Application of Online Reverse Auctions in Revenue Management of Airline Company

Based On the online reverse auction formalism in Priceline.com, In this paper,the use of online reverse auctions in airline companies revenue management is highlighted.This research examines the process of online reverse auctions in detail, point out the potential benefits of online reverse auctions. At last we examines how the online reverse auction mechanism design for optimal allocation.

Winner determination problem with loss-averse buyers in reverse auctions

Reverse auctions have been widely adopted for purchasing goods and services. This paper considers a novel winner determination problem in a multiple-object reverse auction in which the buyer involves loss-averse behavior due to uncertain attributes. A corresponding winner determination model based on cumulative prospect theory is proposed. Due to the NP-hard characteristic, a loaded route strategy is proposed to ensure the feasibility of the model. Then, an improved ant colony algorithm that consists of a dynamic transition strategy and a Max-Min pheromone strategy is designed. Numerical experiments are conducted to illustrate the effectiveness of the proposed model and algorithm. We find that under the loaded route strategy, the improved ant colony algorithm performs better than the basic ant colony algorithm. In addition, the proposed model can effectively characterize the buyer's loss-averse behavior.

Optimal Procurement Management by Reverse Auctions for a Price-Setting Newsvendor

In this paper, we study the optimal procurement management by reverse auctions for a price-setting newsvendor(retailer) in a single period setting. The retailer facing price-dependent stochastic demand first designs a procurement contract and then invites the suppliers to bid for this contract in the reverse auction. The winning supplier produces and delivers the demanded quantity.The retailer obtains the procurement quantity and simultaneously determines the retail price. By using the price elasticity of the lost-sales rate, we show that the retailer’s expected profit(excluding the procurement cost) is a concave function of the purchased quantity, which can be used to obtain the optimal procurement and retail pricing decisions for the retailer. Further, when the underlying random term of demand function is normally distributed under left-truncation(at 0), we get the analytical expressions of the purchased quantity and expected profit function for the retailer. Moreover, some numerical examples are given.

A Reverse Auction Mechanism for Time-Varying Multidimensional Resource Allocation in Vehicular Fog Computing with Cloud and Edge Collaboration

It is a hot issue to allocate resources using auction mechanisms in vehicular fog computing(VFC)with cloud and edge collaboration.However,most current research faces the limitation of only considering single type resource allocation,which cannot satisfy the resource requirements of users.In addition,the resource requirements of users are satisfied with a fixed amount of resources during the usage time,which may result in high cost of users and even cause a waste of resources.In fact,the actual resource requirements of users may change with time.Besides,existing allocation algorithms in the VFC of cloud and edge collaboration cannot be directly applied to time-varying multidimensional resource allocation.Therefore,in order to minimize the cost of users,we propose a reverse auction mechanism for the time-varying multidimensional resource allocation problem(TMRAP)in VFC with cloud and edge collaboration based on VFC parking assistance and transform the resource allocation problem into an integer programming(IP)model.And we also design a heuristic resource allocation algorithm to approximate the solution of the model.We apply a dominant-resource-based strategy for resource allocation to improve resource utilization and obtain the lowest cost of users for resource pricing.Furthermore,we prove that the algorithm satisfies individual rationality and truthfulness,and can minimize the cost of users and improve resource utilization through comparison with other similar methods.Above all,we combine VFC smart parking assistance with reverse auction mechanisms to encourage resource providers to offer resources,so that more vehicle users can obtain services at lower prices and relieve traffic pressure.

An Improved Reverse Auction for Addressing Water Quality in Agricultural Watersheds Using Coupled Simulation-Optimization Models

As nutrients and sediment in agricultural watersheds continue to degrade water quality, attention is increasingly given to reverse auctions to cost-effectively address these pollutants. Typically, reverse auctions include a selection process which depends on both the monetary bid and a ranking of the environmental benefit, where the latter is often approximated using simple models, such as the Universal Soil Loss Equation （USLE）. When the environmental objective is to improve water quality, the cost-effectiveness of such ranking methods cannot always be assured since simple models may poorly approximate the effects on downstream water quality. In this paper, we introduce an alternative reverse auction approach that takes advantage of richer watershed process models and optimization tools that are now much more commonly available. This ＂improved＂ reverse auction allows decision-makers to better consider the cost-effective assignment of conservation practices and to address water quality or other environmental objectives. In a spatially detailed simulation, we demonstrate how this approach can improve the design of a reverse auction for the Raccoon River Watershed in Iowa, and estimate the potential gains from using the simulation-optimization approach relative to simpler ranking methods for selecting bids. We also point out that simple bid ranking schemes may not yield sufficient nutrient reductions to achieve water quality goals but bids areeasily selected to achieve any feasible water quality improvement in the ＂improved＂ auction process.

