Slot auction in an airport network with demand uncertainty

This paper investigates the effectiveness of airport slot auction by developing a two-stage model, which distributes slots among competing airlines using an ascending-bid multi-unit auction. Airlines assign different values to slots at peak and off-peak periods, and each carrier has its private (subjective) forecast of future demand. Conditional on the slots available to them, airlines compete in frequency, fare, and aircraft size over a congested airport network. The market outcome under such a scheme is benchmarked to those under an ex ante allocation and an ex post allocation by a social planner. Comparison results suggest that the auction-based scheme is inferior to the other two schemes when there is little fluctuation in demand, whereas the auction-based system is more effective when there is substantial demand uncertainty. Auctioning some grandfathered slots can improve social welfare but the marginal effect may diminish quickly.     

A hybrid implementation mechanism of tradable network permits system which obviates path enumeration: An auction mechanism with day-to-day capacity control

Akamatsu, 2007a, Akamatsu, 2007b proposed a new dynamic traffic congestion control scheme called tradable network permits, and demonstrated its efficiency properties for general road networks. To implement tradable permit markets, this paper proposes a novel auction mechanism with capacity control. This mechanism employs an evolutionary approach to achieve a dynamic system optimal allocation of network permits in a computationally efficient manner. We prove that the proposed mechanism has the following desirable properties: (i) truthful bidding is a dominant strategy for each user on each day and (ii) the permit allocation pattern under the mechanism converges to a dynamic system optimal allocation pattern.     

A MIP model for locating slow-charging stations for electric vehicles in urban areas accounting for driver tours

In this paper we propose an improved mathematical model for locating EV charging stations. We consider the successive activities of the travelers, i.e., a person with two main stops during the day should charge the vehicle in just one of the parking spots, hence avoiding double counting the demand. The model is tested for the city of Coimbra (Portugal), where there is a network of nine stations. We conclude that our solution is better than the one that was implemented in reality, moreover we are able to conclude that demand transference has a rather significant impact on the solutions.     

Cooperation through capacity sharing between competing forwarders

In this paper, we consider a shipping system consisting of one carrier and two shipping forwarders who compete on price for businesses from potential shippers. The carrier may quote different prices or a single price to the two shipping forwarders who will then order shipping capacity from the carrier and set the selling prices to the shippers before market uncertainties are revealed. Inspired by cooperation between competing parties in many industries including the maritime shipping industry, we propose a new model under which the shipping forwarders are allowed an opportunity to purchase shipping capacity from each other after they order capacity from the carrier but before they set the selling prices and satisfy demand, referred to as the capacity reservation model. We show analytically that capacity reservation between competing forwarders benefits both the carrier and the forwarders, leading to a win–win situation under various market conditions. Furthermore, capacity reservation can offset the negative effect of a carrier’s pricing power which enables the carrier to charge discriminatory shipping prices to squeeze more profits out of the forwarders.     

Optimal route decision with a geometric ground-airborne hybrid model under weather uncertainty

Adverse weather is the dominant cause of delays in the National Airspace System (NAS). Since the future weather condition is only predictable with a certain degree of accuracy, managing traffic in the weather-affected airspace is a challenging task. In this paper, we propose a geometric model to generate an optimal combination of ground delay and route choice to hedge against weather risk. The geometric recourse model (GRM) is a strategic Probabilistic Air Traffic Management (PATM) model that generates optimal route choice, incorporating route hedging and en-route recourse to respond to weather change: hedged routes are routes other than the nominal or the detour one, and recourse occurs when the weather restricted airspace becomes flyable and aircraft are re-routed to fly direct to the destination. Among several variations of the GRM, we focus on the hybrid Dual Recourse Model (DRM), which allows ground delay as well as route hedging and recourses, when the weather clearance time follows a uniform distribution. The formulation of the hybrid DRM involves two decision variables - ground delay and route choice - and four parameters: storm location, storm size, maximum storm duration time, and ground-airborne cost ratio. The objective function has two components: expected total ground delay cost and expected total airborne cost. We propose a solution algorithm that guarantees to find the global optimum of the hybrid-DRM. Based on the numerical analysis, we find that ground-holding is effective only when combined with the nominal route. Otherwise, it is optimal to fly on the route determined by the DRM without ground delay. We also find the formula of the threshold ground-airborne cost ratio, which we call the Critical Cost Ratio (CCR), that determines the efficacy of ground delay: the higher the CCR, the more effective the strategies involving ground delay. We conclude that both ground delay and route hedging should be considered together to produce the best ATM decisions.     

