Incentive-compatible cost allocations for inventory games with private information

IF 0.8 4区管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE

Operations Research Letters Pub Date : 2024-01-27 DOI:10.1016/j.orl.2024.107073

Yinlian Zeng , Siyi Wang , Xiaoqiang Cai , Lianmin Zhang

引用次数: 0

Abstract

In this paper we design cost allocation rules for inventory games with private information. First, we design incentive-compatible cost allocation rules for inventory games with private information via Vickrey-Clarke-Groves (VCG) rules. Then, we propose incentive-compatible and approximate budget-balanced cost allocations via polynomial approximations such as the Chebyshev approximation and the Taylor approximation. In addition, we propose an incentive-compatible cost allocation with individual rationality. Finally, we conduct numerical experiments to compare the performance of the proposed cost allocations.

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具有私人信息的存货博弈的激励相容成本分配

本文设计了具有私人信息的存货博弈成本分配规则。首先，我们通过 Vickrey-Clarke-Groves (VCG) 规则为具有私人信息的存货博弈设计了激励相容的成本分配规则。然后，我们通过切比雪夫近似法和泰勒近似法等多项式近似法，提出了与激励相容的近似预算平衡成本分配法。此外，我们还提出了具有个体理性的激励兼容成本分配方案。最后，我们通过数值实验来比较所提成本分配方案的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Operations Research Letters 管理科学-运筹学与管理科学

CiteScore

2.10

自引率

9.10%

发文量

111

审稿时长

83 days

期刊介绍： Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.