A concise guide to existing and emerging vehicle routing problem variants

Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges

A concise guide to existing and emerging vehicle routing problem variants

Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of applications has motivated the study of a myriad of problem variants with different attributes. In this article, we provide a concise overview of existing and emerging problem variants. Models are typically refined along three lines: considering more relevant objectives and performance metrics, integrating vehicle routing evaluations with other tactical decisions, and capturing fine-grained yet essential aspects of modern supply chains. We organize the main problem attributes within this structured framework. We discuss recent research directions and pinpoint current shortcomings, recent successes, and emerging challenges.</p

Uncertainty management at the airport transit view

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system's robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance

Aircraft requirements for low/medium density markets

A study was conducted to determine the demand for and the economic factors involved in air transportation in a low and medium density market. The subjects investigated are as follows: (1) industry and market structure, (2) aircraft analysis, (3) economic analysis, (4) field surveys, and (5) computer network analysis. Graphs are included to show the economic requirements and the aircraft performance characteristics

Options for reshaping the railway

In many countries the mismatch between what the railways offer and what the customers want has caused significant economic inefficiency and severe financial strains for the railways and their government owners. The concept of the railway as a monolithic entity is so strong in many countries as to be a roadblock against reshaping the railway. The authors explore four options which can be used to reshape the railways. First is the lines of business option which improves accountability and responsiveness to markets. The second is the competitive access option which introduces intramodal competition in selected markets, while maintaining unitary control over most railway operations. The third is the"wholesaler"option which would accomplish an excellent marketing job, but the actual operation would remain in monolithic hands. Finally there is the"toll rail enterprise"option which comes closest to reflecting a theoretical model of marketing effectiveness, however it would generate potential operating conflicts and higher transaction costs. The authors show that one generalization holds true in all circumstances: a monolithic railway does not function well in a market economy in competition with privately owned, properly regulated competitors - especially trucking. The authors point out that solutions will vary, but the universal objective as an economy becomes more market driven is to make the railway more market sensitive.Railways Transport,Roads&Highways,Environmental Economics&Policies,Banks&Banking Reform,ICT Policy and Strategies

Synchromodal logistics: An overview of critical success factors, enabling technologies, and open research issues

Abstract As supply chain management is becoming demand driven, logistics service providers need to use real-time information efficiently and integrate new technologies into their business. Synchromodal logistics has emerged recently to improve flexibility in supply chains, cooperation among stakeholders, and utilization of resources. We survey the existing scientific literature and real-life developments on synchromodality. We focus on the critical success factors of synchromodality and six categories of enabling technologies. We identify open research issues and propose the introduction of a new stakeholder, which takes on the role of orchestrator to coordinate and provide services through a technology-based platform