Methodological approach for assessing the potential of a rural tourism destination: An application in the province of Cáceres (Spain)

Evaluating the resources in a tourism destination is one of the previous tasks in the development of its comprehensive planning. There are many criteria to use in order to evaluate tourism resources; but, independently on the number of attributes considered the fact is that not every criterion is equally important in the process of evaluation and ranking of the tourism potential of a destination's resources. In contrast to other well-known methodologies, the aim of this paper is to propose a methodology to weight qualitative and hierarchical evaluation attributes by estimating a discrimination parameter. In this research, an item response theory (IRT) model is used, the graded response model, to estimate each attribute's discrimination coefficient. This parameter will be the basis to propose a weighting system for the entire set of attributes. Graded response model (GRM) will also allow establishing a hierarchy of resources by constructing a continuous latent scale, where it will be possible to position every analysed resource in the tourism destination. The applicability and robustness of the IRT methodology will be tested using data from rural tourism resources in the Spanish province of Cáceres.     

An integrated model for stock replenishment and shipment scheduling under common carrier dispatch costs

We examine a joint inventory replenishment and shipment scheduling problem that arises in the context of a vendor-managed inventory (VMI) arrangement. Since a temporal shipment consolidation policy is being implemented, the inventory requirements at the vendor are affected by the timing and quantity of shipment release. The vendor’s problem is to determine an integrated policy for inventory replenishment and shipment release and to set its parameters. We develop analytical models for computing such integrated policies where it is economical to use common carriage for outbound transportation. We propose algorithmic approaches to set the optimal policy parameter values.     

Managing uncertainty in on-demand air travel

Fractional management companies (FMCs) that provide on-demand air travel services experience frequent changes in aircraft availability and flight requests. We propose scheduling heuristics which are both cost-effective and persistent (i.e., close to the original schedule) to address the uncertainty. The heuristics include pro-actively enforcing idleness of aircraft in creating the original schedule, strategically repositioning aircraft to serve yet-unknown demand and dense scheduling. Computational experiments are conducted in a simulator that mimics FMCs’ daily operations. Simulation results quantify the value of each heuristic, which can be easily incorporated into existing computational methods used in FMCs for static scheduling problems.     

A multi-start heuristic approach for the split-delivery vehicle routing problem with minimum delivery amounts

We propose a new multi-start solution approach for the split-delivery vehicle routing problem with minimum delivery amounts (SDVRP-MDA). Initial solutions are generated by both node-insertion and route-addition procedures with a single parameter to control the restart. These solutions are then improved by a variable neighborhood descent metaheuristic with a novel search operator inspired by node-ejection chains. We test the proposed approach with 32 benchmark instances for four different minimum delivery fractions. Using the proposed algorithm, out of 128 cases tested, we find 81 best known solutions and 34 new best solutions; overall, we find 43 new best solutions.     

Solutions to the request reassignment problem in collaborative carrier networks

The paper considers an arrangement for exchanging transportation requests to facilitate collaboration among independent carriers. The goal is to maximize the total profit without decreasing the individual profit of the carriers. Two solution approaches are developed for this problem involving decentralized control and auction based exchange mechanisms. The results are compared with those obtained without collaboration and by a centralized control. They indicate that horizontal collaboration pays off even in highly competitive environments.     

Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm

This paper presents a bi-objective VMI problem in a single manufacturer-single vendor multi-retailer (SM-SV-MR) supply chain, which a redundancy allocation problem is incorporated. In the hybridized problem, a manufacturer produces a single item using several machines that work in series, and stores it in a warehouse to replenish one vendor who delivers it to several retailers using the shortest possible route. A novel meta-heuristic, called hybrid bat algorithm (HBA), with calibrated parameters is utilized to find a near-optimum solution. To show the efficiency of HBA, the results are compared to the ones using the traditional BA and a genetic algorithm.     

A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling

We propose an efficient evolutionary multi-objective optimization approach to the capacitated facility location–allocation problem (CFLP) for solving large instances that considers flexibility at the allocation level, where financial costs and CO₂ emissions are considered simultaneously. Our approach utilizes suitably adapted Lagrangian Relaxation models for dealing with costs and CO₂ emissions at the allocation level, within a multi-objective evolutionary framework at the location level. Thus our method assesses the robustness of each location solution with respect to our two objectives for customer allocation. We extend our exploration of selected solutions by considering a range of trade-offs for customer allocation.     

Policy,users and discourses: Examples from bikeshare programs in (Kolkata) India and (Manila) Philippines

This paper examines two bikeshare programs implemented in two Global South cities, examining the role of users in promoting sustainable transport. To explore the sustainability of smart cycling, we argue that it is important to understand the prevailing administrative and socio-institutional practices within a given context. For the effective stabilisation of smart regimes, harmony between the administrative and socio-institutional practices must be established. In this context, we introduce a complementary approach to understanding transitions. Maintenance of political commitments and institutional support are crucial for cycling success, not incidental footloose initiatives. We explore two case studies in the context of the Global South, in the first one top-down policies and planning initiatives dictate the directions of transitions by enabling or constraining user routines. In the second one, citizens take control to resolve a transport deficit by initiating and driving a very bottom-up user-led transition narrative. We propose a framework to cater to the unique political, cultural and smart discourses of the Global South and the role of users in conjunction with the administrative and socio-institutional practices around them. Investigating both the bikeshare cases through the lens of this framework provides unique insights extending our knowledge beyond the built environment features of sustainable planning initiatives. Our findings reveal the complex narratives that are in play in developing nations and conclude that understanding and realising cycling transitions in southern megacities require a different approach compared to the Global North.     

