Three-stage airline fleet planning model

One of the main factors affecting airline success is bringing supply and demand as closely together as possible. In order to achieve this goal, an airline needs to adopt an appropriate methodological approach for the fleet planning process. Selection of an aircraft for operating a defined route network is a key element which has a direct impact on the increase of an airline's profitability and on the reduction of an airline's costs. The objective of this paper is to develop a robust model for fleet planning that deals with both fleet size and fleet composition problems for airlines operating on short haul and medium haul routes. The three-stage model for fleet planning involves approximate fleet composition, fleet sizing and aircraft type selection based on fuzzy logic, heuristic and analytic approaches, and multi-criteria decision making, respectively. This model is exemplified with a hypothetical airline based at Belgrade Airport.     

Introducing a preliminary consists selection in the locomotive assignment problem

The Locomotive Assignment Problem (LAP) is a class of planning and scheduling problems solved by assigning a fleet of locomotives to a network of trains. In the planning versions of the LAP, the type of consist (a group of linked locomotives) assigned to each train in a given schedule is determined. We introduce an optimization model (called consists selection) that precedes the planning LAP solution and determines the set of consist types. This selection leads to solutions that are characterized by potential savings in terms of overall fueling cost and are easier to handle in the routing phase.     

Scenario tree airline fleet planning for demand uncertainty

This paper proposes an innovative multi-period modeling approach to solve the airline fleet planning problem under demand uncertainty. The problem is modeled using a scenario tree approach. The tree is composed of nodes, which represent points of decision in multiple time stages of the planning horizon, and branches, representing demand variation scenarios. The branches link the decision nodes in consequent time stages and compose scenario paths. Fleet decisions are modeled according to these scenario paths, resembling the real-life process in which fleet plans are not defined in a single moment but instead are adjusted according to the demand development. Given that some scenario paths share common decision nodes, decisions among scenarios need to be synchronized. A mixed-integer linear programming model is proposed to determine the ideal fleet composition for each scenario in the tree and to describe this interdependency between scenarios. Considering the probability of a scenario, fleet composition probabilities for each time-period can be determined. Two real-world based case studies are performed to show the validity of the model. Results show that the proposed scenario tree approach can provide flexible multi-period airline fleet plans, which are more robust to future demand scenarios than fleet solutions obtained using the traditional approach of considering a single deterministic demand evolution scenario.     

Hybrid metaheuristic solutions to inventory location routing problem

This paper considers a supply chain network with multiple depots and geographically dispersed customers, each of which faces non-constant demand over a discrete planning horizon. The goal is to determine a set of depots to open, the delivery quantities to customers per period and the sequence in which they are replenished by a vehicle fleet such that the total system-wide cost is minimized. To solve it, first we construct a mixed integer program, and then propose a hybrid metaheuristic consisting of initialization, intensification and post-optimization. Results show that the proposed heuristic is considerably efficient and effective for many classical instances.     

Optimal fleet utilization and replacement

The fleet replacement problem of a profit-maximizing manager is examined using an optimal control model that captures both utilization and replacement decisions. Conditions for optimal utilization of each vessel in the fleet and optimal vessel acquisition and retirement strategies are discussed. The results indicate that the optimal replacement schedule and fleet size are influenced by utilization schedules, and vice versa. Thus, replacement and utilization strategies should be determined jointly. We develop a numerical example to illustrate the model's potential as a practical management decision tool and the procedures to solve it.     

Solving an integrated operational transportation planning problem with forwarding limitations

In integrated operational transportation planning (IOTP) problems, the traditional vehicle routing problem is extended by using external resources for the fulfillment of transportation requests. IOTP is getting more complex when the choice of the fulfillment mode is limited for some requests. In this paper, an existing column generation-based heuristic for IOTP is extended by two strategies for handling forwarding limitations. The computational experiments indicate that one of the extended versions of the heuristic outperforms all previous approaches in literature. Further on, the impact of forwarding limitations on different location structures and on the size of the private fleet is analyzed.     

Optimizing station location and fleet composition for a high-speed rail line

This paper proposes a new strategic planning model for high-speed rail ventures. It is a mixed-integer optimization model that applies to a given line and focuses on two key strategic decisions: station location and fleet composition. Our purpose is to improve on previous station location models by including fleet composition decisions. In the new model, we additionally take into account in an approximate fashion the interrelationships between strategic and subsequent tactical decisions, regarding line planning, train scheduling and fleet assignment issues. The usefulness of the model is demonstrated for a case study involving a planned Lisbon-Oporto high-speed rail line.     

