Multi-attribute Reverse Auction Research Articles

A Multi-Attribute Auction Mechanism based on Conditional Constraints and Conditional Qualitative Preferences

Auctioning multi-dimensional items is a key challenge, which requires rigorous tools. This study proposes a multi-round, first-score, semi-sealed multi-attribute reverse auction system. A fundamental concern in multiattribute auctions is acquiring a useful description of the buyers' individuated requirements: hard constraints and qualitative preferences. To consider real requirements, we express dependencies among attributes. Indeed, our system enables buyers eliciting conditional constraints as well as conditional preferences. However, determining the winner with diverse criteria may be very time consuming. Therefore, it is more useful for our auction to process quantitative data. A challenge here is to satisfy buyers with more facilities, and at the same time keep the auctions efficient. To meet this challenge, our system maps the qualitative preferences into a multi-criteria decision rule. It also completely automates the winner determination since it is a very difficult task for buyers to estimate quantitatively the attribute weights and define attributes value functions. Our procurement auction looks for the outcome that satisfies all the constraints and best matches the preferences. We demonstrate the feasibility and measure the time performance of the proposed system through a 10-attribute auction. Finally, we assess the user acceptance of our requirements specification and winner selection tool.

Winner determination for risk aversion buyers in multi-attribute reverse auction

Multiattribute reverse auction has become prevalent for the procurement of goods and services in recent days. In such an auction, a group of potential suppliers bid to win the contract that has been defined in multiple attributes by the buyer for providing goods or services. A corresponding winner determination problem provides important decisions for the buyer to select its best supplier. Considering the buyer with risk aversion behavior and suppliers with positive and negative attributes described by a combination of crisp data, interval numbers and linguistic variables in a multiattribute reverse auction setting, we incorporate the prospect theory (PT) into the “benefits, opportunities, costs and risks” (BOCR) framework to propose a novel PT-BOCR solution method. The effectiveness and distinct advantage of our method on dealing with the buyer׳s risk averse attitude are demonstrated in comparison with other known methods. Computational results indicate that the PT-BOCR method is robust with respect to the variance of suppliers׳ attributes and the level of reference points. An interesting result reveals that when suppliers׳ attributes vary a lot, the degree of risk aversion increases or decreases depending on the reference point is low or high. The PT-BOCR method could be a useful tool for risk aversion buyers to avoid losses and for suppliers to win the bids by improving their attributes.

Simulation and analysis of bid evaluation behaviors for multiattribute reverse auction

Reverse auctions with multiattributes are widely used for centralized procurements of large enterprises and government departments. The bid evaluation mechanism is a key factor for a fair auction and resource allocation. The current bid evaluation process is usually done by two groups, a business expert group and a technical expert group, separately. Taking bounded rationality as a precondition, we analyze the existence of antagonistic feelings between the two groups. The antagonistic feelings may grow as time goes by. To verify the discovered points, a multiagent-based approach is used to simulate the bid evaluation behaviors. The prototype system of a current bid evaluation mechanism is described by a multiagent model. In the model, the behaviors of both auctioneer and bidders are described by the attributes of each agent and decision rules. Their interactions are described by the collaboration and information exchange between different agents. The procedure of multiagent simulation is specifically presented. Then, the multiagent simulation system is developed and repeatedly runs on the platform of MATLAB GUI while adjusting relevant parameters. The results demonstrate that the behaviors of raising and repressing bid scores are increasingly severe with the passage of time. The result is that differences between the two groups increase with a decrease in the objectiveness of experts. The accumulation of antagonistic feelings can be obviously observed. The current mechanism is unfair to the bidders, as it may make the best bid lose the auction. To solve this problem, two modified bid evaluation mechanisms are suggested. The simulation comparison results show that the new bid evaluation mechanisms can efficiently weaken the antagonistic feelings of the two groups. Finally, three constructive suggestions are put forward to the organizer of tendering and bidding.

English multi-attribute reverse auction model with the minimum non-monetary attributes bidding values

We propose a new English multi-attribute reverse auction model with the minimum non-monetary attributes bidding values under the procurement auction scenario. The existing multi-attribute auction models usually do not include the constraints on non-monetary attributes bidding values. Obviously, it is unreasonable because the auctioneer usually will have a requirement for the non-monetary attribute value. So we extend the multi-attribute reverse auction model and propose the structurised mathematical expressions of the optimal bidding price and non-monetary attributes for the bidders’ bidding decision. Further, we analyse the mathematical characteristics and the economic implications of these expressions. Finally, we present two numerical examples to demonstrate the minimum non-monetary attributes bidding values indeed impact on the bidders’ bidding decision and the final auction result.

