Optimal solution for a cargo revenue management problem with allotment and spot arrivals

We consider a single-leg cargo revenue management problem, in which a two-dimensional cargo capacity is sold through allotment contracts and in the spot market. Capacity sold on an allotment basis is guaranteed. We optimally solve the problem of determining how much of the total weight and volume capacity to sell on an allotment basis, by deriving a closed-form expression of the objective function. We provide numerical examples of industry-size problems and perform sensitivity analysis by changing some problem parameters. The sensitivity analysis illustrates the dependency of the optimal decisions on the spot and allotment booking types. The remaining capacity is then sold over a booking horizon in the spot market. Allotment bookings and spot requests can arrive any time over the booking horizon. Since some of the allotment bookings might not show up at departure, cargo carriers tend to overbook the remaining capacity allocated to spot requests. For these requests, we formulate a discrete-time dynamic capacity control model, to decide which of the spot requests to accept, based on the total weight and volume of the allotment show-ups and spot bookings accepted at the time of an arrival. We solve the exact dynamic programming model for medium-size industry problems. Since the booking policy based on critical booking levels or time periods is not optimal, we propose several heuristics to solve large industry problems and derive an upper bound on the value function. We test their performance via simulation against the optimal solution, the upper bound, and the first-come first-served policy, and recommend a heuristic that performs well in a wide variety of numerical cases. Finally, we show via simulation, that our model outperforms the one existing in the literature, for small and medium-size industry problems.     

A Linear Programming approach for robust network revenue management in the airline industry

The classical revenue management problem consists of allocating a fixed network capacity to different customer classes, so as to maximize revenue. This area has been widely applied in service industries that are characterized by a fixed perishable capacity, such as airlines, cruises, hotels, etc.It is traditionally assumed that demand is uncertain, but can be characterized as a stochastic process (See Talluri and van Ryzin (2005) for a review of the revenue management models). In practice, however, airlines have limited demand information and are unable to fully characterize demand stochastic processes. Robust optimization methods have been proposed to overcome this modeling challenge. Under robust optimization framework, demand is only assumed to lie within a polyhedral uncertainty set (Lan et al. (2008); Perakis and Roels (2010)).In this paper, we consider the multi-fare, network revenue management problem for the case demand information is limited (i.e. the only information available is lower/upper bounds on demand). Under this interval uncertainty, we characterize the robust optimal booking limit policy by use of minimax regret criterion. We present an LP (Linear Programming) solvable mathematical program for the maximum regret so our model is able to solve large-scale problems for practical use. A genetic algorithm is proposed to find the booking limit control to minimize the maximum regret. We provide computational experiments and compare our methods to existing ones. The results demonstrate the effectiveness of our robust approach.     

Mixed logit analysis of trade-off effects between international airline fares and fences: a revenue management perspective

As transportation is essential for tourism development, effectively utilizing its perishable resources has become an important issue. This study aims to analyse the relationship between airline fares and using conditions from the perspective of millennial tourists and taking the Taipei–Tokyo market as an example. The study attempts to show a revenue management practice in the manipulation of homogeneous seat service and give millennial tourists a better understanding of their preferences for ticket choices. We categorize availability of flight, advance booking, ticket validity, and changing conditions as main attributes and develop a stated-preference questionnaire with multiple hypothetical scenarios for respondents to select in the experiment. We effectively collect 390 valid samples for a mixed logit analysis and the results show that all applied attributes are statistically significant. Ticket validity is revealed to be the most important fence with the largest willingness-to-pay value and followed by availability of flight, advanced booking, and changing conditions.     

Improved approaches to the network design problem in regional hazardous waste management systems

This paper investigates the network design problem arising from the regional hazardous waste management system. The problem is to identify the locations of various waste facilities, and determine the transportation routes of hazardous wastes and waste residues between those waste facilities. Aiming at minimizing jointly the total cost and total risk, the problem is formulated as a multi-objective mixed integer linear programming model. By exploiting the advantages of the model, three multi-objective optimization approaches are customized to find highly qualified non-dominated solutions. The effectiveness and efficiency of the approaches are examined both on a hypothetical case and a realistic case.     

A decomposition scheme for large-scale Service Network Design with asset management

In this paper, we address a large-scale freight transportation problem for maximizing the profit of a carrier. We propose two solving algorithms using a decomposition of the problem into three main steps: construction of the network, filling vehicles with commodities and construction of the vehicle plannings. The resolution of these steps involves heuristic schemes, Mixed Integer Programming and Constraint Programming techniques. To evaluate the model and the solution algorithms, we produce instances based on a study of real-life data. The results show that the methods without transhipment provide solutions with a good computation time/quality trade-off.     

