Titlebook: Algorithms and Complexity; 11th International C Pinar Heggernes Conference proceedings 2019 Springer Nature Switzerland AG 2019 approximati

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https://doi.org/10.1007/978-3-658-06259-0 no .-time algorithm even in sparse graphs [Roditty and Williams, 2013]. To circumvent this lower bound we aim for algorithms with running time?. where?. is a parameter and . is a function as small as possible. We investigate which parameters allow for such running times. To this end, we systematica

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Der Klimawandel-Diskurs in China positive weights expressing the capacity of a given agent to contribute to a given project. The realization of a project produces some reward that has to be allocated to the agents. The reward of a realized project is fully allocated to its contributors, according to a simple proportional rule. Exi

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https://doi.org/10.1007/978-3-662-37024-7. in?. at least one edge is weak. In this work, we study the following generalizations of . with?. different strong edge colors. In . an induced?. may receive two strong labels as long as they are different. In . and . we may additionally restrict the set of permitted colors for each edge of?.. We s

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https://doi.org/10.1007/978-3-662-37022-3 . independent set) . with . (resp. .). Possibly contradicting intuition, these problems tend to be .-complete, even in graph classes where the classical problem can be solved efficiently. Yet, we exhibit some graph classes where the extension variant remains polynomial-time solvable. We also study

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https://doi.org/10.1007/978-3-662-38159-5n as a sequence of pickup and delivery stops, there exist polynomial time algorithms to find a schedule respecting these constraints, provided that there exists one. However, if no feasible schedule exists, the natural question is to find a schedule minimising constraint violations. We model a gener

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