A Reverse Auction Framework for Hybrid Access in Femtocell Network

In the two-tier macro-femto heterogeneous network, hybrid access is regarded as the most ideal access con- trol approach to mitigating macro-femto cross-tier interference and enhancing overall network performance. However, the implementation of hybrid access is hindered by a lack of incentive market mechanism to motivate private femtocell owners to offer access permissions to macro users. In this paper, we propose a reverse auction framework for access permission transaction between a macrocell operator and multiple femtocell owners to promote hybrid access. Our goal is to maximize social welfare while guaranteeing the truthfulness of the auction. Since the coverage of multiple femtocells may overlap, we partition each cell to adjust the granularity of access permission availability. We first propose a Vickery-Clarke-Grove （VCG）-based mechanism, which costs the least among all auction mechanisms that produce maximum social welfare. As the VCG mechanism is too time-consuming, we propose two alternative truthful mechanisms, namely, generalized second- price and suboptimal mechanism. We further extend the auction framework to the scenario where femtocell owners have heterogeneous valuations for access permissions in different locations.

Mechanism design of reverse auction on concession period and generalized quality for PPP projects

Reverse auctions of PPP projects usually require the bid to specify several characteristics of quality and the concession period to be fulfilled. This paper sets up a summary function of generalized quality, which contributes to reducing the dimensions of information.Thus, the multidimensional reverse auction model of a PPP project can be replaced by a two-dimensional direct mechanism based on the concession period and the generalized quality. Based on the theory of the revelation principle, the feasibility conditions, equilibrium solution and generalized quality requirements of such a mechanism,considering the influence of a variable investment structure are described. Moreover, two feasible multidimensional reverse auctions for implementing such a direct mechanism: Adjusting the scoring function and establishing a special reverse auction rule are built. The analysis shows that in these types of reverse auctions, optimal allocation can be achieved, the social benefit under the incomplete information will be maximized, and the private sector with the highest integrated management level wins the bid. In such a direct mechanism, the investment and financial pressure of the public sector can be reduced.

An Integrated Incentive Framework for Mobile Crowdsourced Sensing

Currently, mobile devices （e.g., smartphones） are equipped with multiple wireless interfaces and rich builtin functional sensors that possess powerful computation and communication capabilities, and enable numerous Mobile Crowdsourced Sensing （MCS） applications. Generally, an MCS system is composed of three components： a publisher of sensing tasks, crowd participants who complete the crowdsourced tasks for some kinds of rewards, and the crowdsourcing platform that facilitates the interaction between publishers and crowd participants. Incentives are a fundamental issue in MCS. This paper proposes an integrated incentive framework for MCS, which appropriately utilizes three widely used incentive methods： reverse auction, gamification, and reputation updating. Firstly, a reverse-auction-based two-round participant selection mechanism is proposed to incentivize crowds to actively participate and provide high-quality sensing data. Secondly, in order to avoid untruthful publisher feedback about sensing-data quality, a gamification-based verification mechanism is designed to evaluate the truthfulness of the publisher＇s feedback. Finally, the platform updates the reputation of both participants and publishers based on their corresponding behaviors. This integrated incentive mechanism can motivate participants to provide high-quality sensed contents, stimulate publishers to give truthful feedback, and make the platform profitable.

A strategy-proof auction mechanism for service composition based on user preferences

Service composition is an effective method of combining existing atomic services into a value-added service based on cost and quality of service(QoS).To meet the diverse needs of users and to offer pricing services based on QoS,we propose a service composition auction mechanism based on user preferences,which is strategy-proof and can be beneficial in selecting services based on user preferences and dynamically determining the price of services.We have proven that the proposed auction mechanism achieves desirable properties including truthfulness and individual rationality.Furthermore,we propose an auction algorithm to implement the auction mechanism,and carry out extensive experiments based on real data.The results verify that the proposed auction mechanism not only achieves desirable properties,but also helps users find a satisfactory service composition scheme.