Relevance of route and network profitability analysis for the network management process of network carriers

Route profitability analysis (RPA) and network profitability analysis (NPA) represent common approaches to measure the profitability of flights in the airline industry. Scientific discussion, however, lacks an in-depth understanding of their impact on the network management process or of their implementation throughout the industry and their design. Here we analyze RPA and NPA and evaluate their potential influence on network management-related decision making. We argue that both approaches vary in applicability and suitability according to airline business models (i.e. network carriers, point-to-point carriers). Furthermore, we present the findings of a study among the top 100 network carriers worldwide on the relevance of RPA and NPA. Results indicate a wide implementation of RPA and to a lesser degree of NPA. In addition, the sophistication of the profitability analysis and the application of the retrieved profitability data for planning purposes differ considerably between airlines.     

建立计算机管理系统 提高机车检修质量

山海关机务段针对传统质量管理手段和机车检修方法存在管理方法落后、检测手段落后和考核机制滞后等弊端,建立机车检修质量计算机管理系统。该系统具有收集处理检修质量信息,提供质量分析、定责、考核依据,强化配件检修质量及检修质量控制等功能,促进了机车质量稳步提高,为旅客列车安全正点运行提供了有力保障,为运输畅通和增运增收发挥了重要作用。     

Estimating the impact of COVID-19 on air travel in the medium and long term using neural network and Monte Carlo simulation

The COVID-19 pandemic has had a substantial impact on the airline industry. Air travel in the United States declined in 2020 with significantly lower domestic and international flights. The dynamic change and uncertainty in the trend of COVID-19 have made it difficult to predict future air travel. This paper aims at developing and testing neural network models that predict domestic and international air travel in the medium and long term based on residents' daily trips by distance, economic condition, COVID-19 severity, and travel restrictions. Data in the United States from various sources were used to train and validate the neural network models, and Monte Carlo simulations were constructed to predict air travel under uncertainty of the pandemic and economic growth. The results show that weekly economic index (WEI) is the most important predictor for air travel. Additionally, daily trips by distance play a more important role in the prediction of domestic air travel than the international one, while travel restrictions seem to have an impact on both. Sensitivity analysis results for four different scenarios indicate that air travel in the future is more sensitive to the change in WEI than the changes in COVID-19 variables. Additionally, even in the best-case scenario, when the pandemic is over and the economy is back to normal, it still takes several years for air travel to return to normal, as before the pandemic. The findings have significant contributions to the literature in COVID-19's impact on air transportation and air travel prediction.     

Performance measurement of a transportation network with a downtown space reservation system: A network-DEA approach

We propose an evaluation approach for a novel travel demand management strategy known as the downtown space reservation system (DSRS). This approach takes into account three perspectives, i.e., transportation service provider’s, the user’s, and the community’s and is based on network-Data Envelopment Analysis (DEA) where the perspectives are inter-related through intermediate inputs/outputs. Two types of network-DEA models (radial and slacks-based models) are considered. An example is provided using data propagated from a microscopic traffic simulation model of the DSRS. The results show that individual node performance can drive network DEA performance and that this information can inform future designs of the DSRS.     

A multi-criteria analysis framework including environmental and health impacts for evaluating traffic calming measures at the road network level

Recent interests in both vehicle emissions and public health have facilitated the development of more eco-friendly transportation systems. This study developed a multi-criteria evaluation framework to evaluate the effectiveness of traffic calming measures (TCMs) from the various perspectives at the road network level; operational efficiency, traffic safety, environmental and health impacts. The proposed methodology employs four-step sequential simulation experiments, including driving, traffic flow, emissions, and air dispersion simulations. The results obtained from these four simulations are used to evaluate the effectiveness in terms of safety and operational efficiency in addition to environmental and health impacts. A multi-criteria value function based on the weights estimated from the analysis of an analytical hierarchy process (AHP) is applied in the evaluation framework. As an application, chicanes and speed humps widely implemented in Korean school zones were evaluated at the road network level. The proposed simulation-based approach is expected to be effectively used for the decision-making process in selecting better alternatives for TCM.     

A robust optimization approach for the road network daily maintenance routing problem with uncertain service time

This paper studies the robust optimization approach for the routing problem encountered in daily maintenance operations of a road network. The uncertainty of service time is considered. The robust optimization approach yields routes that minimize total cost while being less sensitive to substantial deviations of service times. A robust optimization model is developed and solved by the branch-and-cut method. In computational experiments, the behavior of the robust solutions and their performance are analyzed using Monte Carlo simulation. The robust optimization model is also compared with a classic chance-constrained programming model. The experimental analysis provides managerial insights for decision makers to determine an appropriate routing strategy.     

An analysis of traveler need for and willingness to purchase airline dynamic packaging: A Korean case study

This study analyzes (1) the need among air travelers for commission-based ancillary products and services from airline websites via dynamic packaging and (2) the willingness to purchase them. For this purpose, a survey is conducted with 2030 airline customers in Korea. This study aims to provide insights into Korean traveler preference to enable airlines serving Korean customers to formulate and implement successful business strategies that incorporate dynamic packaging into airline websites to expand ancillary revenues. The results confirm that Korean travelers demonstrate the need for and willingness to purchase commission-based ancillaries when purchasing tickets from airlines. On average, commission-based ancillary products are positively received by respondents. Airport transfers (e.g. rail and shuttle services), foreign currency exchange offers, and travel insurance are the most popular. Female travelers, travelers in their 20s, and frequent travelers (10 + times a year) report a significantly higher need for and willingness to purchase a set of commission-based ancillaries with flights from airline websites. Willingness to purchase third-party products from airlines is higher than in previous studies, and the preference rankings also differ. This study supports the viability of commission-based ancillary offerings from airline websites targeting Korean travelers. It shows the potential for airlines to successfully upsell and cross-sell via dynamic packaging strategies, one of the first steps toward becoming competitive travel retailers.     

