Bidding Method Research Articles

Analysis of equilibrium-oriented bidding strategies with inaccurate electricity market models

In order to make competitive electricity markets effective, bidding generation companies (GENCOs) need to estimate market demand models according to information available to each of them. However, many stochastic factors (e.g. weather, demand side features) make it very hard for GENCOs to accurately capture the actual market demand in a model. Each GENCO might hold an estimated model deviating, from the real market model as well as from its peers’. Little work has been done in discussing the impacts of model deviations towards the design of GENCO’s bidding strategies.In this paper, the effects of model deviations upon the equilibrium-oriented bidding methods (EOBMs), more specifically conjectural variation (CV) based methods, are studied. We relax the strong assumptions that one uniform and accurate market demand model is employed by all GENCOs in the basic CV-based learning bidding algorithm (CVBA). In this work, the market demand model utilized for bidding by each GENCO is different from each other and from the actual market model as well. The impacts of such model deviations are analyzed from both theoretical and simulation perspective. Theoretical analyses point out that as a consequence of the model deviations it is possible that the basic CVBA algorithm will bring the bidding process into an unstable state. In order to eliminate the effects from inaccurate modeling, a CV-based learning bidding method with data filtering capabilities is proposed. Several sets of simulations have been done to test the impact of the model deviations. The simulation results confirm the theoretical analyses. The feasibility and effectiveness of the proposed bidding methods are also verified. The proposed algorithm can bring systems into stable state even when model deviations exist.

An Efficient Outpatient Scheduling Approach

Outpatient scheduling is considered as a complex problem. Efficient solutions to this problem are required by many health care facilities. This paper proposes an efficient approach to outpatient scheduling by specifying a bidding method and converting it to a group role assignment problem. The proposed approach is validated by conducting simulations and experiments with randomly generated patient requests for available time slots. The major contribution of this paper is an efficient outpatient scheduling approach making automatic outpatient scheduling practical. The exciting result is due to the consideration of outpatient scheduling as a collaborative activity and the creation of a qualification matrix in order to apply the group role assignment algorithm.

효율적인 턴키사업 추진을 위한 클레임 저감방안

Currently, TK(Turn-key) projects have been implemented, the projects on TK basis still have shown several problems rather than its own merits as a bidding method. Increasing the number of claims being occurred during construction process of the projects is reality because of unclear notice of tender documents and conditions of the contract, design review system, and decision process of the qualified bidder. To establish desirable TK projects in domestic market, not only should resonable alternatives for carrying out design review system and selecting the bid winner be set up, but also proper standards for reforming irrational system of contract, bid, and notice of tender related to TK projects. This study is intended to reduce the number of claims and implement efficient projects of apartment construction on TK basis by identifying potential problems through analysis of claim examples of TK projects which have difficulties of revising contract agreement such as drawings and suggesting improvement methods for contract conditions and notice of tender docuements.

Procurement decision making mechanism of divisible goods based on multi-attribute auction

Multi-attribute auction enables negotiation on several attributes in addition to the price such as quality, quantity, time of delivery and service levels. Most of the existing multi-attribute auction mechanisms are designed by considering a unique good or indivisible multiple goods. This paper focuses on designing a multi-attribute auction mechanism for addressing the decision making problem of multi-attribute and multi-source procurement of a kind of homogeneous continuous divisible goods (such as coal, oil, electricity and gas). The suppliers’ optimal bidding strategies are discussed, and a bidding method named the minimum bid increment method is proposed to simulate the overall process of suppliers’ multiple rounds of bidding. Theoretical analysis shows that our auction mechanism is an efficient mechanism, and satisfies the incentive compatibility conditions and the individual rationality conditions. Moreover, a multi-attribute auction example about the steam coal procurement is given to show how to implement our multi-attribute auction mechanism.

공동주택 관리업체 선정방식의 문제점과 개선방안

As the construction of multi-family housings, especially apartments, has been increased since 1970s, the multi-family housing becomes one of the main housing types in Korea. With the increase of multi-family housings, managing them becomes an important issue. Since 2010, the government has made a lowest price award system by a competitive bid compulsory to promote the development of housing management systems. Although competitive bids were implemented, the maintenance company was finally selected by the price without any other consideration. Consequently, the quality of management service was not enhanced. The purpose of this study is to suggest the improvement scheme of multi-family housing management system. In this study, the bidding data of K-apt, the bidding method and the successful tendered price are analyzed. The results of analyzing bidding materials, the proportion of applying a lowest price system was 67.7%. Also many diverse ways to select the best management company were used, but most of these ways were violate the law and guidelines of Ministry of Land, Transport and Maritime Affairs. It meant that the lowest price award system was not implemented by strict standards and didn`t correspond with the needs of residents of apartment. This condition made the housing maintenance quality low and deteriorated the management industry development. To enhance this condition, a new standard to select the management company, which are included contents of quality of managing quality, management expenses and companies` soundness, is necessary.