Service quality in a mid-sized air terminal: A SEM-MIMIC ordinal probit accounting for travel,sociodemographic, and user-type heterogeneity

Service quality of the airline industry is still unexplored, if compared to the public transport service quality literature. In this paper, we propose an analysis of the services provided by an Italian airport based on an SEM approach. Specifically, we propose a SEM-MIMIC ordinal Probit capturing the heterogeneity in perceptions of air transport passengers and identify groups of passengers with similar assessments of the services. Results suggest the presence of four constructs affecting the overall satisfaction at the terminal, namely information, control, environment, and food service. Results also suggest that there are two different user-types: accessory user (who uses ticket office, luggage trolleys, and escalator lifts), and technology user (who uses charging stations, airport website, and airport wi-fi).     

Analysis of airport noise through LAeq noise metrics

The methodology used in several countries for airport noise simulations, including Brazil, is based on Day-Night Sound Pressure Level (DNL) metric. However, DNL metrics can in some cases bring distortions for sound levels, daily and nightly. The purpose of this study is to make an analysis of airport noise through the L_Aeq metric and propose new alternatives based on Day Equivalent Sound Level (L_AeqD) and Night Equivalent Sound Level (L_AeqN) noise metrics. We also apply the concept of acoustic influence areas for the analysis.     

The relationship between on-time performance and airline market share: a new approach

We propose a new method of modeling the relationship between on-time performance and market share in the airline industry. The idea behind the method is that the passengers’ decision to remain (use same airline) or switch (use other airlines) at time t depends on whether they have experienced flight delays at time t−1 or not. More specifically, we posit that the passengers who experienced flight delays are more likely to switch airlines for the subsequent flight than those passengers who did not experience delays. To capture such effect, we develop an aggregate-level Markovian type model that estimates the transition probability matrices separately for the passengers who experienced flight delays at time t−1 and for those who did not experience delays. The model was calibrated with the US DOT data. The study results imply that, once experiencing flight delays, passengers are more likely to switch airlines. The results also imply that on-time performance affects a carrier’s market share primarily through the passengers’ experience, and not though the “advertisement” of performance.     

A location-routing model for prepositioning and distributing emergency supplies

We propose a two-stage location-routing model with recourse for integrated preparedness and response planning under uncertainty. The model is used for risk management in disaster situations where there are uncertainties in demand and the state of the infrastructure. We solve the two-stage model by converting it into a single-stage counterpart. The latter is then implemented in an illustrative example. Comparative analyses are run to investigate the (1) value of planning location and routing in a single model, (2) value of transshipment, (3) differences when an expected-value objective is used, and (4) value of transshipment in the expected-value model.     

Regulation in the air: price-and-frequency caps

In spite of deregulation on the air-transportation markets, many connections are still operated by a single operator on regional markets, in particular in Europe. Evidence thus calls for some regulation in this industry. There is, however, a great concern for the (possibly negative) consequences of price regulation on the quality of services. We argue that both aspects should be considered jointly and propose a mechanism for the decentralization of the optimal structure of services. The regulatory procedure is based on the sole book-keeping data and requires the regulator to use only an estimate of travellers’ average value of time.     

Selecting between batch and zone order picking strategies in a distribution center

An order picking strategy in a distribution center (DC) defines the manner in which pickers navigate the picking area to pick items from storage locations. We focus on the problem of selecting between a batch picking and a zone picking strategy. For this problem, we propose a cost model to estimate the cost of each type of picking strategy. In our cost model we consider the effects of pick-rate, picker blocking, workload-imbalance, and the sorting system requirement. Through an example problem, we show how system throughput, order sizes, item distribution in orders, and wavelength affect the picking strategy selection decision.     

A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows

For VRP with time windows (VRPTW) solved by conventional cluster-first and route-second approach, temporal information is usually considered with vehicle routing but ignored in the process of clustering. We propose an alternative approach based on spatiotemporal partitioning to solving a large-scale VRPTW, considering jointly the temporal and spatial information for vehicle routing. A spatiotemporal representation for the VRPTW is presented that measures the spatiotemporal distance between two customers. The resulting formulation is then solved by a genetic algorithm developed for k-medoid clustering of large-scale customers based on the spatiotemporal distance. The proposed approach showed promise in handling large scale networks.