上海治理论坛第505期
标题：覆盖约束p-中值问题的Benders分化算法
演讲人：戴彧虹教授，中科院数学与系统钻研院
主持人：林贵华教授，新宝GG治理学院
功夫：2023年10月12日（周四），下午15:00
地址：新宝GG校本部东区治理学院420室
主办单元：新宝GG治理学院、新宝GG治理学院青老大师联谊会
演讲人简介：
国际驰名优化专家，中科院数学与系统钻研院钻研员、副院长。
中国运筹学会理事长，亚太运筹学会结合会主席。
主持国度杰青项目、沉点研发打算项目、创新钻研群体项目等。
曾获国度天然科学二等奖、中国青年科技奖、钟家庆数学奖、冯康科学推算奖、陈省身数学奖、首届萧树铁利用数学奖等。
演讲内容简介：
In this talk, we study the p-median problem with the addition of a coverage constraint which requires the total customer demand, covered at a distance greater than a prespecified coverage distance, to be smaller than or equal to a given threshold. We propose an efficient Benders decomposition (BD) approach for solving large-scale problems. We show that both Benders feasibility and optimality cuts can be separated in efficient combinatorial polynomial-time algorithms. Moreover, we enhance the BD approach by using tight initial cuts to initialize the relaxed master problem, implementing an effective two-stage algorithm to find high-quality solutions, and adding valid inequalities to strengthen the problem formulation. Computational results on benchmark instances show that the proposed BD approach outperforms the state-of-the-art general-purpose MIP solver's branch-and-cut and automatic BD algorithms by at least one order of magnitude.
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