讲座人介绍：

陈礴，英国华威大学(Warwick)商学院运筹与管理学系教授,英国社会科学院院士。获荷兰Erasmus大学(鹿特丹)运筹学博士和英国华威大学(Warwick)高级博士(DSc)，为英国运筹学会会士，自2006年起任诺贝尔经济学奖推荐提名专家。
陈礴教授主要研究组合最优化、排序与调度、博弈论及机制设计。相关研究得到荷兰、英国和中国等多项重大研究资助，经费共计470余万英镑。陈礴教授作为三位创始人之一创建了具有国际顶级影响力的离散数学及其应用研究中心(DIMAP)，获得全英科技与创新奖。
陈礴教授在本专业国际顶级或一流学术期刊上发表论文六十余篇，是JCO、IJSS、JoS、Omega等多个国际著名学术期刊编委以及著名出版社John Wiley & Sons学术出版顾问。
       陈旭瑾，2004年获香港大学博士学位，现为中国科学院数学与系统科学研究院研究员。从事运筹学及相关领域的研究工作，主要研究兴趣和方向是组合优化的理论和应用，包括算法博弈论、网络优化、多面体组合等。2010年获“中国运筹学会青年科技奖”一等奖，2013年获首届国家优秀青年基金。

王长军，讲师，现在北京工业大学应用数理学院工作。2015年博士毕业于中科院数学与系统科学研究院运筹学专业。研究方向为组合优化、算法博弈论、机制设计等。目前已在相关重要国际期刊及会议发表论文十多篇，包括 Information and Computation, Journal of AI Research, Journal of Mathematical Economics，EC, WINE, IJCAI等。目前主持一项国家自然科学基金面上项目和中国科协青年人才托举工程项目。

“Business is cooperation when it comes to creating a pie and competition when it
comes to dividing it up.” We study an organic combination of cooperation and
competition in resource sharing settings, which we call coopetitive games. These
settings arise when stakeholders of the games realize the benefits of collaboration and agree upon a sharing mechanism, while at the same time they need to decide the extent to which they invest their resources. The cooperation aspect is modelled as a cooperative game, while the utility maximization aspect is modelled as a non-cooperative game. We demonstrate the coopetition framework with the linear production games and show that, under some settings,the Shapley value allocation scheme dominates other fair allocation schemes in terms of the quality of their resulting social welfare at equilibrium. Our research is a first attempt to extend the focal dimension of incentive schemes from whether players would stay in the grand coalition in cooperative game theory to what extent they would cooperate in the grand coalition in a coopetitive game. 
    We study single-candidate voting embedded in a metric space, where both voters and candidates are points in the space, and the distances between voters and candidates specify the voters’ preferences over candidates. In the voting, each voter is asked to submit her favorite candidate. Given the collection of favorite candidates, a mechanism for eliminating the least popular candidate finds a committee containing all candidates but the one to be eliminated. 
    Each committee is associated with a social value that is the sum of the costs (utilities) it imposes (provides) to the voters. We design mechanisms for finding a committee to optimize the social value. We measure the quality of a mechanism by its distortion, defined as the worst-case ratio between the social value of the committee found by the mechanism and the optimal one. We establish new upper and lower bounds on the distortion of mechanisms in this single-candidate voting, for both general metrics and well-motivated special cases. (Joint work with Minming Li and Chenhao Wang.)
     Possessing a long history and diverse applications, models of atomic dynamic routings (ADR) are recently drawing increasing attention. ADRs are more realistic and at the same time more challenging than their nonatomic counterparts. The difficulty stems from the fact that interactions among atomic agents could be formidably complicated due to their dynamic nature and hard-to-predict chain-effects. 
    We investigate the problem of bounding agent residence time for a broad class of ADRs by exploring novel token techniques that help to circumvent direct analyses of complicated chain-effects. Even though agents may enter the network over time for an infinite number of periods, we show that under a mild condition, the residence time of every agent is upper-bounded by a network constant plus the total number of agents inside the network at entry time of the agent.