Multi-Attribute Auctioning Resource in Grids: Model and Protocols

Auction models and protocols are found efficient in managing resources allocation, which are a key technology in grid computing system. In this paper, a new multi-attribute multi-round reverse auction is proposed, and related reverse auction based protocols are designed. The resource user’s satisfaction degree is introduced into the traditional grid resource allocation problem to help the grid resource broker make multi-attribute decisions with incomplete information. Numerical simulating experiments show that our model and protocols can satisfy the resource user’s quality demand on multiple attributes, and achieve high efficiency in user utility. The results also illustrate that the on-line multi-attribute algorithm in ONMRA protocol has better performance in an on-line setting for grid allocation. DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3347

Auction-Based Resource Allocation in Computational Grids

Auction techniques have been becoming the key methods in grid resource allocation. In this paper, we propose the multi-attribute reverse auction models for computational grid resource based on the designed satisfaction degree function. The fairness is also introduced into the models and protocols to match the reality. Two auction-based protocols are presented, i.e., the offline multi-attribute auction-based protocol and the on-line multi-attribute auction-based protocol. The goal is to help the resource user make multi-attribute decisions with complete information or incomplete information. Results from simulation experiments show that these two protocols can achieve market efficiency and fairness in most instances.

Relationship preserving multi-attribute reverse auction: A web-based experimental analysis

Repeated use of reverse auction often degrades the buyer–supplier relationship. Theoretical studies show that providing incentive to the losing but competing suppliers can keep them interested to participate in future auctions thereby maintaining a healthy level of competition. We conduct web-based experiments to validate this theoretical observation in multi-attribute reverse auctions. We compare incentive-oriented and standard multi-attribute reverse auctions and demonstrate that the results in the laboratory setting corroborate the theoretical findings. Adopting incentive-oriented mechanism, the buyer is able to provide better utility to suppliers while protecting her own. We conclude that such a mechanism can reduce the negative perception of the suppliers and help build better buyer–supplier relationship in the long run.

An Interactive Approach for Multi-Attribute Resource Allocation in Grids

Auction-based models and protocols introduce money and pricing as the technique for coordination between users and producers of resources in grids. In this paper, we propose a multi-attribute reverse auction protocol to allocate grid resource. In order to enhance the information efficiency we develop a novel interactive approach supporting both user agents and producer agents. In this approach, an iterative algorithm used to estimate the resource user’s preference utility function can facilitate producer agents to update their bids with incomplete information. Numerical simulating experiments show that our approach can satisfy the resource user’s quality demand on multiple attributes, and achieve high efficiency in user utility. The results also provide an idea to analyze the two-side private information problem in gird resource allocation.

Bid evaluation behavior in online procurement auctions involving technical and business experts

Multi-attribute reverse auction-based procurement has been widely used by large organizations. The attributes of the auctioned objects are usually divided into two groups: technical and business attributes. They are reviewed and scored by technical and business experts who act as referees in the bid evaluation process. To analyze their bid evaluation behavior, we built a model for a multi-attribute reverse auction. With correlations between the bid evaluations of the different referee groups across the attributes, the bid evaluation problem is not the usual multi-attribute decision-making problem. We assess the cause–effect relationship that is present, and show that antagonism between referee groups tends to grow over time. We tested how this works with data from simulated auctions. To diminish the potential for antagonism between the two referee groups, we propose a modified bid evaluation mechanism. We also conducted role-playing experiments involving the referee behaviors as a means for assessing the proposed mechanism. Our results suggest that the modified bid evaluation mechanism is beneficial.

A Multi-attribute Reverse Auction Decision Making Model Based on Linear Programming

Because of the popularity of the Internet, e-commerce is used more and more widely around the world. At the same time, the business style of procurement has also changed a lot. Under this circumstance, online reverse auction came into being. Based on the theoretical knowledge and practical status quo, this paper has studied some key issues, such as the applicable conditions and the basic process of multi-attribute reverse auction, especially focused on the mechanism of decision-making in the process of performing multi-attribute reverse auction. Again in this paper, AHP method has been employed to determine the weight of each attribute; moreover, based on the linear programming theory, a multi-attribute reverse auction model has been established. Finally, a calculation example has been conducted to demonstrate the utility and availability of the model.

Online Multi-Attribute Reverse Auction Mechanism Design Based on Utility

A good auction mechanism is able to release the information who owns to the other side who lacks of. In order to ensure a positive flow of information and to improve the active participation of suppliers, negotiation mechanism is introduced, and suppliers can participate in the design of auction mechanism. Several rounds of English auction is applied to determining the final winner. Taking into account that the buyer has a preference on the property, we use AHP to calculate final weights, and use multi-attribute utility function to calculate the greatest utility as the winner.

