scholarly journals Scenario tree airline fleet planning for demand uncertainty

2017 ◽  
Vol 65 ◽  
pp. 198-208 ◽  
Author(s):  
Martijn G.J. Repko ◽  
Bruno F. Santos
2021 ◽  
Vol 13 (14) ◽  
pp. 7708
Author(s):  
Yiping Huang ◽  
Qin Yang ◽  
Jinfeng Liu ◽  
Xiao Li ◽  
Jie Zhang

In order to reduce the energy consumption of furnaces and save costs in the product delivery time, the focus of this paper is to discuss the uncertainty of demand in the rolling horizon and to globally optimize the sustainability of the production in the aluminum furnace hot rolling section in environmental and economic dimensions. First, the triples α/β/γ are used to describe the production scheduling in the aluminum furnace hot rolling section as the scheduling of flexible flow shop, satisfied to constraints of demand uncertainty, operation logic, operation time, capacity and demand, objectives of minimizing the residence time of the ingot in the furnace and minimizing the makespan. Second, on the basis of describing the uncertainty of demand in rolling horizon with the scenario tree, a multi-objective mixed integer linear programming (MILP) optimization model for sustainable production in the aluminum furnace hot rolling section is formulated. Finally, an aluminum alloy manufacturer is taken as an example to illustrate the proposed model. The computational results show that when the objective weight combination takes the value of α=0.7, β=0.3, the sustainability indicators of the environmental and economic dimensions can be optimized to the maximum extent possible at the same time. Increasingly, managerial suggestions associated with the trade-off between environmental and economic dimensions are presented. Scheduling in the rolling horizon can optimize the production process of the aluminum furnace hot rolling section globally, indicating that it is more conducive to the sustainable development of the environment and economic dimensions than scheduling in a single decision time period.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anton Ochoa Bique ◽  
Leonardo K. K. Maia ◽  
Ignacio E. Grossmann ◽  
Edwin Zondervan

Abstract A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.


2014 ◽  
Vol 505-506 ◽  
pp. 645-649
Author(s):  
Yu Wang

Traditional methods for determining airline fleet composition could not reflect the impact of network effects on fleet composition. To solve this problem for airlines operating in the mode of Hub & Spoke network, the passenger mix problem was incorporated into the model of determining airline fleet composition. The purchasing number of aircrafts in each fleet type, the frequencies of each aircraft type flying on legs and the spilling number of passengers from each itinerary were treated as decision variables. The limitations including maximum flying frequencies on each leg, available flying time each fleet type can provide and maximum passengers spilled from each flight leg were considered as constraints. A model to minimize the fleet planning cost was constructed. The numerical example shows that the fleet planning cost derived from this proposed model is 46266381.64 Yuan and reduces by 3914969.70 Yuan compared to the result from the traditional leg-based model. In hence, this proposed model is effective and feasible.


Omega ◽  
2020 ◽  
Vol 97 ◽  
pp. 102101
Author(s):  
Constantijn A.A. Sa ◽  
Bruno F. Santos ◽  
John-Paul B. Clarke

Transport ◽  
2018 ◽  
Vol 33 (3) ◽  
pp. 707-717
Author(s):  
Mo Zhu ◽  
Michael Chen ◽  
Murat Kristal

The maritime transport industry continues to draw international attention on significant Greenhouse Gas emissions. The introduction of emissions taxes aims to control and reduce emissions. The uncertainty of carbon tax policy affects shipping companies’ fleet planning and increases costs. We formulate the fleet planning problem under carbon tax policy uncertainty a multi-stage stochastic integer-programming model for the liner shipping companies. We develop a scenario tree to represent the structure of the carbon tax stochastic dynamics, and seek the optimal planning, which is adaptive to the policy uncertainty. Non-anticipativity constraint is applied to ensure the feasibility of the decisions in the dynamic environment. For the sake of comparison, the Perfect Information (PI) model is introduced as well. Based on a liner shipping application of our model, we find that under the policy uncertainty, companies charter more ships when exposed to high carbon tax risk, and spend more on fleet operation; meanwhile the CO2 emission volume will be reduced.


2015 ◽  
Vol 46 ◽  
pp. 30-39 ◽  
Author(s):  
Slavica Dožić ◽  
Milica Kalić

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yu Wang ◽  
Hong Sun ◽  
Jinfu Zhu ◽  
Bo Zhu

This paper presents a multiobjective mathematical programming model to optimize airline fleet size and structure with consideration of several critical factors severely affecting the fleet planning process. The main purpose of this paper is to reveal how multiairline competitive behaviors impact airline fleet size and structure by enhancing the existing route-based fleet planning model with consideration of the interaction between market share and flight frequency and also by applying the concept of equilibrium optimum to design heuristic algorithm for solving the model. Through case study and comparison, the heuristic algorithm is proved to be effective. By using the algorithm presented in this paper, the fleet operational profit is significantly increased compared with the use of the existing route-based model. Sensitivity analysis suggests that the fleet size and structure are more sensitive to the increase of fare price than to the increase of passenger demand.


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