A classification framework and management approach for the sustainable use of natural assets used for tourism

There is growing concern internationally about how best to sustainably manage natural assets used by tourists. Existing approaches lack a coherent framework around which like‐assets can be clustered and managed consistently. In this paper we propose an integrated framework which provides for a simple‐to‐use asset classification system, management guidelines based on the relationship between importance and fragility of the asset, and a set of indicators based on the pressure–state–response model for monitoring management progress. Copyright © 2004 John Wiley & Sons, Ltd.     

关于铁路工程项目造价控制与管理审计的思考

铁路工程项目造价的控制与管理是一个动态过程,审计部门应根据铁路工程项目建设的不同阶段,有重点地实施全过程的审核与评价。通过对铁路工程项目建设各阶段的审核与评价,促进决策部门、设计单位、建设单位、施工单位等加强对铁路工程项目造价的控制与管理,使铁路工程项目造价确实得到有效的控制,避免铁路工程项目＂初设超可研、实施超概算、决算超预算＂现象的发生,从而不断提高铁路工程项目建设的管理水平和投资效益。     

Spatial structure and network behaviour of strategic airline groups: A comparison between Europe and the United States

The Gini-index has gained in legitimacy when measuring traffic distributions of air traffic as compared to other more established measures, such as Herfindahl's. In order to render the index more meaningful for policy-makers, a partial decomposition into strategic groups of airlines along distinct geopolitical scopes of air traffic is suggested. Air traffic across airports is considered an aggregate of complex networks that are subject to multiple constraints, such as geopolitics or technology. A multi-layered analytic approach accounts for network operators as economic agents that behave in strategic ways within these constraints. Our approach allows for comparing traffic distributions in Europe with that of the US and, in particular, introduces a normative component by isolating patterns in airlines’ strategies that are likely to induce different degrees of spatial concentration and balanced traffic distributions within these common markets.     

铁路运输客货管理机制的探讨

随着我国加入WTO和铁路全面参与运输市场竞争,必须尽快构建适应市场需求的铁路客货管理的动力机制和运作机制,以激发企业和员工搞好营销的内在活力,同时要构建铁路客运和货运的服务质量评价指标,以及相应的质量监督和考核管理办法,做到各项管理活而不乱、管而不死,使铁路客货运输服务质量不断提高,以满足不断增长的经济和社会发展需要。     

发挥直管优势推进管理创新为实现路局又好又快发展注入强大合力

探索铁路局直管站段新体制下的企业管理模式,发挥运输部门的专业管理优势,强化综合部门的服务管理职能,加强企业管理,强化制度创新,推进管理创新,促进铁路的改革和发展.     

德国铁路货运公司运营管理简况

德国铁路货运公司在2001年进行了2次组织机构调整,使公司部门设置能更好地适应市场发展的需要,同时进一步加强了公司部门间的联系与配合。主要介绍了德国铁路货运公司2001年的运营指标情况,客户服务中心的服务内容和工作程序,公司的运价体系结构,以及发展联合运输和物流运输的情况。     

2-Stage stochastic programming approach for hub location problem under uncertainty: A case study of air network of Iran

In this paper 2-stage stochastic programming has been developed for formulating stochastic uncapacitated multiple allocation hub location problem. This problem is studied under three cases. The first, stochastic demand, the second, stochastic transportation cost and the third, integrated stochastic, which is compounded of first and second cases. A case of air network in Iran is used to evaluate proposed formulations and computational results obtained by GAMS are presented. The results show that considering uncertainty into formulation could cause in different solutions.     

A complex network approach towards modeling and analysis of the Australian Airport Network

An airport network forms the backbone of any air transportation system. The relationships among the origins and destinations of flights result in a complex network of routes which can be complemented with information associated with the routes themselves, for instance, traffic load and distance. In this paper, we modeled the Australia's civil domestic airport infrastructure as a network and analyzed the resulting network structure and its features using complex network tool. This case study identifies and investigates complex network measures, such as the degree distribution, characteristics path length, clustering coefficient and centrality measure as well as the correlations among them to understand the topology of an airport network. This analysis of the Australian Airport Network (AAN) indicates that it has a cumulative degree distribution described by the power-law function. As it has an average path length of 2.90, it is considered to have small-world properties. It is also found that it has a clustering coefficient of 0.50 which is higher than that of a random network of the same size which indicates that the transitivity and cohesiveness of AAN is different from a random network. In contrast to the World-wide Airport Network (WAN), the AAN is found to have disassortative mixing similar to the airport networks of China and India.