Consolidation effects: Whether and how inventories should be pooled

This paper presents a framework for deciding whether and how inventories should be pooled, using the consolidation effect as a cornerstone tool to measure inventory costs, service levels, and total costs. Based on the random generation of different scenarios, it is indicated the adequacy of inventory centralization, regular transshipments, and independent systems to a given set of demand, lead time, and holding costs characteristics. Sensitivity analyses on mathematical expressions are performed to determine when one alternative is preferable in terms of total costs. Real settings are also presented in light of the framework developed.     

考虑换乘费用的城市公共交通票价优化

换乘所产生的附加费用,如时间和票价等,导致配流影响因素产生变化,如果沿用传统方式将降低预测精度和可靠性。通过引入换乘次数和方式等因子计算出行等待、乘车、换乘及风险评估预留时间等,定义广义出行费用与计算方法;建立双层规划模型求解最优票价,最后通过算例分析弹性出行需求、换乘费用、票价之间的关系。计算结果表明,换乘费用对出行需求的影响小于票价优化对出行需求的影响,优化票价随换乘费用增加而加速降低,为公共交通票价优化提供研究依据。     

Consolidation effects and inventory portfolios

This paper presents a formal analysis of the consolidation effect in a wider perspective. While demonstrating that the stock saving structure depends on the interaction between the coefficient of variation of demand and the ratio between inventory ordering and holding costs, this research indicates that the ratio between the standard deviations of lead time at potential facilities is the key variable for consolidation. Sensitivity analyses are also performed to address common managerial issues, which can arise during the consolidation decision, such as the impact on total costs and the assumption of uncorrelated demands.     

Incorporating location,routing and inventory decisions in supply chain network design

This paper for the first time presents a novel model to simultaneously optimize location, allocation, capacity, inventory, and routing decisions in a stochastic supply chain system. Each customer’s demand is uncertain and follows a normal distribution, and each distribution center maintains a certain amount of safety stock. To solve the model, first we present an exact solution method by casting the problem as a mixed integer convex program, and then we establish a heuristic method based on a hybridization of Tabu Search and Simulated Annealing. The results show that the proposed heuristic is considerably efficient and effective for a broad range of problem sizes.     

The future of airline distribution

This paper provides an overview of the changes taking place in airline distribution and evaluates the impact of these changes on the key stakeholders; the airlines, travel agents, global distribution systems companies and corporate travellers. Conclusions as to the future of airline distribution are drawn. It is likely that global distribution systems deregulation will lead to the fragmentation of airline inventories across different distribution channels. Airlines will seek to increase the proportion of sales they make directly on their own website, thereby reducing their costs. Travel management companies will need to demonstrate their value to corporate clients clearly. Corporate clients are most concerned about ensuring access to the widest possible range of airline products and tariffs, at the same time as distribution costs are removed from the value chain.     

Transportation uncertainty and international trade

This paper uses a numerical framework to demonstrate that uncertainty in the arrival time of foreign goods can substantially reduce the demand for foreign goods. It further reveals that the impacts of falling transport costs and shipment time on international trade growth could be discounted, if uncertainty arises in the arrival time of the imported goods. This in turn suggests that reduced uncertainty, which is possibly the results of transportation improvements, might have contributed to the growth experienced in world trade growth over the past several decades. Thus, neglecting the roles of improvements in international transportation arrangements and reduced uncertainty will lead to underestimating the contribution of transportation improvements to trade growth.     

Mixed truck delivery systems with both hub-and-spoke and direct shipment

This paper studies a mixed truck delivery system that allows both hub-and-spoke and direct shipment delivery modes. A heuristic algorithm is developed to determine the mode of delivery for each demand and to perform vehicle routing in both modes of deliveries. Computational experiments are carried out on a large set of randomly generated problem instances to compare the mixed system with the pure hub-and-spoke system and the pure direct shipment system. The experiment results show that the mixed system can save around 10% total traveling distance on average as compared with either of the two pure systems.     

A rolling planning horizon heuristic for scheduling agents with different qualifications

This paper presents an optimization model for the tour scheduling problem for agents with multiple skills and flexible contracts in check-in counters at airports. The objective is to minimize the total assignment costs subject to demand fulfillment and labor regulations. In order to solve this problem we develop a rolling planning horizon-based heuristic. Our heuristic is robust and provides near-optimal schedules within reasonable computation time for real-world cases, although the parameter selection is important to its performance. In addition, we discuss the impact of the skill distribution on the scheduling costs for several instances.     

