A dynamic approach for aircraft assignment and maintenance scheduling by airlines

The problems of assigning planes to flights and of fleet maintenance operations scheduling are considered in this paper. While recent approaches make use of artificial intelligence techniques running on main frame computers to solve combinatorial optimization problems for nominal operations, a dynamic approach is proposed here to face on-line operation conditions. The proposed solution mixes a Dynamic Programming approach (to cope with the fleet assignment problem) and a heuristic technique (to solve the embedded maintenance schedule problem). When applied to a medium charter airline, this approach shows acceptability characteristics for operational staffs, while providing efficient solutions. The proposed solution scheme can be considered as the basis for the development of an on-line decision support system for fleet operations management within airlines.     

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.     

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。     

A robust mathematical model and heuristic algorithms for integrated aircraft routing and scheduling,with consideration of fleet assignment problem

One of the most important airline's products is to determine the aircraft routing and scheduling and fleet assignment. The key input data of this problem is the traffic forecasting and allocation that forecasts traffic on each flight leg. The complexity of this problem is to define the connecting flights when passengers should change the aircraft to reach the final destination. Moreover, as there exists various types of uncertainties during the flights, finding a solution which is able to absorb these uncertainties is invaluable. In this paper, a new robust mixed integer mathematical model for the integrated aircraft routing and scheduling, with consideration of fleet assignment problem is proposed. Then to find good solutions for large-scale problems in a rational amount of time, a heuristic algorithm based on the Simulated Annealing (SA) is introduced. In addition, some examples are randomly generated and the proposed heuristic algorithm is validated by comparing the results with the optimum solutions. The effects of robust vs non-robust solutions are examined, and finally, a hybrid algorithm is generated which results in more effective solution in comparison with SA, and Particle Swarm Optimization (PSO).     

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.     

How fleet commonality influences low-cost airline operating performance: Empirical evidence

This paper investigates the effect of fleet commonality on operating performance of low-cost airlines. It examines the role fleet size and route length variations on this relationship. Results of an analysis of 28 airlines show that fleet commonality is positively associated with operating performance. Further, fleet size positively affects this relationship, whereas route length variations do not.     

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.     

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.     

The dynamics between freight volatility and fleet size growth in dry bulk shipping markets

This paper studies the relationship between the time-varying volatility of dry bulk freight rates and the change of the supply of fleet trading in dry bulk markets. An abundance of research has been done to understand the time-varying characteristics of freight rate volatility, yet few have discussed the determinants of freight volatility. We therefore examine freight volatility against the changes in fleet size and other shipping market variables over January 1973–October 2010. The study employs a two-step model specification. The first step is the measurement of freight rate volatility through an AR-GARCH model; the second step is the analysis of the relationship between freight rate volatility and fleet size growth through a GMM regression. We confirm similar findings in the literature that freight rate volatility is time varying. Furthermore, the results reveal that the change in fleet size positively affects freight rate volatility, while the spot rate volatility of Capesize dry bulk exhibits a stronger reaction to the change in fleet size. The results of this study contribute in a general sense to understanding the systematic risk of shipping markets.     

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.     

Fleet composition of commercial jet aircraft 1952–2005: Developments in uniformity and scale

The fleet composition of an airline is important in determining its costs and operational performance. This composition can be measured using numerical values. An index for measuring fleet uniformity is available, and a structured way of measuring fleet scale is introduced here. The history of all jet aircraft operated by commercial passenger or cargo airlines world-wide is analyzed both in general terms and using these measures. The analysis shows that uniformity in airline fleets has been steadily decreasing, while their scale has been steadily increasing.     

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.     

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.     

Reliability and operations: Keys to lumpy aircraft spare parts demands

This study provides unique new insights into the reasons for lumpy aircraft spare parts demands, and identifies opportunities to improve the regularity of aircraft spares demands. The study develops its unique insights into aircraft spare parts demands by considering the typical failure probability distribution (Weibull Distribution) for aircraft spare parts. The study identifies the range of Weibull model parameters that explain typical aircraft part failure rates, and uses these parameters to perform a Monte Carlo simulation of notional aircraft components in typical aircraft fleet sizes and operations. Each notional component is repeatedly used to failure and replaced, providing a simulated spare part demand rate. The data is evaluated to uncover patterns that allow a deeper understanding of how reliability and operational input factors impact the spare part demand characteristics. The study finds that the aircraft fleet size has the greatest impact on the lumpiness of aircraft spare parts demands. The study also recommends other measures that fleet managers may take to reduce the lumpiness of their spares demands.     

A dynamic carsharing decision support system

This paper proposes a dynamic optimization–simulation model as a decision support system for one-way carsharing organizations. To reduce the vehicle imbalance in one-way systems, a Vehicle Relocation Optimization model is solved successively in a discrete event simulation. Each event is the arrival of a new user. The model is compared to an a priori benchmark model. Autoshare is chosen as a case study. Results show that increasing the reservation time (time between requesting and picking up a vehicle) from 0 to 30 min reduces fleet size by 86%. The model captures a tradeoff between vehicle relocation hours and fleet size.     

Optimizing the service area and trip selection of an electric automated taxi system used for the last mile of train trips

We propose two integer programming models for optimizing an automated taxi (AT) system for last mile of train trips. Model S1: trip reservations are accepted or rejected by the operator according to the profit maximization; model S2: any reservation on a selected zone by the model must be satisfied. Models were applied to a case-study. Results indicate that fleet size influences the profitability of the taxi system: a fleet of 40 ATs is optimal in S1 and 60 ATs in S2. Having electric ATs constrains the system for small fleets because ATs will not have time for charging.     

Profiling road transport activity: Emissions from 2000 to 2005 in Ireland using national car test data

This work describes a methodology for determining the average vehicle kilometres travelled by the private national car fleet in Ireland and estimating the disaggregated CO₂ and NO_x emissions from private vehicles in the Irish road transport sector for the period 2000–2005 using national car test records. The developed methodology facilitates the calculation of greatly improved estimates for vehicle kilometres under a range of constraint variables and thereby enables the disaggregated analysis of specific vehicle fleet groups and their associated activity patterns to support evidence-based policy development. The results indicate that while older vehicles are contributing significantly to car NO_x emissions; newer cars produce a higher share of CO₂ emissions than older cars in the vehicle fleet.     

Urban bus fleet-to-route assignment for pollutant emissions minimization

This study proposes a methodology to optimize the assignment of an urban bus fleet to a set of fixed routes, taking into account the differences among routes and the differences among vehicle types and propulsion technologies in order to reduce pollutant emissions (CO₂, CO, THC, NO_x and PM). A Mixed Integer Linear Programming optimization model is stated and two scenarios are assessed: minimization of CO₂ and NO_x. The results show that it is feasible to obtain a fleet distribution in which emissions for any given pollutant are reduced without increase in emissions of other pollutants.     

Robust planning and disruption management in roll-on roll-off liner shipping

This paper presents different strategies for handling disruptions in fleet deployment in roll-on roll-off liner shipping, which basically consists of assigning a fleet of vessels to predefined voyages at minimum cost. A new mathematical model of the problem is presented, including a set of robust planning strategies, such as adding slack and rewarding early arrivals. To solve real-life instances a rolling horizon heuristic is proposed. A computational study, where we also propose some recovery planning strategies, is conducted, and simulation results show that adding robustness significantly reduces the actual cost of the plan and the total delays of the voyages.