Optimal and Efficient Auctions for the Gradual Procurement of Strategic Service Provider Agents

We consider an outsourcing problem where a software agent procures multiple services  from providers with uncertain reliabilities to complete a computational task before a  strict deadline. The service consumer’s goal is to design an outsourcing strategy (defining  which services to procure and when) so as to maximize a specific objective function. This  objective function can be different based on the consumer’s nature; a socially-focused consumer  often aims to maximize social welfare, while a self-interested consumer often aims  to maximize its own utility. However, in both cases, the objective function depends on  the providers’ execution costs, which are privately held by the self-interested providers and  hence may be misreported to influence the consumer’s decisions. For such settings, we  develop a unified approach to design truthful procurement auctions that can be used by  both socially-focused and, separately, self-interested consumers. This approach benefits  from our proposed weighted threshold payment scheme which pays the provably minimum  amount to make an auction with a monotone outsourcing strategy incentive compatible.  This payment scheme can handle contingent outsourcing plans, where additional procurement  happens gradually over time and only if the success probability of the already hired  providers drops below a time-dependent threshold. Using a weighted threshold payment  scheme, we design two procurement auctions that maximize, as well as two low-complexity  heuristic-based auctions that approximately maximize, the consumer’s expected utility and  expected social welfare, respectively. We demonstrate the effectiveness and strength of our  proposed auctions through both game-theoretical and empirical analysis.