A stochastic programming winner determination model for truckload procurement under shipment uncertainty

We propose a two-stage stochastic integer programming model for the winner determination problem (WDP) in combinatorial auctions to hedge the shipper’s risk under shipment uncertainty. The shipper allows bids on combinations of lanes and solves the WDP to determine which carriers are to be awarded lanes. In addition, many other important comprehensive business side constraints are included in the model. We demonstrate the value of the stochastic solution over one obtained by a deterministic model based on using average shipment volumes. Computational results are given that indicate that moderately sized realistic instances can be solved by commercial branch and bound solvers in reasonable time.     

A stochastic programming approach for floods emergency logistics

This article presents a model to assist decision makers in the logistics of a flood emergency. The model attempts to optimize inventory levels for emergency supplies as well as vehicles’ availability, in order to deliver enough supplies to satisfy demands with a given probability. A spatio-temporal stochastic process represents the flood occurrence. The model is approximately solved with sample average approximation. The article presents a method to quantify the impact of the various intervening logistics parameters. An example is provided and a sensitivity analysis is performed. The studied example shows large differences between the impacts of logistics parameters such as number of products, number of periods, inventory capacity and degree of demand fulfillment on the logistics cost and time. This methodology emerges as a valuable tool to help decision makers to allocate resources both before and after a flood occurs, with the aim of minimizing the undesirable effects of such events.     

Exploring the network structure and nodal centrality of China’s air transport network: A complex network approach

This paper uses a complex network approach to examine the network structure and nodal centrality of individual cities in the air transport network of China (ATNC). Measures for overall network structure include degree distribution, average path length and clustering coefficient. Centrality metrics for individual cities are degree, closeness and betweenness, representing a node’s location advantage as being directly connected to others, being accessible to others, and being the intermediary between others, respectively. Results indicate that the ATNC has a cumulative degree distribution captured by an exponential function, and displays some small-world (SW) network properties with an average path length of 2.23 and a clustering coefficient of 0.69. All three centrality indices are highly correlated with socio-economic indicators of cities such as air passenger volume, population, and gross regional domestic product (GRDP). This confirms that centrality captures a crucial aspect of location advantage in the ATNC and has important implications in shaping the spatial pattern of economic activities. Most small and low-degree airports are directly connected to the largest cities with the best centrality and bypass their regional centers, and therefore sub-networks in the ATNC are less developed except for Kunming in the southwest and Urumchi in the northwest because of their strategic locations for geographic and political reasons. The ANTC is relatively young, and not as efficient and well-developed as that of the US.     

Towards collaborative, intermodal hub networks: A case study in the fast moving consumer goods market

Collaborative hub networks can provide an answer to the need to decrease logistics cost and maintain logistics service levels by shifting consolidated flows to modes that are better suited for handling large volumes (rail, barge, coastal shipping), so economies of scale can be obtained. This necessity has been increased by the tendency of globalization of industries, smaller shipments sizes, high frequencies, and the fragmentation of flows. Through collaboration the necessary synchronization between expensive but fast and flexible means of transport and inexpensive, but slow and inflexible means can be combined in an intermodal hub network. This paper shows the rationale behind these collaborative hub networks, based on the literature on the design of many-to-many hub networks. The resulting methodology is explained through presenting the results of the design and implementation of collaborative hub network for the distribution of fast moving consumer goods using a combination of trucking and inland barges. This concept, first proposed by Vermunt [Vermunt, A.J.M., 1999. Multilognet, the intelligent multimodal logistics network, an important node in the worldwide logistics net, Vermunt Logistiek Advies v.o.f., working paper (in Dutch)], won the European Intermodal Award of the European Intermodal Association in 2003, and after extensive research was launched in The Netherlands as a commercial pilot by logistics service provider Vos Logistics and barge operator Riverhopper in January 2004.     

A new hub and spoke system proposal: A case study for Turkey's aviation industry

In this paper, we are proposing a multi-objective mathematical model for the selection of a newly constructed hub and spoke system. The objectives of this model are maximizing aircraft utilization and revenue whilst reducing the commercially infeasible network detour factor. The sensitivity analysis of the model is tackled using weights related to the objectives as well as the network detour factor. The number of available aircraft and the range that an aircraft can reach are also considered in this model. Since Istanbul has already got a hub and spoke system with busy airports on both sides of the city, the model is applied to three other major cities of Turkey, Ankara, Antalya, and Izmir. The test data consists of over 90 cities in Europe and in the Middle East. The data includes unit passenger revenues and operating costs for the segments, distances between cities and hubs, expected load factors and flying times of segments. The scenarios are tested under specific expectations of airline network experts and the results are visualized by using Pareto front graphs. Compared to other candidates, Antalya stands out as a good choice for a new hub and spoke system in Turkey. The results of this model could be helpful for airlines and other airports in Turkey in order to identify their potential and competitive position in relation to their counterparts.     