Consideration of the Environmental Cost in Construction Contracting for Public Works: A+C and A+B+C Bidding Methods

AbstractGrowing concerns about sustainable development have brought about an urgent need to develop global efforts to mitigate environmental impact. Although construction projects and their related activities consume much energy and generate a significant amount of greenhouse gas (GHG) and other diesel emissions, the efforts to mitigate these emissions remain at an early stage. To address this issue, this paper explores opportunities to consider contractors’ green capabilities during the bid evaluation phase. Based on reviews of the success story of the A+B bidding method, this paper suggests a modified bidding system in which contractors bid on the cost (part A) and environmental cost (part C) or on the cost (part A), time (part B), and environmental cost (part C) for public projects. An application of the proposed bidding methods is described using a bid for a highway reconstruction project. This case study reveals the potential impact of environmental cost criteria on the selection of a winning bid. Th...

Bidding analysis in joint energy and spinning reserve markets based on pay-as-bid pricing

Owing to the interaction between energy and spinning reserve markets, designing proper bid functions and offering optimal prices to these markets is economically a challenging task from generation companies (GenCos) point of view, especially in the pay-as-bid pricing mechanism. A previously presented only-energy bidding method is generalised in order to model and solve a multimarket bidding problem. Considering a joint probability distribution function for energy and spinning reserve prices, the bidding problem is formulated and solved as a classic optimisation problem. The results show that the contribution of GenCos in each market strongly depends on their production costs, GenCo's risk-aversion degree and the mean values of market prices.

Stock Price Correlation and the Method of Payment in Corporate Acquisitions

We provide novel evidence that the interim risk between a merger deal's announcement and completion is asymmetrically borne by the bidder. While the target can generally accept higher offers during the interim period -- presumably when its value increases -- the legal literature argues that bidders are more constrained in their ability to withdraw. We find that the likelihood of deal renegotiation is higher only when the target's value increases relative to the offer value during the interim period. Furthermore, we find significant effects on the bid premium, break-up fee, and method of payment, all consistent with this asymmetric risk hypothesis.

Research on Power Equipment Bidding Evaluation Combining the Entropy-Weight Method and the ELECTRE Method

Bidding evaluation is an important aspect in equipment procurement, and there are still some problems with the current bidding evaluation method being used. This paper presents a bidding evaluation method which combines the entropy-weight method and the ELECTRE method to create a new bidding evaluation model. Finally, the application of this bidding evaluation method in power equipment purchase is illustrated by using thermal power auxiliary equipment bidding procurement as an example.

Application of Value Engineering Based on the Comprehensive Weights in Construction Project Bidding

The bid assessment method is adopted in conducting qualitative indicators in the quantitative process, lack of a scientific and reasonable conversion method.Against these problems of the project evaluation methods, the value of the project will be introduced in the bid assessment mechanism, considering the project features and costs, integrating comprehensive weight method to quantify the weight of sub-functional evaluation of bidders value target.And it make the evaluation method is more scientific, reasonable and conducive to achieve optimal project value.

How to Franchise Highways

Electronic toll collection has trimmed transaction costs and moved highways out of the public goods box and into the public utilities box. Economists and policymakers should think of highways as a service to be made demand-responsive, self-financing, and privately owned. This paper proposes a novel method of franchise bidding called marginal return bidding. The scheme negotiates the knowledge and incentive problems of upfront bidding to provide a practical path for policy. The paper provides practical advice on other aspects of privatizing highways.

Study on recent execution of overall evaluation bidding method in small and medium-sized regional local governments

平成22年度現在，全地方自治体の約70％が総合評価方式による入札制度を試行的に導入したが，多くの地方自治体では本格的な導入に至ってはいない．その理由は，最も簡便な特別簡易型による型式でさえも，事務量の増大や入札期間の長期化などが負担とされているからである．その背景として，入札を担当する人員の問題や総合評価方式に相応しい工事規模や工種と実際の発注案件との乖離といった実務的な問題，さらに公共調達に関する自治体職員の意識の問題があるものと推定できる． 本研究では，北関東3県の入札担当職員の配置状況と事務量，そして，職員の総合評価に対する意識等，地方中小自治体が総合評価導入に対して抱える実務上の課題を抽出した． その結果，上記の課題に対して小規模であっても，比較的総合評価方式に対応している自治体のグループの存在を確認できた．一方，体制と工事発注量の不均衡から，今以上の総合評価方式の導入に限界を感じている規模の自治体グループの存在も窺えた．

