstract: Since American Airlines successfully applied revenue management (RM) to raise its revenue, RM has become a common technique in the airline industry. Due to the current hub-and-spoke operation of the airline industry, the focus of RM research has shifted from the traditional single-leg problem to the network-type problem. The mainstream approaches, bid price and virtual nesting, are faced with some limitations such as inaccuracy due to their suboptimal nature and operation interruption caused by the required updates. This study developed an algorithm to generate a seat control policy by approximating the expected revenue function in a dynamic programming (DP) model. In order to deal with the issue of dimensionality for the DP model in a network context, this study used a suitable parameterized function and a sampling concept to achieve the approximation. In the numerical experiment, the objective function value of the developed algorithm was very close to the one achieved by the optimal control. We believe that this approach can serve as an alternative to the current mainstream approaches for the network RM problem for airlines and will provide an inspiring concept for other types of multi-resource RM problems. [Copyright &y& Elsevier]

Abstract: For the air cargo revenue management problem, this study developed a solution algorithm based on approximating the expected revenue function in the dynamic programming (DP) model while taking into account the stochastic volume and weight of shipments. In order to alleviate the computational load, the approximation was achieved by computing only a limited number of points in the DP state space. In the simulation experiment, the developed algorithm was compared with a recent heuristic algorithm based on de-coupling the relationship between weight and volume. It was found that the approach of this study can generate higher revenue than the de-coupling control for most of the cases. [Copyright &y& Elsevier]

Abstract: International air cargo is an operation-intensive industry, involving complex procedures and many players. As an important player, airfreight forwarders need to consolidate the collected goods skillfully in order to satisfy the requirements of the shippers and, at the same time minimize the expense charged by the airlines. However, the air cargo rate structure is very complicated, making the consolidation a difficult mixed-integer programming problem for the airfreight forwarder. In this paper, the consolidation problem is first transformed into a well-known set covering problem by treating a feasible consolidated shipment as a set. Lagrangian Relaxation is used as the backbone to develop a recursive heuristic algorithm. Based on the numerical experiment, the heuristic algorithm generates solutions very close to optimality. In particular, a sensitivity analysis is performed with respect to the degree of concavity. The results suggest that the solution algorithm can be used as a core module of the decision support system for air cargo consolidation. [Copyright &y& Elsevier]

A marine container terminal operator may have a situation with excessive calling requests to be served especially when some new service contracts are under consideration. For this situation, we propose a strategic berth template problem (BTPS) that selects the ships among the requesting ones to be served and arrange their berth-windows within a limited planning horizon. The BTPS employs the subgradient optimization procedure, which is an improved version of the procedure that the authors developed for the operational berth allocation problem. A wide variety of numerical experiments indicate the improved subgradient procedure works well for the BTPS. [ABSTRACT FROM AUTHOR]