Marginal valuations of travel time and scheduling,and the reliability premium

Previous works have established synonymity between the notions of uncertainty and unreliability, exploiting this in deriving marginal valuations of travel time and scheduling under uncertainty. Whilst valid for forecasting demand, such valuations fail to illuminate the costs of bearing unreliability – herein referred to as the ‘reliability premium’. The paper derives marginal valuations of travel time and scheduling at the certainty equivalent, showing these to diverge from those under uncertainty. That divergence, which represents the marginal valuation of reliability, raises the possibility of bias should the costs of unreliability not be included in appraisal.     

Replenishment and lead time decisions in manufacturer–retailer chains

This study investigates the decisions of replenishment and lead-time reduction for a single-manufacturer multiple-retailer integrated inventory system in which the probability distribution of demand for each retailer is unknown but its mean and variance are given. A decision model is presented and a minimax distribution free procedure is applied to determine the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost can be minimized. A decision support system has been implemented on a personal computer to illustrate the application of the model.     

Recovering from demand disruptions on an air cargo network

In this work we introduce the Air Cargo Schedule Recovery Problem (ACSRP). In this problem, a carrier airline has to reschedule flights and requests to adapt to last-minute demand changes. We consider three different possible crew management policies that translate into three different way to evaluate the costs of deviating from the original schedule. We formulated the ACSRP as a mixed integer linear programming problem, and tested our implementation on 24 original schedules with up to 30 orders and 8 airports, and 4 different disruption scenarios for each one. Our results show that, against a benchmark recovery policy where only cargo is re-routed, recovery can yield savings of roughly 10%.     

Expanding airport capacity of cities under uncertainty: Strategies to mitigate congestion

Airport capacity constraints are increasingly challenging the growth of air traffic. At the same time, decision-making about airport capacity investments is extremely complex, involving trade-offs. This paper’s objective is to optimise a privately owned airport system’s capacity investment decision in a city under demand uncertainty. Next to the investment size, our real options model incorporates the timing of the investment, as well as the cost of congestion. The results reveal that the larger a city’s initial airport capacity, the smaller its investment will relatively be and the lower the occupancy rate threshold at which investment will take place. We also show that, in case of a higher demand growth combined with more demand uncertainty, the city will benefit from a significantly larger investment, but made later at a higher occupancy rate. In this case, cities with a small initial capacity will sometimes even more than double current capacity. Higher airport charges and an increase in non-aeronautical revenues both lead to a later investment in more capacity, due to the increased project attractiveness. An increase in congestion costs results in a larger investment made earlier, in order to eliminate delays. Airport operational cost and capacity holding cost increases both lead to smaller investments.     

Optimizing flight equencing and gate assignment considering terminal configuration and walking time

Operating airline hub-and-spoke networks (HSN) rather than direct flights among city pairs may significantly reduce supplier cost; however, passengers' travel time may significantly increase due to increased transfer and in-flight time. The costs considered in this study are hub-related and incurred by passengers and aircraft (i.e., passenger transfer, flight dwelling, and gate occupancy). The objective is to minimize the total cost by optimizing flight sequence (i.e., arrivals and departures) and gate assignment, while considering transfer speed, transfer demand, flight size, gate size and terminal configuration. A real-world HSN whose hub airport (HA) is located at Xianyang International Airport (XIY) in Xi'an, China is analyzed. The optimized solutions and their relations to various model parameters are explored.     

Effects of non-aeronautical activities at airports on the public transport access system: A case study of Zurich Airport

Many planning authorities and airports study measures to increase public transport use for airport ground access and egress. At the same time, an increase in real estate development at and around airports is occurring, both due to airports seeking new revenue possibilities and other developers attempting to profit from high value locations. This paper considers non-aeronautical activities at large airports, largely commercial centres and transit hubs, as land uses that have the potential to improve the situation for operating public transport services. In order to assess potential benefits and disadvantages, four research questions are considered: (1) Can the additional travel volume reach levels at which it has a significant impact? (2) To what extent do non-aeronautical activities influence the public transport access system? (3) Is the resulting demand distribution better or worse regarding peaking behaviour? (4) Is there a potential for the resulting overall demand to bring about capacity shortages?A case study is conducted at the airport of Zurich, Switzerland, which finds that non-aeronautical activities in the direct airport vicinity have led to a situation where the operation of public transport services is much more viable due to overall higher passenger numbers and a more even distribution throughout the day. It is concluded that locating non-aeronautical activities at airports can, in addition to providing commercial benefits to developers, lead to a situation where improved public transport services become feasible.     

