基于价值与公平标准的资源匹配：农业水权交易中的应用
Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading
AI总结：
针对干旱下农业用水分配问题，提出基于价值函数和公平约束的匹配算法，最大化社会福利或最小满意度，并通过实验验证有效性。
摘要：
干旱时期农业用水的优化分配是一个重要的全球性问题。在解决这一问题时，必须考虑农民福利、经济和环境等多个方面。在此背景下，我们的工作聚焦于几个资源匹配问题，这些问题涉及拥有多种作物组合的智能体、地理约束和公平性。首先，我们解决了一个匹配问题，其目标是在双边市场中最大化福利函数，其中买方的需求和卖方的供应由价值函数表示，这些函数为特定体积的水分配价格（或成本）。对于价值函数满足特定单调性的情况，我们提出了一种高效算法，该算法最大化社会福利函数。当存在最小用水需求约束时，我们提出了一种随机算法，确保约束在期望上得到满足。对于具有公平约束的单卖方-多买方设置，我们设计了一种高效算法，该算法最大化任何买方的最小满意度。我们还提供了计算复杂性结果，这些结果突显了我们结果可推广性的限制。我们使用真实世界和合成数据集对我们的算法进行了实验评估，涉及干旱严重程度、价值函数和智能体的资历。
英文摘要：
Optimal allocation of agricultural water in the event of droughts is an important global problem. In addressing this problem, many aspects, including the welfare of farmers, the economy, and the environment, must be considered. Under this backdrop, our work focuses on several resource-matching problems accounting for agents with multi-crop portfolios, geographic constraints, and fairness. First, we address a matching problem where the goal is to maximize a welfare function in two-sided markets where buyers' requirements and sellers' supplies are represented by value functions that assign prices (or costs) to specified volumes of water. For the setting where the value functions satisfy certain monotonicity properties, we present an efficient algorithm that maximizes a social welfare function. When there are minimum water requirement constraints, we present a randomized algorithm which ensures that the constraints are satisfied in expectation. For a single seller--multiple buyers setting with fairness constraints, we design an efficient algorithm that maximizes the minimum level of satisfaction of any buyer. We also present computational complexity results that highlight the limits on the generalizability of our results. We evaluate the algorithms developed in our work with experiments on both real-world and synthetic data sets with respect to drought severity, value functions, and seniority of agents.
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