Two fundamental algorithm-design paradigms are Tree Search and Dynamic Programming. The techniques used therein have been shown to complement one another when solving the complete set partitioning problem, also known as the coalition structure generation problem [5]. Inspired by this observation, we develop in this paper an algorithm to solve the coalition structure generation problem on graphs, where the goal is to identifying an optimal partition of a graph into connected subgraphs. More specifically, we develop a new depth-first search algorithm, and combine it with an existing dynamic programming algorithm due to [9]. The resulting hybrid algorithm is empirically shown to significantly outperform both its constituent parts when the subset-evaluation function happens to have certain intuitive properties.
The pseudo code of @math is shown in Algorithm . For a proof of the correctness of this algorithm, see @cite_1 .
@cite_1
1598605111 2964184416 2138092283 91979434
The EQUAL SUM SUBSETS problem, where we are given a set of positive integers and we ask for two nonempty disjoint subsets such that their elements add up to the same total, is known to be NP-hard. In this paper we give (pseudo-)polynomial algorithms and or (strong) NP-hardness proofs for several natural variations of EQUAL SUM SUBSETS. Among others we present (i) a framework for obtaining NP-hardness proofs and pseudopolynomial time algorithms for EQUAL SUM SUBSETS variations, which we apply to variants of the problem with additional selection restrictions, (ii) a proof of NP-hardness and a pseudo-polynomial time algorithm for the case where we ask for two subsets such that the ratio of their sums is some fixed rational r > 0, (iii) a pseudo-polynomial time algorithm for finding k subsets of equal sum, with k = O(1), and a proof of strong NP-hardness for the same problem with k = Ω(n), (iv) algorithms and hardness results for finding k equal sum subsets under the additional requirement that the subsets should be of equal cardinality. Our results are a step towards determining the dividing lines between polynomial time solvability, pseudo-polynomial time solvability, and strong NP-completeness of subset-sum related problems. We prove that any submodular function f: 0, 1 n → 0, 1,..., k can be represented as a pseudo-Boolean 2k-DNF formula. Pseudo-Boolean DNFs are a natural generalization of DNF representation for functions with integer range. Each term in such a formula has an associated integral constant. We show that an analog of Hastad's switching lemma holds for pseudo-Boolean k-DNFs if all constants associated with the terms of the formula are bounded. This allows us to generalize Mansour's PAC-learning algorithm for k-DNFs to pseudo-Boolean k-DNFs, and hence gives a PAC-learning algorithm with membership queries under the uniform distribution for submodular functions of the form f: 0, 1 n → 0, 1,..., k . Our algorithm runs in time polynomial in n, For an @math -variate degree– @math real polynomial @math , we prove that @math is determined up to an additive @math as long as @math is a @math -wise independent distribution over @math for @math . This gives a broad class of explicit pseudorandom generators against degree- @math boolean threshold functions, and answers an open question of (FOCS 2009). Recently Bogdanov and Viola (FOCS 2007) and Lovett (ECCC-07) constructed pseudorandom generators that fool degree k polynomials over F2 for an arbitrary constant k. We show that such generators can also be used to fool branching programs of width 2 and polynomial length that read k bits of inputs at a time. This model generalizes polynomials of degree k over F2 and includes some other interesting classes of functions, for instance k-DNF. The constructions of Bogdanov and Viola and Lovett consist of adding a constant number of independent copies of a generator that fools linear functions (an -biased set). It is natural to ask, in light of our first result, whether such generators can fool branching programs of width larger than 2. Our second result is a lower bound showing