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Abstract: The voting rules proposed by Dodgson and Young are both designed to find an alternative closest to being a Condorcet winner, according to two different notions of proximity; the score of a given alternative is known to be hard to compute under either rule. In this paper, we put forward two algorithms for approximating the Dodgson score: a combinatorial, greedy algorithm and an LP-based algorithm, both of which yield an approximation ratio of , where m is the number of alternatives and is the st harmonic number. We also prove that our algorithms are optimal within a factor of 2, unless problems in have quasi-polynomial-time algorithms. Despite the intuitive appeal of the greedy algorithm, we argue that the LP-based algorithm has an advantage from a social choice point of view. Further, we demonstrate that computing any reasonable approximation of the ranking produced by Dodgsonʼs rule is -hard. This result provides a complexity-theoretic explanation of sharp discrepancies that have been observed in the social choice theory literature when comparing Dodgson elections with simpler voting rules. Finally, we show that the problem of calculating the Young score is -hard to approximate by any factor. This leads to an inapproximability result for the Young ranking. [Copyright &y& Elsevier]

Abstract: In this paper we introduce and study cooperative variants of the Traveling Salesperson Problem. In these problems a salesperson has to make deliveries to customers who are willing to help in the process. Customer cooperativeness may be manifested in several modes: they may assist by approaching the salesperson, by reselling the goods they purchased to other customers, or by doing both. Several objectives are of interest: minimizing the total distance traveled by all of the participants, minimizing the maximal distance traveled by a participant and minimizing the total time until all of the deliveries are made. All of the combinations of cooperation modes and objective functions are considered, both in weighted undirected graphs and in Euclidean space. We show that most of the problems have a constant approximation algorithm, many of the others admit a PTAS, and a few are solvable in polynomial time. On the intractability side we provide NP-hardness proofs and inapproximability factors, some of which are tight. [Copyright &y& Elsevier]

Abstract: Given an -vertex directed graph and a set of requests, we consider assigning a set of edges to each vertex in so that for every request in the union of the edge sets assigned to and contains a path from to . The Minimum Certificate Dispersal Problem (MCD) is defined as one to find an assignment that minimizes the sum of the cardinalities of the edge sets assigned to each vertex. This problem has been shown to be NP-hard in general, though it is polynomially solvable for some restricted classes of graphs and restricted request structures, such as bidirectional trees with requests of all pairs of vertices. In this paper, we give an advanced investigation about the difficulty of MCD by focusing on the relationship between its (in)approximability and request structures. We first show that MCD with general has lower and upper bounds on approximation ratio under the assumption . We then assume forms a clique structure, called Subset-Full, which is a natural setting in the context of the application. Interestingly, under this natural setting, MCD becomes 2-approximable, though it has still no polynomial time approximation algorithm whose factor is better than 677/676 unless . Finally, we show that this approximation ratio can be improved to 3/2 for the undirected variant of MCD with Subset-Full. [Copyright &y& Elsevier]

Abstract: This paper deals with the maximum triangle packing problem. For this problem, Hassin and Rubinstein gave a randomized polynomial-time approximation algorithm that achieves an expected ratio of for any constant . By modifying their algorithm, we obtain a new randomized polynomial-time approximation algorithm for the problem which achieves an expected ratio of for any constant . [Copyright &y& Elsevier]