This paper considers the integrated order picking (joint order batching and picker routing) and delivery problem in a manual picker-to-parts and multi-block 3D warehouse with considering Overbooking and delivery-delay allowed strategies. Received orders by the customers are grouped into the batches, assigned to the pickers with horizontal and vertical velocities to compute the travel time, picked up from the shelves of the warehouse, and delivered to customers’ community. The warehouse’s policy is to accept orders for a certain number of unavailable products in addition to the available products. Thus, the concept of the Overbooking strategy for supplying unavailable products and the delivery postponed strategy for delayed delivery is applied. Hence, this study introduces a novel mathematical model to deal with such a system, where the objective aims to minimize the cost of the completion time of all batches, the purchasing of the unavailable products and the return time of all vehicles to the depot. To solve this model, four new heuristic algorithms are devised, a broad range of numerical experiments is investigated to illustrate the validity and applicability of the proposed model and solution approaches.

In the early stages of the COVID-19 pandemic, global supplies of vaccines were extremely tight, but some high-income countries (HICs) pre-ordered more vaccines than their nationals needed. We consider an entity overbook COVID-19 vaccines when the percentage of the national population that can be vaccinated with the pre-order vaccine reaches or exceeds 200% since most vaccines require only two doses, 1 and not everyone is suitable for vaccination. There are five such entities as of January 29, 2021 (Figure). The Overbooking of vaccines in HICs has led to complaints from other countries, . . . . . .

Overbooking flights are a common practice of the airline industry. This business practice aims at ensuring that airplanes fly at their full capacity. However, due to boilerplate contracts that bury the relevant clause, most passengers are shocked when they are denied boarding due to the lack of passenger capacity. This article looks at the legal aspects of Overbooking in three jurisdictions: Iran, France, and the U. S. It studies the legal basis of Overbooking in each jurisdiction and analyzes the remedies each system offers passengers. While the policy of ensuring a functioning airline industry requires the practice of Overbooking, states can provide a higher degree of legal protection for passengers. This article suggests that Iran's legal system must improve its current requirement for airlines' contracts of carriage. Providing a comprehensive guideline on the passengers' rights in case of Overbooking must become mandatory for airlines. It should also require airlines to be transparent about all of their policies and ensure that the Overbooking clause in the contract of carriage is as conspicuous as possible.

The use of revenue management models has been increased in various industries. The cause of such increasing is as a result of performance and profitability of these models in businesses. Hoteling industry is considered as an important business in the field of revenue management that has a reservation process and stochastic variables due to it. Classic Overbooking model is considered as a common model in revenue management that causes to make a trade-off between the number of present customers and no-show customers. This model makes a situation for studying the functions which describe costumers’ presence distribution in probable form and then we can add some customers to system for increasing revenue due to no-shows. In this research, the binomial probability distribution using in Overbooking model has been improved and estimated its probable parameter more accurately using artificial neural network as a tool in no-show estimation. This estimation is caused by fitting to effective indexes in show-up or no-show process using one-layer or multi-layer perceptron neural network. Therefore, a dynamic model for each sale and customers’ reservation is represented that it can estimate the probability parameter of customers’ show-up or no-show considering effective indexes.

The successful application of "revenue management" in airline industry motivated hotel industry management as well as some researchers to apply the concept and techniques of revenue management to enhance the income of hotels. In this paper, we develop a multi objective model for hotel management in stochastic environments. Since demand for rooms, and in some cases the supply, is random we introduce a robust model, in order to manage its uncertain parameters. Therefore, the objectives of the model are robustness as well as income enhancement. Furthermore, some other new assumptions such as Overbooking, early (or late) departure of a passenger and different prices are also included in the model.

To formulate a single-leg seat inventory control problem in an airline ticket sales system, the concept and techniques of revenue management are applied in this research. In this model, it is assumed that the cabin capacity is stochastic and hence its exact size cannot be forecasted in advance, at the time of planning. There are two groups of early-reserving and late-purchasing customers demanding this capacity. The price rate as well as the penalty for booking cancellation caused by Overbooking is different for each group. The model is developed mathematically and we propose an analytical solution method. The properties of the optimal solution as well as the behavior of objective function are also analyzed. The objective function is neither concave nor convex in general. However, we prove it is a unimodal function and by taking advantage of this property, the optimal solution is determined.