Pre-distribution and post-distribution cross-docking operations

In this paper, we construct analytical models for distribution strategies with two major types of cross-docking, pre-distribution cross-docking (Pre-C) and post-distribution cross-docking (Post-C). A traditional distribution center system is also discussed for comparison purposes. Three models are compared pair-wisely. Analytical results show that, Pre-C is preferred for environments with shorter supply lead time and lower uncertainty of demand, without the benefits of risk-pooling. The Post-C mitigates the weakness of the Pre-C at the expense of higher operations cost spent at the cross-dock. Numerical experiments are conducted to support our results and explore other findings.     

Space-time demand cube for spatial-temporal coverage optimization model of shared bicycle system: A study using big bike GPS data

As a sustainable transport mode, bicycle sharing is increasingly popular and the number of bike-sharing services has grown significantly worldwide in recent years. The locational configuration of bike-sharing stations is a basic issue and an accurate assessment of demand for service is a fundamental element in location modeling. However, demand in conventional location-based models is often treated as temporally invariant or originated from spatially fixed population centers. The neglect of the temporal and spatial dynamics in current demand representations may lead to considerable discrepancies between actual and modeled demand, which may in turn lead to solutions that are far from optimal. Bike demand distribution varies in space and time in a highly complex manner due to the complexity of urban travel. To generate better results, this study proposed a space-time demand cube framework to represent and capture the fine-grained spatiotemporal variations in bike demand using a large shared bicycle GPS dataset in the “China Optics Valley” in Wuhan, China. Then, a more spatially and temporally accurate coverage model that maximizes the space-time demand coverage and minimizes the distance between riders and bike stations is built for facilitating bike stations location optimization. The results show that the space-time demand cube framework can finely represent the spatiotemporal dynamics of user demand. Compared with conventional models, the proposed model can better cover the dynamic needs of users and yields ‘better’ configuration in meeting real-world bike riding needs.     

The impacts of Radio Frequency Identification (RFID) technology on supply chain costs

Radio Frequency Identification (RFID) is regarded as a promising technology for the optimization of supply chain processes since it improves manufacturing and retail operations from forecasting demand to planning, managing inventory, and distribution. This study uses a simulation model to calculate the expected benefits of an integrated RFID system on a three-echelon supply chain obtained through performance increases in efficiency, accuracy, visibility, and security level. The study investigates how the product value, lead time, and demand uncertainty affect the performance of the integrated RFID supply chain in terms of cost factors at the echelon level.     

The lead-time reliability paradox and inconsistent value-of-reliability estimates

The value-of-reliability (VOR) reflects the savings in inventory-system costs from more reliable (less variable) lead times. Previous studies have revealed that more reliable, but positively skewed, lead times could actually increase optimal safety inventory when the probability of satisfying all demand during a replenishment cycle drops below 70%. Researchers claim that this paradox affects most firms and that it explains the inconsistent VOR estimates found in the transportation economics literature. Our investigation reveals that firms interested in high product availability may safely ignore the paradox and that less lead-time variability consistently increases VOR, the paradox notwithstanding.     

Airline cost changes: To what extent are they passed through to the passenger?

Since the start of the Millennium airline costs have been highly volatile, mainly due to large fluctuations in jet fuel prices. An important question for airlines and regulators is whether airlines are able to pass through cost changes to their prices. Little empirical evidence on the pass-through of costs exists. In this paper, we investigate which pass-through rates are most likely. According to economic theory, the pass-through of costs depends strongly on the type of cost increase (firm-specific or sector-wide) and market conditions (monopoly, oligopoly, perfect competition). In monopolistic markets, the shape of the demand curve also matters (linear, constant elasticity, log, power function). A pass-through rate of 100% is often assumed based on the reasoning that the aviation sector is highly competitive. We analyse market concentration in all airline markets in the world, and generally find a high level of concentration. Additionally, different airlines offer different products based on a variety of factors, including service, flight frequency, legroom, bags allowed on board, flight time and transfer time. Therefore, most aviation markets can be characterised as differentiated oligopolies. As airlines choose their quantities first (flight schedules) and adapt their prices to demand (yield management), we consider the Cournot model the best choice. In such markets, firmspecific cost changes will be passed through by a rate of less than half while sector-wide cost changes are passed through by a rate of more than half. In specific situations, the pass-through rate may be different. Examples are limited airport capacity (congestion), cross-subsidization, and the extent to which there is a level playing field.     

Robust hub network design problem

This paper presents a robust formulation for the uncapacitated single and multiple allocation hub location problem where demand is uncertain and its distribution is not fully specified. The proposed robust model is formulated as a mixed integer nonlinear program and then transformed into a mixed integer conic quadratic program. An efficient linear relaxation strategy is proposed which is found to deliver the optimal solutions for all the cases considered in this paper. Numerical experiments suggest location of more number of hubs when accounting for demand uncertainty using robust optimization compared to the deterministic setting.