A novel modeling approach for the fleet deployment problem within a short-term planning horizon

This paper is concerned with model development for a short-term fleet deployment problem of liner shipping operations. We first present a mixed integer nonlinear programming model in which the optimal vessel speeds for different vessel types on different routes are interpreted as their realistic optimal travel times. We then linearize the proposed nonlinear model and obtain a mixed integer linear programming (MILP) model that can be efficiently solved by a standard mixed integer programming solver such as CPLEX. The MILP model determines the optimal route service frequency pattern and take into account the time window constraints of shipping services. Finally, we report our numerical results and performance of CPLEX on randomly generated instances.     

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.     

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.     

Deployment and utilization of plug-in electric vehicles in round-trip carsharing systems

Electric Vehicles (EVs) and Plug-in Hybrid Electric Vehicles (PHEVs) can reduce gasoline consumption, but increase vehicle acquisition costs and introduce operational constraints. We develop a comprehensive approach to EV/PHEV deployment and utilization in round-trip carsharing systems. First, we formulate and solve the tactical problem of utilizing a mix of gasoline vehicles and EVs/PHEVs to serve trip demand, using Mixed Integer Programming optimization to estimate the minimal gasoline consumption in a computationally efficient manner, and simulation to assess the effect of reservation order on realized gasoline consumption. Second, we use these results to inform the strategic deployment of EVs/PHEVs in the carsharing fleet, using meta-optimization. We implement our approach using data from a large carsharing provider. From the perspective of a carsharing operator, our results suggest that replacing some portion of existing gasoline fleets by EVs/PHEVs would result in gasoline savings likely to outweigh upfront investments and the constraints on vehicle utilization that it creates. Moreover, we find that easily implementable heuristics can capture some of these benefits, and that the integration of vehicle utilization patterns into the design of EV/PHEV deployment strategies can result in added benefits.     

Space allocating strategies for improving import yard performance at marine terminals

This paper focuses on the organization of the import storage yard at container port terminals. Three new stacking strategies are introduced which take into account the containers’ arrival and departure rates and the storage yard characteristics. A mathematical model based on probabilistic distribution functions is developed to estimate the number of rehandles required to manage an import container yard. The model is applied to the three proposed stacking strategies. Results show that the optimal strategy depends on stacking height and the relationship between vessel headway and container dwell time.     

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.     

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.     

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.     

Aircraft replacement scheduling: A dynamic programming approach

This study developed a stochastic dynamic programming model to optimize airline decisions regarding purchasing, leasing, or disposing of aircraft over time. Grey topological models with Markov-chain were employed to forecast passenger traffic and capture the randomness of the demand. The results show that severe demand fluctuations would drive the airline to lease rather than to purchase its aircrafts. This would allow greater flexibility in fleet management and allows for matching short-term variations in the demand. The results of this study provide a useful reference for airlines in their replacement decision-making procedure by taking into consideration the fluctuations in the market demand and the status of the aircraft.     

The impact of foldable containers on container fleet management costs in hinterland transport

This paper analyzes the possibility to save container fleet management costs in repositioning empty containers through the use of foldable containers. We model this entire empty container flow as an integer programming problem with different strategies in empty container flow itinerary. The model is used to carry out numerical experiments that optimize the empty container repositioning in the hinterland, where there are serious empty container repositioning problems caused by extremely imbalanced trades. The study finds that foldable containers can substantially save on repositioning costs compared to the use of standard containers.     

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.     

A carrier’s optimal bid generation problem in combinatorial auctions for transportation procurement

We consider the carrier’s optimal bid generation problem in combinatorial auctions for transportation procurement. Bidders (carriers) employ vehicle routing models to identify sets of lanes (origin-destination pairs) based on the actual routes that a fleet of trucks will follow in order to maximize profit. Routes are constructed by optimally trading off repositioning costs of vehicles and the rewards associated with servicing lanes. The carrier optimization represents simultaneous generation and selection of routes and can incorporate any existing commitment. We employ both column generation and Lagrangian based techniques for solving the carrier optimization model and present numerical results.     

