Designing Non-Convex Markets (DNCM)

多目标市场自早期以来一直处于经济科学的中心舞台。一般均衡理论和拍卖理论发展了一般模型，表明多目标市场机制处于竞争均衡或激励相容和有效时的假设。真实的市场往往不满足一般模型的假设。市场设计描述了最近的流在文献中，旨在设计特定类型的市场，并反映各自的分配问题的重要特征。这些特征通常可以被描述为分配和定价问题中的约束。例子包括用于模拟市场参与者复杂偏好的约束（例如补充和替代），限制市场可能结果的约束，或者预算约束。这些约束将分配问题转化为非凸优化问题。这种非凸市场的例子很普遍，包括频谱拍卖市场、机场时段市场、物流服务市场、污染权市场、港口容量市场或日前电力市场。虽然各自的分配问题被认为是棘手的现实问题的大小只有几年前，数学优化的进步是惊人的。先进的数学优化最近被用于全球高风险市场。然而，这些市场的理论还处于起步阶段。DNCM的目标是新型的市场模型、开源软件和实验结果。

Multi-object markets have been at the centre stage of the economic sciences since the early days. General equilibrium theory and auction theory have developed general models showing assumptions when multi-object market mechanisms are in a competitive equilibrium or when they are incentive-compatible and efficient. Real markets often do not satisfy the assumptions of generic models. Market design describes a recent stream in the literature aiming to design specific types of markets and reflect important features of the respective allocation problems. These features can typically be described as constraints in the allocation and pricing problems. Examples include constraints that are used to model complex preferences of market participants (e.g. complements and substitutes), constraints restricting the set of possible outcomes of a market, or also budget constraints. These constraints turn the allocation problem into a non-convex optimisation problem. Examples of such non-convex markets are widespread and include spectrum auction markets, markets for airport time-slots, logistics services, pollution rights, port capacities, or day-ahead electricity markets. While respective allocation problems were considered intractable only a few years ago for realistic problem sizes, the advances in mathematical optimisation are staggering. Advanced mathematical optimisation has recently been used in high-stakes markets worldwide. However, the theory of these markets is in its infancy. DNCM aims at new types of market models, open source software, and experimental results.