Value-based Resource Matching with Fairness Criteria: Application to Agricultural Water Trading
CoRR(2024)
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.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要