Mechanism design for decentralized online machine scheduling

Traditional optimization models assume a central decision maker who optimizes a global system performance measure. However, problem data is often distributed among several agents, and agents take autonomous decisions. This gives incentives for strategic behavior of agents, possibly leading to sub-optimal system performance. Furthermore, in dynamic environments, machines are locally dispersed and administratively independent. Examples are found both in business and engineering applications. We investigate such issues for a parallel machine scheduling model where jobs arrive online over time. Instead of centrally assigning jobs to machines, each machine implements a local sequencing rule and jobs decide for machines themselves. In this context, we introduce the concept of a myopic best response equilibrium, a concept weaker than the classical dominant strategy equilibrium, but appropriate for online problems. Our main result is a polynomial time, online mechanism that |assuming rational behavior of jobs| results in an equilibrium schedule that is 3.281-competitive with respect to the maximal social welfare. This is only lightly worse than state-of-the-art algorithms with central coordination

Web Service Retrieval by Structured Models

Much of the information available on theWorldWideWeb cannot effectively be found by the help of search engines because the information is dynamically generated on a user’s request.This applies to online decision support services as well as Deep Web information. We present in this paper a retrieval system that uses a variant of structured modeling to describe such information services, and similarity of models for retrieval. The computational complexity of the similarity problem is discussed, and graph algorithms for retrieval on repositories of service descriptions are introduced. We show how bounds for combinatorial optimization problems can provide filter algorithms in a retrieval context. We report about an evaluation of the retrieval system in a classroom experiment and give computational results on a benchmark library.Economics ;

Design and Evaluation of an Economic Experiment via the Internet

The paper investigates whether Internet experiments are an appropriate alternative to traditional laboratory experiments. For an economic experiment of individual decision making results obtained over the Internet are compared to results obtained in the laboratory using exactly the same software. Of particular interest are differences in individual behavior. Our main findings are: 1) Running our own experiment on the Internet and in the laboratory generated similar data when economic decision behavior is concerned. (2) Variance in economic decision behavior is generally higher on the Internet experiment. (3) Decision times are shorter on the Internet. (4) Internet software provides a helpful platform for implementing economic experiments. The paper also reports on design challenges and how we have solved them.economics of technology ;

Combinatorial Scoring Auctions

This paper is concerned with a combinatorial, multi-attribute procurement mechanism called combinatorial scoring auction. In the setting that we analyze, private information of the suppliers is multi-dimensional. The buyer wants to procure several items at once. Subsets of these items are characterized by a price as well as by a number of non-monetary attributes called quality (e.g. completion time). The suppliers submit offers specifying prices and quality levels for these subsets. These offers are evaluated according to a quasilinear scoring rule. Based on the resulting scores suppliers win contracts for the delivery of certain items. Such a contract only specifies the set of items a supplier has to deliver and a score that he has to meet. The decision about the specific price-quality combination yielding this contracted score is at the discretion of the supplier who aims at optimizing his own profit. We analyze the equilibria in such auctions and show the link between combinatorial scoring auctions and combinatorial price-only auctions. We demonstrate how this link can be used to employ preexisting knowledge about the equilibrium behavior in regular price-only auctions in the strategic analysis of combinatorial scoring auctions. Our results are the multi-item extension to the results of Asker and Cantillon (2007).mathematical economics;

Games and Mechanism Design in Machine Scheduling – An Introduction

In this paper, we survey different models, techniques, and some recent results to tackle machine scheduling problems within a distributed setting. In traditional optimization, a central authority is asked to solve a (computationally hard) optimization problem. In contrast, in distributed settings there are several agents, possibly equipped with private information that is not publicly known, and these agents need to interact in order to derive a solution to the problem. Usually the agents have their individual preferences, which induces them to behave strategically in order to manipulate the resulting solution. Nevertheless, one is often interested in the global performance of such systems. The analysis of such distributed settings requires techniques from classical Optimization, Game Theory, and Economic Theory. The paper therefore briefly introduces the most important of the underlying concepts, and gives a selection of typical research questions and recent results, focussing on applications to machine scheduling problems. This includes the study of the so-called price of anarchy for settings where the agents do not possess private information, as well as the design and analysis of (truthful) mechanisms in settings where the agents do possess private information.computer science applications;

Decentralization and Mechanism Design for Online Machine Scheduling

We study the online version of the classical parallel machine scheduling problem to minimize the total weighted completion time from a new perspective: We assume a strategic setting, where the data of each job j, namely its release date r(j) , its processing time p(j) and its weight w(j) is only known to the job itself, but not to the system. Furthermore, we assume a decentralized setting, where jobs choose the machine on which they want to be processed themselves. We study this setting from the perspective of algorithmic mechanism design and present a polynomial time decentralized online scheduling mechanism that induces rational jobs to select their machine in such a way that the resulting schedule is 3.281-competitive. The mechanism deploys an online payment scheme that induces rational jobs to truthfully report about their private data: with respect to release dates and processing times, truthfully reporting is a dominant strategy equilibrium, whereas truthfully reporting the weights is a myopic best response equilibrium. We also show that the local scheduling policy used in the mechanism cannot be extended to a mechanism where truthful reports with respect to weights constitute a dominant strategy equilibrium.operations research and management science;

Characterization of revenue equivalence

The property of an allocation rule to be implementable in dominant strategies by a unique payment scheme is called \emph{revenue equivalence}. In this paper we give a characterization of revenue equivalence based on a graph theoretic interpretation of the incentive compatibility constraints. The characterization holds for any (possibly infinite) outcome space and many of the known results are immediate consequences. Moreover, revenue equivalence can be identified in cases where existing theorems are silent

Dominant Strategy Mechanisms with Multidimensional Types

This paper provides a characterization of dominant strategy mechanisms with quasi-linear utilities and multi-dimensional types for a variety of preference domains. These characterizations are in terms of a monotonicity property on the underlying allocation rule.operations research and management science;

Characterization of Revenue Equivalence

The property of an allocation rule to be implementable in dominant strategies by a unique payment scheme is called revenue equivalence. In this paper we give a characterization of revenue equivalence based on a graph theoretic interpretation of the incentive compatibility constraints. The characterization holds for any (possibly infinite) outcome space and many of the known results are immediate consequences. Moreover, revenue equivalence can be identified in cases where existing theorems are silent.computer science applications;

Auctions - the Big Winner Among Trading Mechanisms for the Internet Economy

Auctions are probably the most important mechanism for dynamic pricing in electronic commerce. Although they constitute a very old mechanism as well, the new popularity has raisen a lot of questions on the appropriate design of an auction mechanism for a particular situation. This chapter describes reasons for auction popularity by setting them into the context of trends in electronic commerce. We then illustrate the main issues in auction design. Our analysis starts with simple single-item auctions, as we can see them in many B2C markets. We then look at the more complex auction designs, which are necessary for B2B markets. For the latter design has to take into account that buyers want to purchase collections of items and services, and that the valuation for winning collections is not simply equal to the sum of valuations of single items. We show how multi-item auction mechanisms can benefit from a synthesis of microeconomic and mathematical optimization models.economics of technology ;