Robust global supply chain network design under disruption and uncertainty considering resilience strategies: A parallel memetic algorithm for a real-life case study

A mixed-integer, non-linear model is developed for designing robust global supply chain networks under uncertainty. Six resilience strategies are proposed to mitigate the risk of correlated disruptions. In addition, an efficient parallel Taguchi-based memetic algorithm is developed that incorporates a customized hybrid parallel adaptive large neighborhood search. Fitness landscape analysis is used to determine an effective selection of neighborhood structures, while the upper bound found by Lagrangian relaxation heuristic is used to evaluate quality of solutions and effectiveness of the proposed metaheuristic. The model is solved for a real-life case of a global medical device manufacturer to extract managerial insights.     

A scenario planning approach for the flood emergency logistics preparation problem under uncertainty

This paper aims to develop a decision-making tool that can be used by government agencies in planning for flood emergency logistics. In this article, the flood emergency logistics problem with uncertainty is formulated as two stochastic programming models that allow for the determination of a rescue resource distribution system for urban flood disasters. The decision variables include the structure of rescue organizations, locations of rescue resource storehouses, allocations of rescue resources under capacity restrictions, and distributions of rescue resources. By applying the data processing and network analysis functions of the geographic information system, flooding potential maps can estimate the possible locations of rescue demand points and the required amount of rescue equipment. The proposed models are solved using a sample average approximation scheme. Finally, a real example of planning for flood emergency logistics is presented to highlight the significance of the proposed model as well as the efficacy of the proposed solution strategy.     

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 assessment of the regulation of air cargo security in Europe: A Belgian case study

The discovery of explosive devices concealed in air cargo in October 2010 triggered an action plan to strengthen air cargo security in Europe. This paper addresses the potential implications for different actors with respect to the introduction of recent European Union (EU) regulation. The focus is on the legislative efforts to reinforce air cargo security and, in particular, the issue of third countries flights to Belgium. Based on existing literature, a review of the legislation and several interviews with experts and different stakeholders in Belgium, it can be concluded that the current air cargo and mail security framework is not satisfactory. Evidence from both the literature review and the interviews points to a necessary policy paradigm shift towards a risk assessment based security process. Special emphasis should be put on a collaborative industry driven supply chain security and the urgent need to harmonize air cargo security procedures at EU level.     

A hybrid decomposition algorithm for designing a multi-modal transportation network under biomass supply uncertainty

This study presents a two-stage stochastic programming model for the design and management of a biomass co-firing supply chain network under feedstock supply uncertainty. To represent a more realistic case, we generate scenarios from prediction errors of the historical and forecasted biomass supply availabilities. We solve the model using a hybrid decomposition algorithm that combines Sample average approximation with an enhanced Progressive hedging algorithm. The proposed algorithm is validated via a real-world case study using data from Mississippi and Alabama. Computational results indicate that the proposed algorithm is capable of producing high quality solutions in a reasonable amount of time.     

An accelerated Benders decomposition algorithm for sustainable supply chain network design under uncertainty: A case study of medical needle and syringe supply chain

This paper proposes a multi-objective possibilistic programming model to design a sustainable medical supply chain network under uncertainty considering conflicting economic, environmental and social objectives. Effective social and environmental life cycle assessment-based methods are incorporated in the model to estimate the relevant environmental and social impacts. An accelerated Benders decomposition algorithm utilizing three efficient acceleration mechanisms is devised to cope with computational complexity of solving the proposed model. Computational analysis is also provided by using a medical industrial case study to present the significance of the proposed model as well as the efficiency of the accelerated Benders decomposition algorithm.     

A fully fuzzy network DEA-Range Adjusted Measure model for evaluating airlines efficiency: A case of Iran

Due to the competition among companies, evaluating the performance is one of the most important issues for managers. Data Envelopment Analysis (DEA) - Range Adjusted Measure model (RAM) is one of the non-radial models to evaluate the performance of companies. This paper presents a fully fuzzy network DEA-RAM model for evaluating airlines and extends the network DEA-RAM model in the fully fuzzy framework. First, a network structure is designed for airlines and then, a DEA-RAM model is presented for calculating efficiency scores. To handle uncertainty in data, fully fuzzy approach is considered and finally, a multi-objective network model is proposed to calculate airlines’ efficiencies. To solve the proposed fully fuzzy DEA-RAM model, the lexicographic approach is used and the efficiency scores are reported as interval numbers. To illustrate the capability of the proposed fully fuzzy DEA-RAM model, the actual data of 14 Iranian airlines are gathered and the interval efficiencies of airlines are evaluated.     

Real option analysis of aircraft acquisition: A case study

This paper demonstrates that aircraft acquisition by airlines may contain a portfolio of real options (flexible strategies) embedded in the investment's life cycle, and that if airlines rely solely on the static NPV method, they are likely to underestimate the true investment value. Two real options are investigated: i) the “shutdown-restart” option (a carrier may shutdown a plane if revenues are less than costs, but restarts it if revenues are more than costs), and ii) the option to defer aircraft delivery. We quantify the values of these options in a case study of a major U.S. airline. The economic insight could help explain observed capital expenditures of airlines, and serve as a rule of thumb in evaluating capital budgeting decisions. A compound option (consisting of both the shutdown-restart and defer options) is also analyzed.     