Optimal capacity decisions of airlines under supply-demand equilibrium

In the last three decades, airlines across the globe have experienced significant incidents and milestones such economic recessions, de-regulations, and jet fuel fluctuations, leading to many consolidations and even bankruptcies. Airlines seem to have a few options to respond to these disruptions and fluctuations. Capacity planning is one of the key tools that airlines apply to manage air traffic demand and their operating costs. As such, the carriers may alter the number of flights, use different types of airplanes, upgrade the seats in the aircraft, and even increase the load factor to maintain their market share and profitability, which can occasionally lead to passenger dissatisfaction. &#039;Capacity Planning&#039; is defined in this research as a combination of the number of flights and aircraft size that airlines choose to manage traffic demand on a given origin-destination route. It affects the airlines&#039; service quality and operating costs, in turn, influencing their market share and profitability. Capacity planning has become more important for airlines due to the diminishing relative significance of traditional tools such as airfare management or hedging contracts. However, capacity planning seems to be a difficult decision-making task for airlines as they need to consider many factors on both sides of the supply-demand equilibrium of the flight market and different limitations such as access to specific aircrafts, airports, or even flight regulations. Any changes in the capacity would trigger a sophisticated set of interrelated changes in passenger demand, flight frequency, aircraft size, airfare, and flight delay, finally leading to an equilibrium shift. This statement considers economies of density that means, given no congestion, more density in terms of higher passenger demand leads to more plane-miles by either more flights or larger aircrafts. In fact, with no capacity constraints, there is an ongoing loop causing higher density from the demand side and more plane-miles from the supply side of the flight equilibrium. However, this picture is no longer valid once the capacity constraint is added to the equilibrium. Capacity constraint introduces a new player, flight delay, to the equilibrium. In other words, higher density leads to more flight delays because of capacity constraints. Flight delays bring extra costs to airlines, diminishing economies of density. Therefore, airlines need to consider all these interrelated interactions to make efficient capacity plans on their operating networks. This thesis develops an optimisation model to assist airlines to make the optimum capacity decisions for individual routes of a given market such as a specific airport or network to maximise the potential passenger demand under the flight supply-demand equilibrium. To address this research, three key questions are identified as follows: What are the key determinants of airlines&#039; capacity decisions under the supply-demand equilibrium of flight market? How does an airline&#039;s capacity decision influence flight delays? How can airline capacity decisions be optimised for the individual routes of a given market to maximise the total potential flight demand with respect to the market&#039;s capacity constraints? Furthermore, this research answers some significant questions related to the interactions among the key players of the supply-demand equilibrium of the flight market. To answer these questions, this research is implemented in three steps. In the first step, the key drivers of capacity planning and demand modelling are statistically identified on both sides of the supply-demand equilibrium by applying the two-stage least square technique on the time-series cross-sectional data of 21 major routes of the Australian domestic market. In the second step, the impact of changes in the elements of capacity decisions in flight delay are investigated by using the Hausman-Taylor regression technique on the Australian domestic data. By connecting the findings of step 1 and 2, a research framework is created to be used as the basis of the optimisation algorithm in the final step. The model is developed by the inclusion of a series of exogenous and endogenous factors under the supply-demand equilibrium. To address the simultaneity among the variables, a system of four non-linear equations, flight demand, flight frequency, aircraft size, and flight delay, is developed and estimated individually by two statistical simultaneous techniques - three-stage least square technique (3SLS) and maximum likelihood estimator (MLE). The data of seven Australian domestic routes, linking Melbourne to other major cities in Australia, was applied, as the case study, to estimate the model&#039;s coefficients. Finally, the non-linear optimisation technique was applied to the estimates of 3SLS and MLE separately to find the optimum capacity plan of the given routes. All proposed models were verified and tested in different steps. As the key contribution, this thesis proposes an optimisation model based on a system of non-linear equations of the flight supply-demand equilibrium to maximise the potential flight demand of a given market with respect to the market&#039;s capacity constraints. This model is based on the theory of economies of density and applied the time-series cross-sectional data of flight market to empirically estimate the coefficients of passenger demand equation as the objective function. Compared to other models of capacity planning that generally contain a relatively a short list of micro-level factors in modelling, the proposed model contains all required macro- and micro-level factors. As the key contribution, this thesis highlights the key drivers of capacity planning and demand modeling of supply-demand equilibrium and their relationships in the Australian flight domestic market. As a part of results, there is a bilateral relation among the elements of capacity decisions and passenger demand. The results statistically differentiate the airlines&#039; policies of capacity planning across the different markets. The results suggest that a higher demand for flights primarily results in increased flight frequency rather than increased aircraft size or load factor. The load factor is identified to be an insignificant variable in capacity planning of the airlines. Competition between airlines, participation of low-cost carriers, and jet fuel expenses are thought to influence airlines&#039; capacity decisions, albeit differently across the given markets. Interestingly, jet fuel cost inflations stimulate the flight demand in the short-haul market as well as the routes linking the major cities to the industrial ones. The socio-economic parameters of population and employment rates affect the flight demand in the different markets in different ways. The findings indicate the airlines&#039; capacity decisions influence flight delays. The results indicate that more frequent flights and larger aircrafts together are associated with more flight delays. Route congestion is caused by more flights, albeit to a higher degree for low-cost carriers. Jet fuel cost inflation is expected to cause flight delays, but more for the legacy airlines than low-cost carriers. From the results of the optimisation model, for a given period, December 2015, the optimum solutions of 3SLS and MLE indicate, respectively, a 1.72% and 0.66% improvement on the flight demand compared to the reported actual plan for the airlines. The estimated MSE of the MLE model is smaller than that of 3SLS; however, estimated coefficients of 3SLS are statistically more significant than those of MLE, resulting in more practical results in the optimisation section. The proposed model and findings of this thesis can potentially be applied by airlines as well as policy makers to fleet planning and airport infrastructure development projects in different airports and hub-and-spoke networks across the globe. The proposed optimisation model may be enhanced by using the theory of full equilibrium to develop the optimisation model through adding the factors of the other transportation modes. Due to the data limitation, airfare was only applied as an exogenous parameter in the passenger demand equation of the optimisation model. Airfare can potentially be upgraded to become a key variable of airline capacity planning under the supply-demand equilibrium. In future research, the data of individual airlines can be applied separately at the route level. With the airline dimension in modelling, further explorations can be done on the airline&#039;s policies and performance of capacity planning in different markets. The proposed model can potentially be applied to other airports and hub-and-spoke networks across the globe which it surely leads to further explorations about the airlines&#039; policies and capacity planning as well as the demand modelling under the supply-demand equilibrium