Economies of scale in large containerships: optimal size and geographical implications

In recent years, liner shipping has experienced an explosion in containership size. This is explained by the economies of scale in utilising such ships. This paper presents a model which quantifies the economies of scale in operating large containerships. A sensitivity analysis is conducted to test the effect of various input scenarios and the results analysed to determine optimal containership size with respect to different operational scenarios. Inferences are then drawn concerning the optimal deployment of the existing fleet of large containerships, likely future trends in containership size and deployment and the impact these trends will have upon container operations, logistical systems and ports.     

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.     

Coordinated inventory replenishment and outsourced transportation operations

We consider a one-warehouse N retailers supply chain with stochastic demand. Inventory is managed in-house whereas transportation is outsourced to a 3PL provider. We develop analytical expressions for the operating characteristics under both periodic and continuous joint replenishment policies. We identify the settings where a periodic review policy is comparable to a continuous review one. In our numerical test-bed, the periodic policy performed best in larger supply chains operating with larger trucks. We also observed that if the excess utilization charge is less than 25%, outsourcing becomes beneficial even if outsourcing cost is 25% more than the in-house fleet costs.     

Analysis of the recent evolution of commercial air traffic CO2 emissions and fleet utilization in the six largest national markets of the European Union

This paper presents the results of a study performed to analyze the evolution of commercial air traffic and CO₂ emissions in the European Union, from 2010 to 2013. Data sources are the European Commission's Eurostat Air Transport Statistics (Eurostat) and EUROCONTROL flight plans database. The changes in the fuel efficiency are analyzed and the potential reasons for those changes investigated. The evolution in the airline fleet composition during the last decade is presented as one of the reasons for the improvement in fuel efficiency, measured in burnt fuel per total Revenue Tonne Kilometre (RTK), as well as the different parameters depending on the airline business model (network carriers, low cost companies, etc.) and the aircraft type.Results show a slight reduction in the traffic, both for passengers and cargo (about −0.8%), and a more important reduction in CO₂ emissions (−4.3%), thanks to an improvement in the fuel efficiency parameter (−3.5%) for the three years period. There has been a relevant change in the fleet composition in the last ten years, with the replacement of older models for more efficient ones, and a shift to larger aircraft, particularly in the regional segment. Traffic has decreased in shorter distances (internal EU traffic), but increased in more efficient long range flights (extra-EU traffic), resulting also in an improvement of the efficiency parameter as average aircraft size and stage length increases.     

Min–Max exact and heuristic policies for a two-echelon supply chain with inventory and transportation procurement decisions

We study the problem in which one supplier delivers a product to a set of retailers over time by using an outsourced fleet of vehicles. Since the probability distribution of the demand is not known, we provide a Min–Max approach to find robust policies. We show that the optimal Min-Expected Value policy can be very poor in the worst case. We provide a Min–Max Dynamic Programming formulation that allows us to exactly solve the problem in small instances. Finally, we implement a Min–Max Matheuristic to solve benchmark instances and show that it is very effective.     

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.     

Understanding the usage of dockless bike sharing in Singapore

A new generation of bike-sharing services without docking stations is currently revolutionizing the traditional bike-sharing market as it dramatically expands around the world. This study aims at understanding the usage of new dockless bike-sharing services through the lens of Singapore's prevalent service. We collected the GPS data of all dockless bikes from one of the largest bike sharing operators in Singapore for nine consecutive days, for a total of over 14 million records. We adopted spatial autoregressive models to analyze the spatiotemporal patterns of bike usage during the study period. The models explored the impact of bike fleet size, surrounding built environment, access to public transportation, bicycle infrastructure, and weather conditions on the usage of dockless bikes. Larger bike fleet is associated with higher usage but with diminishing marginal impact. In addition, high land use mixtures, easy access to public transportation, more supportive cycling facilities, and free-ride promotions positively impact the usage of dockless bikes. The negative influence of rainfall and high temperatures on bike utilization is also exhibited. The study also offered some guidance to urban planners, policy makers, and transportation practitioners who wish to promote bike-sharing service while ensuring its sustainability.     

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.