A spatio-temporal modelling approach for the study of the connectivity and accessibility of the Guangzhou metropolitan network

The urban growth of large cities in China is at a critical stage with the booming of the economy and impressive increase of the population and traffic demand. This paper studies and qualifies the growth and accessibility of a rapid rail transit network, and characterizes the relations with urban development using a spatio-temporal modelling approach. Several measures of the network topological structure, i.e., beta index (β), cyclomatic number (μ), alpha index (α) and gamma index (γ), are selected in order to examine and quantify the overall metro network growth of the city of Guangzhou in China. The results show that the current spatial connectivity of the Guangzhou’s metro network is relatively low, this stressing the need to augment the reliability of the connections between the network nodes, and to increase the number of circuits in the network. A travel-time matrix is modelled and evaluates the nodes accessibility and characterizes the spatio-temporal evolution of the metro network. The spatial interaction between the different nodes of the network, as well as nodes accessibility are analyzed and derived from a potential-based model. The extension of the metro network clearly shows a dramatic tendency of positive accessibility evolution but with regional differences. In particular, the core of the city is surrounded by areas with highest accessibility values and gradually expanding outward from the core, while the locations of transfer stations have significant influence on the variation of network time-based accessibility. Taking into account different network development scenarios, the approach reveals regional accessibility differences in the metropolitan area of the city of Guangzhou, this clearly illustrating the impact of network accessibility in urban development.     

Designing aviation networks under Public Service Obligations (PSO): A case study in Greece

The present paper explores a Greek case study on optimizing the design of aviation networks under Public Service Obligations (PSO). Based on previous research on airline PSO networks applied to the case studies of the Azores and Norway, optimization models are adapted to minimize not only the cost to the airline, but also the total social costs. Different predictive models to estimate demand are developed and included in the optimization models. It is found that after applying the developed demand and optimization models, the total network costs can be reduced significantly, compared to the actual network's operation ranging from 4% to 20%.     

Evolution trends of the network structure of Spring Airlines in China: A temporal and spatial analysis

Both the sustainable development of China's economy and the deregulation of the China air transport market have acted as a spur for the halting development of low-cost carriers (LCCs) in China. To analyze the development trends of LCCs' network in China, this paper took Spring Airlines, the only LCC in China as an example. First, the winter flight plans of Spring Airlines from 2005 to 2013 were collected. Secondly, the development trends of air transport network of Spring Airlines were explored with methods of mathematical statistics and social network analysis. Additionally, the development trends were analyzed from the levels of navigable cities, air routes and air transport networks. The results show that although Spring Airlines actively launched air routes between tourist cities with non-class I airports, its network has been transformed from a star structure into a complex one with multi-hubs. The development process of the Spring Airlines network can be separated into three stages. In addition, the problems and evolution trends of its network are discussed further.     

Experimental approach to NextGen benefits estimation: A case of single-airline Aircraft Arrival Management System

The Next Generation Air Transportation System (NextGen) embraces multiple operational and technological improvements that enable efficiencies for users and service providers. In managing the development of NextGen, the Federal Aviation Administration (FAA) is assessing initiatives and potential components of the future system. One component is software that jointly optimizes the timing of arriving traffic to streamline flight arrivals at congested airports (Aircraft Arrival Management Systems or AAMS). Since most of the proposed NextGen improvements are not yet implemented, their evaluations typically are conducted through modeling, simulation, and/or subject matter expert surveys. In contrast, this study utilizes experimental settings in a real-time operating environment to examine potential benefits of the AAMS. During the experiment, a number of system performance variables were recorded in two data collection periods: a passive period, when the system was operating without the AAMS, and an active period, when the AAMS optimized arriving traffic of a dominant airline. Due to confounding data issues, the results indicate that with only 6.5 percent of arriving traffic optimized, there are no observable improvements in the overall system performance. However, the study documents tangible benefits for optimized flights and a positive interaction effect between the FAA's Traffic Management Advisor and the AAMS.     

The impact of carbon emission fees on passenger demand and air fares: A game theoretic approach

The implementation of an environmental market-based measure on U.S. aviation industry is studied. Under this policy, each airline pays a carbon fee for the carbon dioxide emissions it generates. The impact on ticket prices and corresponding market shares is investigated via the joint estimation of an air travel demand model and an airlines' behavior model. In the demand model, aggregate air traffic data is used to determine the marginal effects of flight attributes that are specific to itinerary, airline and airport on market share. The airline's behavior model incorporates the carbon fee in the airline marginal cost. After the implementation of the carbon policy, the increased cost forces airlines to adjust ticket prices in order to maximize profits. The results obtained by the proposed model indicate a moderate price increase which strongly depends on the per tonne carbon price. Air travel demand falls from 2.4% to 21% depending on the carbon price level.