Anonymity And Verifiability In Multiattribute Reverse Auction

The use of e-Auction services has been increasing in recent years. Security requirements in conducting e-Auctions are mainly bid privacy, anonymity and public verifiability. Most of the secure protocols concentrate on privacy and anonymity, which are achieved through bidder-resolved multi-party computation, assuming two or more trusted third parties, either through numerous auctioneers or with asymmetric models in which the commercial entity of an auction issuer or registration manager is assumed in addition to the auctioneer. Multi-attribute reverse auctions promise higher market efficiency and effective information exchange. This work extends and uses the existing schemes. This scheme uses scoring function, winner determination in multi-attribute auctions to implement public verifiability. Anonymity is achieved through bidder side pseudonym generation. By results and analysis we say this is very simple and effective scheme. This scheme ensures public verifiability and anonymity in multi-attribute auctions without revelation of the bids received, third parties and complex communications.

A fuzzy TOPSIS based approach for e-sourcing

This study presents a methodology for solving the sealed bid, multi-attribute reverse auction problem of e-sourcing in which the sales item is defined by several attributes, the buyer is auctioneer, and the suppliers are the bidders. There is only one buyer and a number of suppliers. Both qualitative and quantitative attributes of benefit and cost types are considered for solving the winner determination (WD) problem of reverse auction. Here, the WD problem is considered as multi-criteria decision making problem (MCDM). In order to address the imprecision of suppliers or decision makers in formulating the preference value of various attributes in MCDM, a fuzzy TOPSIS based methodology along with a mechanism for determination of fuzzy linguistic value of each attribute is proposed in this article. Entropy method is utilised to enumerate the weights of various attributes automatically without involvement of decision makers. An illustrative example is presented to demonstrate the applicability of the proposed methodology.

Supplier behavior modeling and winner determination using parallel MDP

Behavioral uncertainty of a supplier is a major challenge to a buyer operating in e-procurement setting. Modeling suppliers’ behavior from past transactions, estimation of possible future performance and integrating this knowledge with the winner determination process can bring a new dimension to procurement process automation. We propose a states-space model to capture the uncertainty involved in long-term supplier behavior. The states represent the performance level of a supplier. This behavioral aspect is then integrated with the winner determination process of a multi-attribute reverse auction for efficient supplier selection using parallel MDP. We also propose an implementation framework to collect the feedback on supplier, generate an aggregate performance score and integrate it with the winner determination process. The performance aggregation and winner determination with help of Markov decision process effectively uses the past performance information. In addition, it updates performance information in regular invervals and allevates the problem of maintaining a long history. We compare the MDP-based selection with that of performance score-based selection through a simulation experiment. It is observed that our scheme gives better buyer utility, selects best suppliers and fetches better quality product. The benefits realized through these attributes to the buyer increases the efficiency of the MDP-based selection process.

Information revelation in multiattribute English auctions: A laboratory study

The effects of information revelation on allocational and Pareto efficiency are studied in a multiattribute reverse English auction. The setting is a single sourcing problem in which a buyer seeks to acquire an indivisible object from exactly one of five potential suppliers. Bids are three-dimensional with two non-monetary attributes in addition to the object's price. Results from a computer-based laboratory experiment are reported, and observed differences between two information revelation policies are analyzed with respect to the buyer's utility and suppliers' profits. The results suggest that revealing the buyer's preferences increases allocational efficiency. Suppliers successfully use the additional information to make more profits, but not at the expense of the buyer whose utility increases slightly albeit not significantly.

Bidding decision in multi-attribute reverse auction

We design a decision making model for solving the bidding problem in a sealed bid multi-attribute reverse auction. Bidders in reverse auctions face the problem of decrementing the bid in every round until the final round. Although the bidders receive information from the previous rounds regarding the winning bid, but the decision regarding the bid-decrement is purely subjective. Considering the fuzziness in the available information and the subjective parameters, we develop a new bidding algorithm for multi-attribute reverse auctions using multi-stage fuzzy game technique. In this work, we present the fuzzy decision making model and use this to develop the bidding algorithm for multi-attribute reverse auction. We illustrate the use of the algorithm through an example. The agent using the fuzzy bidding algorithm is able to decide the bid intelligently in every round of the auction. The algorithm may be used by the agents to take bidding decisions adaptively in repeated auction scenario.

Iterative Multi-AttRibute Multi-Unit Reverse Auctions

This article studies iterative multi-attribute auctions for multi-unit procurement. Order splitting among suppliers is allowed in auctions to improve efficiency and take advantage of suppliers' cost structures. Suppliers are also allowed to provide discriminative prices over units based on their cost structures. A mechanism called iterative multi-attribute multi-unit reverse auction (IMMRA) is proposed based on the assumption of the modified myopic best-response strategies. Results from numerical experiments show that the IMMRA achieves market efficiency in most instances. The inefficiency occurs occasionally in special cases when cost structures are significantly different among suppliers. Numerical results also show that the IMMRA results in lower buyer payments than the traditional Vickrey-Clarke-Grove (VCG) payments in most cases without significantly hurting market efficiency.