scholarly journals A chance-constrained programming model for airport ground movement optimisation with taxi time uncertainties

2021 ◽  
Vol 132 ◽  
pp. 103382
Author(s):  
Xinwei Wang ◽  
Alexander E.I. Brownlee ◽  
Michal Weiszer ◽  
John R. Woodward ◽  
Mahdi Mahfouf ◽  
...  
Keyword(s):  
Programming Model ◽  
Ground Movement ◽  
Chance Constrained Programming ◽  
Constrained Programming

A Fuzzy Programming Model of Supplier Selection

2012 ◽  
Vol 468-471 ◽  
pp. 668-673 ◽  
Author(s):  
Hua Jiang ◽  
Zhi Gang Lu
Keyword(s):  
Supplier Selection ◽  
Programming Model ◽  
Fuzzy Programming ◽  
Chance Constrained Programming ◽  
Hybrid Intelligent Algorithm ◽  
Fuzzy Variables ◽  
Fuzzy Expected Value ◽  
Order Quantities ◽  
Constrained Programming ◽  
Fuzzy Programming Model

An integrated supplier selection problem under fuzzy environment is studied in this paper. Firstly, the linear weight method is used to calculate the scores of suppliers according to their different attributes, such as: quality, service, warranty, delivery, reputation and position, which are assumed as fuzzy variables. Secondly, a fuzzy expected value programming model and a fuzzy chance-constrained programming model are proposed to select the best combination of the suppliers and determine the order quantities. A hybrid intelligent algorithm, based on fuzzy simulation, genetic algorithm and neural network, is used to solve the two models. Finally, a numerical example is given to illustrate the effectiveness of the proposed models.

scholarly journals Uncertain Programming for Network Revenue Management

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Deyi Mou ◽  
Xiaoxin Wang
Keyword(s):  
Revenue Management ◽  
Programming Model ◽  
Chance Constrained Programming ◽  
Uncertain Programming ◽  
Network Revenue Management ◽  
Uncertain Variables ◽  
Inventory Control Problem ◽  
Constrained Programming ◽  
Seat Inventory Control ◽  
Network Revenue

The mathematical model for airline network seat inventory control problem is usually investigated to maximize the total revenue under some constraints such as capacities and demands. This paper presents a chance-constrained programming model based on the uncertainty theory for network revenue management, in which the fares and the demands are both uncertain variables rather than random variables. The uncertain programming model can be transformed into a deterministic form by taking expected value on objective function and confidence level on the constraint functions. Based on the strategy of nested booking limits, a solution method of booking control is developed to solve the problem. Finally, this paper gives a numerical example to show that the method is practical and efficient.

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