Cooperation among truck carriers in seaport containerized transportation

Nowadays the majority of goods passing through seaports are transported by road, resulting in a large number of empty movements and high total costs. This paper proposes an optimization model for the cooperative planning of multiple truck carrier operations in a seaport environment for maximizing the total profit derived from their cooperation. A compensation mechanism is introduced to motivate carriers to share their trips. Time windows, trip deadlines and fleet sizes are considered. The planning approach is evaluated using real data sets from the Italian port of Genoa. Numerous scenarios are tested and an extensive computational analysis is reported.     

An adaptive memory programming metaheuristic for the heterogeneous fixed fleet vehicle routing problem

This paper studies the heterogeneous fixed fleet vehicle routing problem (HFFVRP), in which the fleet is composed of a fixed number of vehicles with different capacities, fixed costs, and variable costs. Given the fleet composition, the HFFVRP is to determine a vehicle scheduling strategy with the objective of minimizing the total transportation cost. We propose a multistart adaptive memory programming (MAMP) and path relinking algorithm to solve this problem. Through the search memory, MAMP at each iteration constructs multiple provisional solutions, which are further improved by a modified tabu search. As an intensification strategy, path relinking is integrated to enhance the performance of MAMP. We conduct a series of experiments to evaluate and demonstrate the effectiveness of the proposed algorithm.     

城市配送中心自有车辆规模研究

确定合理的自有车辆规模,是配送中心有效降低物流配送成本的措施之一。通过引入配送周期的概念,修正过去以天为周期计算配送中心所需车辆数的方法,从而得到能更准确反映配送中心用车情况的统计资料,在考虑内外车辆对客户服务水平的影响后,建立成本最小模型及模型求解方法,并结合算例计算出城市配送中心合理的自有车辆数。     

The impact of control strategies on the management of returnable transport items

This research examines the impact of different control strategies on the management of returnable transport items (RTIs) in closed-loop supply chains. A simulation model is developed based on an empirical case and is used to explore different scenarios. The results suggest that the choice of control strategy has a significant impact on investments and operating costs, and that RTI shrinkage can be controlled either through the use of tracking systems, or choice of control strategy. Moreover, a simulation-based method for estimating the fleet size required to operate the system for the different strategies is presented.     

The transformation of a legacy carrier – A case study of Turkish Airlines

This study examines the metronomic rise of Turkish Airlines into a global carrier in the period following domestic deregulation and part privatisation. Using a comparative assessment of the carrier's network and its competitive strategies during the 2003–2013/2014 period it was found that Turkish Airlines now benefits from considerable network, cost, service and brand advantages over competing European and to a lesser extent Middle-Eastern airlines. Its network operation based in Istanbul Ataturk airport enjoys strong geographic and demographic advantages, which enables it to optimise the use of its large and young short-haul fleet between a significant number of domestic and international points. This study has important implications for partially or fully state owned legacy carriers as to how to gain competitive advantages in an increasingly open and liberal airline industry.     

The heterogeneous green vehicle routing and scheduling problem with time-varying traffic congestion

The green vehicle routing and scheduling problem (GVRSP) aims to minimize green-house gas emissions in logistics systems through better planning of deliveries/pickups made by a fleet of vehicles. We define a new mixed integer liner programming (MIP) model which considers heterogeneous vehicles, time-varying traffic congestion, customer/vehicle time window constraints, the impact of vehicle loads on emissions, and vehicle capacity/range constraints in the GVRSP. The proposed model allows vehicles to stop on arcs, which is shown to reduce emissions up to additional 8% on simulated data. A hybrid algorithm of MIP and iterated neighborhood search is proposed to solve the problem.     

The future of airports post COVID-19

COVID-19 pandemic has hit most sectors of the world and has led to many industries coming to a standstill. It has led to restrictions of movement and travel ban. As a result of these restrictions, transport sector especially in aviation has impacted badly.With the uncertainty of further impact of the current situation, there is a likelihood of the aviation business rebounding at a slower pace bringing V-shape and U-shape recovery as per analysis of economic impacts on civil aviation by International Civil Aviation Organization (ICAO (2020). Currently, airline capacity is down 70 to 80 percent in April 2020 compared to April 2019, and multiple large airlines have temporarily ceased operations. Largely, almost 60 percent of the global fleet was grounded in early April 2020 as per McKinsey report (Curley et al., 2020).In order to support the sinking capacities and revenues, the International Air Transport Association (IATA) calls on the European governments to provide relief to their airlines to sustain their operations. Furthermore, this document highlights the future of airport and air transport industry based on revenue generation sources, cost control strategies and integration of innovations with respect to variable demand and capacity during and post COVID-19.     

Risk management in liner ship fleet deployment: A joint chance constrained programming model

This paper provides a tangible methodology to deal with the liner ship fleet deployment problem aiming at minimizing the total cost while maintaining a service level under uncertain container demand. The problem is first formulated as a joint chance constrained programming model, and the sample average approximation method and mixed-integer programming are used to deal with it. Finally, a numerical example of a liner shipping network is carried out to verify the applicability of the proposed model and solution algorithm. It is found that the service level has significant effect on the total cost.     

