خلاصة:
In this paper, we study the problem of integrated capacitated hub location problem and seat inventory control considering concept and techniques of revenue management. We consider an airline company maximizes its revenue by utilizing the best network topology and providing proper booking limits for all itineraries and fare classes. The transportation system arises in the form of a star/star network and includes both hub-stop and non-stop flights. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. We solve various instances carried out from the Turkish network data set. Due to the NP-hardness of the problem, we propose a hybrid optimization method, consisting of an evolutionary algorithm based on genetic algorithm and exact solution. The quality of the solutions found by the proposed meta-heuristic is compared with the original version of GA and the mathematical programming model. The results obtained by the proposed model imply that integrating hub location and seat inventory control problem would help to increase the total revenue of airline companies. Also, in the case of serving non-stop flights, the model can provide more profit by employing less number of hubs.
ملخص الجهاز:
"The main idea of this method was proposed by Kek et al [2008] and also, Eidi & AbdulRahimi (2012) applied this idea to solve vehicle routing problem in multi-depot and multi-period.
The objective of these researchers is to optimize a set of routes for vehicle in order to serve all customers in their defined time windows and as a result, the travelled distance and the transportation cost are reduced by considering the earliest and the latest arrival times without violating the capacity of vehicles.
Yu & Yang (2011) began to solve periodic vehicle routing problem with time windows by meta-heuristic ant colony algorithm.
Here, we propose: hypotheses, indexes, decision making variables and the mathematical model of the multi-depot vehicle routing problem by considering time windows.
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