Auctions involve trading of variety of different items. Auctions that allow agents to bid for combinations of items are called Combinatorial Auctions (CAs). The Ascending k-Bundle Auction(AkBA) is a combinatorial auction founded on a notion of bundle price equilibrium. The purpose of this research is to explore the strategy space and help agents evolve strategies for a Proxy version of A1BA(P-AkBA). We use a Genetic algorithm to search the space of strategies. Several experiments were performed for different categories of problems and the resultsshow that the approach yields good solutions. We compare the outcomes of the evolved solutions with the outcomes that result from truthful bidding, and compare prices against those generated in the sealed-bid version of k-bundle auction and the standard GVA payments. We also make several observations about the effect of genetic parameters on the performance of search.

Auction Theory, Second Edition improves upon his 2002 bestseller with a new chapter on package and position auctions as well as end-of-chapter questions and chapter notes. Complete proofs and new material about collusion complement Krishna's ability to reveal the basic facts of each theory in a style that is clear, concise, and easy to follow. With the addition of a solutions manual and other teaching aids, the 2e continues to serve as the doorway to relevant theory for most students doing empirical work on auctions. - Focuses on key auction types and serves as the doorway to relevant theory for those doing empirical work on auctions - New chapter on combinatorial auctions and new analyses of theory-informed applications - New chapter-ending exercises and problems of varying difficulties support and reinforce key points

This book provides a new bidding strategy for agents to adopt in continuous double auctions (CDAs) and proposes some generally used tools to enhance the performance of existing bidding strategies in CDAs. It is the first book to focus on CDAs where a limited amount of seller agents and buyer agents trade what they want. The superior performance of the new bidding strategy and the tools proposed by this book are illustrated through extensive experiments.

Traditional Combinatorial Reverse Auctions (CRAs) are already very hard problems to solve. By considering the multiplicity of units, attributes and objectives of items; the complexity of CRAs increases. Winner Determination (WD) is one of the main challenges of CRAs, and which has been shown to be NP-complete. Researchers limit the auction features because of the issue of time efficiency. We address several types of advanced CRAs by varying the auction parameters. We tackle the combinatorial procurement problem instances using Genetic Algorithms (GAs). In the first instance, we consider multiple units, single attribute and objective. To this end, we propose a modified crossover operator and two routines. Our proposed WD method is capable of finding the winner(s) with a minimum procurement cost and an efficient processing time. To validate our GA-based method, we conduct several experiments and the results clearly demonstrate the good-time performance and the high quality of the solution. In the second problem, we tackle CRAs with two attributes, single objective and multiple units and rounds. We make this problem more interesting by considering all-units discounts and the availability of sellers' stock. To evaluate our proposed method, we conduct several experiments. In the next problem instance, we include additional constraints, such as seller stocks and discount rate. In this part, we perform a comparative study of several exact and evolutionary techniques addressing different types of CRAs. In particular, we show that our technique based on GAs outperforms some other methods in terms of time efficiency. Lastly, we address CRAs with multiple units, attributes, objectives and rounds. We define optimization approach based on GAs that we integrate with our own variants of diversity and elitism strategies to greatly improve the solution quality. We conduct a case study as well as simulated testing to illustrate the importance of the diversity and elitism schemes. We also validate the proposed WD method through simulated experiments by generating large instances of our CRA problem. Moreover, we apply our WD approach to a real-life electricity application based on renewable energy sources. The option for public utilities to organize electricity CRAs to purchase the needed electricity from other power suppliers is a new concept. For this purpose, we develop a constrained CRA to procure power from diverse sources including residents and plants. In our CRA, subject to various trading constraints, an item denotes a time slot that has two conflicting attributes, energy volume and price. To secure electricity, we design our auction with two bidding rounds: the first one is for variable energy suppliers and the second one for other sources, like controllable load and other renewable technologies. Our CRA leads to a complex WD problem. We view this problem as a resource allocation optimization that we solve with multi-objective GAs in order to find the best trade-off solution that lowers the price and increases the energy. This solution consists of multiple winning suppliers, their prices, power volumes and schedules. We validate our WD approach based on simulated data by generating large instances of our multi-objective constrained auction problem. The goal of the experiments is to assess the time-efficiency of our WD method and its significant superiority to well-known heuristic and exact WD techniques. Furthermore, we implement two exact algorithms to solve our complex procurement problem in order to evaluate the accuracy of our WD method i.e. how near to optimal is the solution.

This book provides a comprehensive introduction to modern auction theory and its important new applications. It is written by a leading economic theorist whose suggestions guided the creation of the new spectrum auction designs. Aimed at graduate students and professionals in economics, the book gives the most up-to-date treatments of both traditional theories of 'optimal auctions' and newer theories of multi-unit auctions and package auctions, and shows by example how these theories are used. The analysis explores the limitations of prominent older designs, such as the Vickrey auction design, and evaluates the practical responses to those limitations. It explores the tension between the traditional theory of auctions with a fixed set of bidders, in which the seller seeks to squeeze as much revenue as possible from the fixed set, and the theory of auctions with endogenous entry, in which bidder profits must be respected to encourage participation.

In recent years, auctions have become an important field and many markets have designed new and sophisticated auction models to assign different types of items. The prime goal of this book is to set an organized classification of the main auction mechanisms in a way that readers can understand the importance of auction design and the advantages and drawbacks of each model. Given the relevance of the subject, there is a great volume of research about this topic. Nevertheless, most of these contributions use complex mathematical language difficult to understand for the average reader. In this book, the authors summarize the main ideas of the auction theory and explain them with simple language and plenty of examples. This book is a good starting point for any researcher interested in embracing the auction design as it also includes numerous real-world examples to engage the reader in the topic. “This book fills an important gap by making the main ideas and findings of auction research accessible.” Professor Paul Milgrom, Department of Economics, Stanford University.