Frequency and aircraft size dynamics in a concentrated growth market: The case of the Chinese domestic market

Despite the explosive growth of the Chinese aviation sector and the major industry reforms undertaken in recent decades, the Chinese domestic market remains highly concentrated with a significant element of regulation and governmental control in areas such as market entry and airline fleet planning. In this study, we investigate the frequency strategies and aircraft choices of airlines operating in this concentrated growth market. Our empirical investigation suggests that airlines mainly accommodate rapid traffic growth by flying more frequently, although increased aircraft size also contributes to market expansion. We also find a negative relationship between market concentration and flight frequency. Due to the more balanced market structure resulting from mergers among leading airlines since 2002, there has been a moderate reduction in market concentration at route level, contributing to a 3.7% increase in traffic volume from 2002 to 2008. The results of our study suggest that Chinese travelers have yet to fully enjoy the benefits of market liberalization, and airports should prioritize increasing capacity related to aircraft movements over the accommodation of larger aircraft.     

Containership routing with time deadlines and simultaneous deliveries and pick-ups

In this paper we seek to determine optimal routes for a containership fleet performing pick-ups and deliveries between a hub and several spoke ports. A capacitated vehicle routing problem with pick-ups, deliveries and time deadlines is formulated and solved using a hybrid genetic algorithm for establishing routes for a dedicated containership fleet. Results on the performance of the algorithm and the feasibility of the approach show that a relatively small fleet of containerships could provide efficient services within deadlines. Moreover, through sensitivity analysis we discuss performance robustness and consistency of the developed algorithm under a variety of problem settings and parameters values.     

Cleaner vehicle buses in Winchester

This paper reports the results of a package of measures, contained within a Quality Bus Partnership, designed to reduce the environmental impact of the local bus fleet in Winchester. These measures were implemented by Hampshire County Council, Stagecoach Bus Company and Winchester City Council as part of the EU-sponsored CIVITAS MIRACLES project which ran from 2002 to 2006 and whose aims included reducing the environmental impact of transport at the local level while increasing urban accessibility. It follows on from a previous paper published in Transport Policy in 2007 looking at the success of measures implemented in Winchester to improve bus service quality and information.These implemented measures included the introduction of 13 new Euro III buses, re-powering 10 older buses from Euro I to Euro III standard, adding particulate traps to four Euro II buses and the demonstration of two different diesel/electric hybrid buses during two week-long trials in 2003 and 2004 along the Park and Ride route.In order to evaluate the effects of these measures, data was collected from the bus operator Stagecoach regarding their fleet of 59 vehicles in Winchester. This included their emission standard, reliability, average age and smoke test results. Emission modelling was carried out using a vehicle activity model on a key city centre street to assess emissions savings as a result of the implemented measures. In addition, two bus questionnaire surveys were carried out to assess passenger's views of the two diesel/electric hybrid buses used during the trials. Conclusions and recommendations have been made with regard to the environmental impact of the cleaner Winchester bus fleet and the contribution it has made to reducing emissions from motor vehicles in the Winchester central area.     

Conditions for electric vehicle taxi: A case study in the Greater Stockholm region

This study investigates the usability of electric vehicles (EVs) in a taxi company in Greater Stockholm, Sweden. By investigating cost and revenue data of both electric and conventional taxi vehicles, as well as by interviewing taxi drivers and carriers, an assessment has been made of the financial and operational implications of using EVs in a company’s taxi fleet. Both the drivers’ and the carriers’ perspectives have been examined. The main findings are that the investigated e-taxis have a similar or lower Total Cost of Ownership and slightly higher profitability than the investigated conventional taxis. For taxi drivers, using e-taxis implies more advanced planning and revenue service time being sacrificed for charging. However, certain customers’ preferences for EVs, as well as benefits such as corporate clients favoring e-taxis and a zero emission priority queuing system at Stockholm’s main international airport (partly) compensate for time devoted to charging. In order to facilitate increased use of e-taxis, more fast charging facilities should become available at strategic locations. Besides that, there are signs that carriers’ lack of information about the opportunities and consequences of shifting towards e-taxis hamper a wider deployment of e-taxis.     

Robust optimization for fleet planning under uncertainty

We create a formulation and a solution procedure for fleet sizing under uncertainty in future demands and operating conditions. The formulation focuses on robust optimization, using a partial moment measure of risk. This risk measure is incorporated into the expected recourse function of a two-stage stochastic programming formulation, and stochastic decomposition is used as a solution procedure. A numerical example illustrates the importance of including uncertainty in the fleet sizing problem formulation, and the nature of the fundamental tradeoff between acquiring more vehicles and accepting the risk of potentially high costs if insufficient resources are available.