/pdf/convex-analysisnoer-san-nojin-zhan-nituite-5dl2rbmoyr.pdf

Convex Analysisの二,三の進展について

Introduction to linear and nonlinear programming

Remaining useful life estimation - A review on the statistical data driven approaches

A survey of maintenance policies of deteriorating systems

/pdf/sequencing-and-scheduling-algorithms-and-complexity-lnutyrr3kz.pdf

Sequencing and scheduling: algorithms and complexity

In this paper, we introduce robust versions of the classical static and dynamic single-leg seat allocation models. These robust models take into account the inaccurate estimates of the underlying probability distributions. As observed by simulation experiments, it turns out that for these robust versions the variability compared to their classical counterparts is considerably reduced with a negligible decrease in average revenue.

https://www.jstor.org/stable/info/40539133

The Role of Robust Optimization in Single-Leg Airline Revenue Management

For the problem of minimizing makespan on parallel machines of different speed, the behaviour of list scheduling rules is subjected to a probabilistic analysis under the assumption that the processing requirements of the jobs are independent, identically distributed nonnegative random variables. Under mild conditions on the probability distribution, we obtain strong asymptotic optimality results for the LPT Longest Processing Time rule, in which the jobs are assigned to the machines in order of nonincreasing processing requirements.

/pdf/the-asymptotic-optimality-of-the-lpt-rule-16ebiwe1nz.pdf

The asymptotic optimality of the LPT rule

Airline revenue management is concerned with identifying the maximum revenue seat allocation policies. Because a major loss in revenue results from cancellations and no-shows, overbooking has received significant attention in the literature over the years. In this study, we propose new static and dynamic single-leg overbooking models. In the static case we introduce two models: the first one aims to determine the overbooking limit and the second one is about finding the overbooking limit and the booking limits to allocate the virtual capacity among multiple fare classes. Because the second static model is hard to solve, we also introduce computationally tractable models that give upper and lower bounds on its optimal expected net revenue. In the dynamic case, we propose a dynamic programming model, which is based on two streams of events. The first stream corresponds to the arrival of booking requests and the second one corresponds to the cancellations. We conduct simulation experiments to illustrate the effectiveness of the proposed models.

/pdf/single-leg-airline-revenue-management-with-overbooking-2qyw0g963d.pdf

Single-Leg Airline Revenue Management with Overbooking

In this paper, we introduce several classes of generalized convex functions already discussed in the literature and show the relation between these classes. Moreover, a Gordan–Farkas type theorem is proved for all these classes and it is shown how these theorems can be used to verify strong Lagrangian duality results in finite-dimensional optimization.

https://www.econstor.eu/bitstream/10419/85720/1/97121.pdf

J. B. G. Frenk

Papers

The Role of Robust Optimization in Single-Leg Airline Revenue Management

The asymptotic optimality of the LPT rule

Single-Leg Airline Revenue Management with Overbooking

On classes of generalized convex functions, Gordan-Farkas type theorems, and Lagrangian duality

On equivalent results in minimax theory