Willingness to pay for implant therapy: a study of patient preference

This study determined the amount of willingness to pay (WTP) for implant treatment and identified the factors affecting WTP. Subjects attending a university dental hospital were recruited (n=59). They were presented with two hypothetical clinical scenarios: missing one anterior/posterior tooth. The clinical procedures, outcome and plausible complications of various replacement options (fixed and removable partial dentures, implants) and sequelae of no treatment were presented. They were then asked how much they were willing to pay for tooth replacement under the two situations using a bidding method, with a starting bid of Hong Kong (HK)$20,000 in HK$1000 increment/decrement if they were willing/unwilling to pay that amount (1 USD=7.8 HKD). The amount was recorded at which the subject chose the opposite option or it reached HK$0. Demographic data were also collected. WTP values were compared between anterior and posterior replacements, and among various demographic subgroups. Spearman's correlations and linear regression analysis were also conducted. Ninety-four percent and 84% of the subjects chose implant treatment to replace missing anterior and posterior teeth, respectively. The mean WTP amounts for anterior/posterior tooth replacement were HK$11,000/HK$10,000 (P>0.05). Higher WTP amounts were obtained from females, subjects without missing teeth or restorative need, and had attained higher level of education (P<0.05). Gender (P<0.05), level of education (P=0.042), and the presence of missing teeth (P=0.001) were independent predictors of WTP. The estimated WTP value for a single tooth replacement using dental implants was HK$10,000. Gender, level of education and presence of missing teeth were independent predictors that influenced WTP.

A neural network-based multi-agent classifier system with a Bayesian formalism for trust measurement

In this paper, a neural network (NN)-based multi-agent classifier system (MACS) utilising the trust-negotiation-communication (TNC) reasoning model is proposed. A novel trust measurement method, based on the combination of Bayesian belief functions, is incorporated into the TNC model. The Fuzzy Min-Max (FMM) NN is used as learning agents in the MACS, and useful modifications of FMM are proposed so that it can be adopted for trust measurement. Besides, an auctioning procedure, based on the sealed bid method, is applied for the negotiation phase of the TNC model. Two benchmark data sets are used to evaluate the effectiveness of the proposed MACS. The results obtained compare favourably with those from a number of machine learning methods. The applicability of the proposed MACS to two industrial sensor data fusion and classification tasks is also demonstrated, with the implications analysed and discussed.

Below-Average Bidding Method

The low-bid method, typically used for competitive bidding in the United States, may result in a contract with a firm that submits either accidentally or deliberately an unrealistically low-bid price. Such an occurrence hurts both the owner and the contractor by promoting disputes, increased costs, and schedule delays. To address this problem, other countries have adopted bidding methods based on the average of the bids submitted. One such approach is the below-average method where the winning bid is closest to but below the average of all bids. A competitive bidding model for the below-average-bid method is presented and its merits relative to the average-bid method and the low-bid method are explored. The below-average-bid process is investigated analytically and through Monte Carlo simulation. The results of bidding models for the below-average, the average, and the low-bid methods are presented in four easy-to-use nomograms which allow contractors to determine the optimal lump-sum bid price for each method without the need for complicated analysis. A comparison of the three methods provides information and insights to help owners with the difficult choice of a suitable bidding method for the project at hand.

On applications of an optimal price‐time bidding model in Hong Kong foundation projects

PurposeTraditionally, construction projects are awarded based on the lowest submitted tendering prices. However, this awarding method often causes problems on project delay, poor risk assessment and increased claims from variations. This paper aims to address these issues.Design/methodology/approachNowadays, clients require tenderers to submit both bidding prices and contract duration. This bidding method is called an optimal price‐time bidding model, the details of which are investigated in this paper, using 24 Hong Kong private and public foundation price‐time contracts.FindingsThe results show that private foundation projects produce better time and cost savings when compared with public foundation projects, meaning that the former are generally more effective in using the optimal price‐time bidding model than in public foundation projects. To further explore the effectiveness of the price‐time bidding model, case studies from a private and a public foundation project are investigated to show that private foundation projects using the price‐time bidding model are more effective than public foundation projects.Originality/valueThis paper encourages contractors to consider both time and cost factors in tendering and construction processes, noting that high liquidated and ascertained damages (LAD) charges need to be applied. This can provide a “balanced environment” for contractors in the construction industry.

