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楼主: Roosevelt
发表于 2025-3-30 08:19:23 | 显示全部楼层
Molecular Basis of Hematopoiesisen graphs, and (7,3)-graphs. Moreover, split-perfect graphs form a new subclass of brittle graphs containing the superbrittle graphs for which a new characterization is obtained leading to linear time recognition.
发表于 2025-3-30 12:40:49 | 显示全部楼层
On the Expected Runtime and the Success Probability of Evolutionary Algorithms (Invited Presentatioues are necessary. Two such results are presented. First, it is shown that the most simple evolutionary algorithm optimizes each pseudo-boolean linear function in an expected time of O(. log .). Second, an example is shown where crossover decreases the expected runtime from superpolynomial to polynomial.
发表于 2025-3-30 18:13:48 | 显示全部楼层
Approximating Call-Scheduling Makespan in All-Optical Networks,s of rings. As a side result, we present a constant approximation algorithm for star networks. We assume for simplicity that all calls are released at time 0, however all our results hold also for arbitrary release dates at the expense of a factor 2 in the approximation ratio.
发表于 2025-3-30 22:37:34 | 显示全部楼层
发表于 2025-3-31 02:25:46 | 显示全部楼层
Split-Perfect Graphs: Characterizations and Algorithmic Use,en graphs, and (7,3)-graphs. Moreover, split-perfect graphs form a new subclass of brittle graphs containing the superbrittle graphs for which a new characterization is obtained leading to linear time recognition.
发表于 2025-3-31 06:32:04 | 显示全部楼层
发表于 2025-3-31 11:17:32 | 显示全部楼层
Angelo Azzi,Zdenek Drahota,Sergio Papa on series-parallel graphs which, for arbitrary δ,ε > 0, produces a solution which exceeds the bounds on the budget and the flow cost by factors 1+δ and 1+ε, respectively, while the amount of flow is at least that of an optimum solution. The running time of the algorithm is polynomial in the input size and 1/(δε).
发表于 2025-3-31 16:38:55 | 显示全部楼层
Optimizing Cost Flows by Modifying Arc Costs and Capacities, on series-parallel graphs which, for arbitrary δ,ε > 0, produces a solution which exceeds the bounds on the budget and the flow cost by factors 1+δ and 1+ε, respectively, while the amount of flow is at least that of an optimum solution. The running time of the algorithm is polynomial in the input size and 1/(δε).
发表于 2025-3-31 19:47:01 | 显示全部楼层
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