Patience Auctions: The Impact of Time vs. Money Bidding on Elicited Discount Rates

We introduce, test, and compare two auction-based methods for eliciting discount rates. In these “patience auctions”, participants bid the smallest future sum they would prefer -or- the longest time they would wait for a reward, rather than receive a smaller, immediate payoff. The most patient bidder receives the delayed reward; all others receive the immediate payoff. These auctions allow us to compare discounting when participants’ attention is focused on the temporal versus monetary dimension of delayed rewards. We find that the estimated parameters in the three most commonly used discount functions (exponential, hyperbolic, and quasi-hyperbolic) differ across these two bidding methods (time-bids vs. money-bids). Specifically, our participants tend to show more impatience under time-bids. Furthermore, we find that people are more likely to exhibit exponential (as opposed to hyperbolic) discounting and exhibit less present bias under time-bids, compared to money-bids. To our knowledge, this paper is the first to directly compare time versus money preference elicitations, within the same subjects, using an incentive-compatible mechanism.

Double auction mechanisms for resource allocation in autonomous networks

Auction mechanisms are used for allocating a resource among multiple agents with the objective to maximize social welfare. What makes auctions attractive is that they are agnostic to utility functions of agents. Auctions involve a bidding method by agents-buyers, which is then mapped by a central controller to an allocation and a payment for each agent. In autonomic networks comprising self-interested nodes with different needs and utility functions, each entity possesses some resource and can engage in transactions with others to achieve its needs. In fact, efficient network operation relies on node synergy and multi-lateral resource trading. Nodes face the dilemma of devoting their limited resource to their own benefit versus acting altruistically and anticipating to be aided in the future. Wireless ad-hoc networks, peer-to-peer networks and disruption-tolerant networks are instances of autonomic networks where the challenges above arise and the traded resource is energy, bandwidth and storage space respectively. Clearly, the decentralized complex node interactions and the double node role as resource provider and consumer amidst resource constraints cannot be addressed by single-sided auctions and even more by mechanisms with a central controller. We introduce a double-sided auction market framework to address the challenges above. Each node announces one bid for buying and one for selling the resource. We prove that there exist bidding and charging strategies that maximize social welfare and we explicitly compute them. We generalize our result to a generic network objective. Nodes are induced to follow these strategies, otherwise they are isolated by the network. Furthermore, we propose a decentralized realization of the double-sided auction with lightweight network feedback. Finally, we introduce a pricing method which does not need a charging infrastructure. Simulation results verify the desirable properties of our approach.

Solving Truckload Procurement Auctions Over an Exponential Number of Bundles

Truckload carriers provide hundreds of billions of dollars worth of services to shippers in the United States alone each year. Internet auctions provide these shippers with a fast and easy way to negotiate potential contracts with a large number of carriers. Combinatorial auctions have the added benefit of allowing multiple lanes to be considered simultaneously in a single auction. This is important because it enables carriers to connect multiple lanes in continuous moves or tours, decreasing the empty mileage that must be driven, and therefore increasing overall efficiency. On the other hand, combinatorial auctions require bidding on an exponential number of bundles to achieve full economies of scope and scale, which is not tractable except for very small auctions. In most real-world auctions, bidding is instead typically limited to a very small subset of the potential bids. We present an implicit bidding approach to combinatorial auctions for truckload procurement that enables the complete set of all possible bids to be considered implicitly, without placing the corresponding burden of an exponential number of bids on the bidders or the auctioneer. We present the models needed to solve this problem. We then provide extensive computational results to demonstrate the tractability of our approach. Finally, we conclude with numerical analysis to assess the quality of the solutions that are generated and to demonstrate the benefits of our approach over existing bidding methods in practice.

3D tensor factorization approach to single-frame model-free blind-image deconvolution

By applying a bank of 2D Gabor filters to a blurred image, single-frame blind-image deconvolution (SF BID) is formulated as a 3D tensor factorization (TF) problem, with the key contribution that neither origin nor size of the spatially invariant blurring kernel is required to be known or estimated. Mixing matrix, the original image, and its spatial derivatives are identified from the factors in the Tucker3 model of the multichannel version of the blurred image. Previous approaches to 2D Gabor-filter-bank-based SF BID relied on 2D representation of the multichannel version of the blurred image and matrix factorization methods such as nonnegative matrix factorization (NMF) and independent component analysis (ICA). Unlike matrix factorization-based methods 3D TF preserves local structure in the image. Moreover, 3D TF based on the PARAFAC model is unique up to permutation and scales under very mild conditions. To achieve this, NMF and ICA respectively require enforcement of sparseness and statistical independence constraints on the original image and its spatial derivatives. These constraints are generally not satisfied. The 3D TF-based SF BID method is demonstrated on an experimental defocused red-green-blue image.