A Study of Memetic Search with Multi-parent Combination for UBQP

We present a multi-parent hybrid genetic–tabu algorithm (denoted by GTA) for the Unconstrained Binary Quadratic Programming (UBQP) problem, by incorporating tabu search into the framework of genetic algorithm. In this paper, we propose a new multi-parent combination operator for generating offspring solutions. A pool updating strategy based on a quality-and-distance criterion is used to manage the population. Experimental comparisons with leading methods for the UBQP problem on 25 large public instances demonstrate the efficacy of our proposed algorithm in terms of both solution quality and computational efficiency

Recent Advances in Graph Partitioning

We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions

The core and nucleolus of games: A note on a paper by Göthe-Lundgren et al.

In the paper “On the nucleolus of the basic vehicle routing game”, Mathematical Programming 72, 83–100 (1996), Göthe-Lundgren et al. develop a constraint generation method to compute the pre-nucleolus of a game. Their method assumes that constraints that are redundant in the representation of the core can be ignored in the computation of the pre-nucleolus. We provide an example that shows that for a game with an empty core such an assumption is, in general, not valid. Further, we show that a statement made by Göthe-Lundgren et al. about an intuitive interpretation of the pre-nucleolus is misleading

Hybridizing GRASP, PROBE and Path Relinking

A number of hybrid metaheuristics are presented based on GRASP, path relinking and PROBE. Instantiations of the resulting metaheuristics are described for the graph bisection problem. Experimental results are given which indicate that a metaheuristic resulting from the hybridization of all three of the above techniques can lead to computationally efficient and robust solution methods

A GRASP-based approach for the Pure Parsimony Haplotype Inference problem

The availability and study of haplotype data is of considerable interest to a wide range of areas including general health care, personalized medicine, and pharmacogenetics. The inner workings of contemporary sequencing techniques however imply that genotype data is generated from a chromosome rather than haplotype data. The reconstruction of the latter from this kind of data lies at the heart of the well studied Pure Parsimony Haplotype Inference problem (PPHI). In this paper, we present a proof of concept that a GRASP-based approach for solving PPHI has the potential of yielding an attractive tool that complements existing approaches. The usage of this strategy for solving PPHI is novel. To assess its suitability, we have implemented it in basic form in the novel and freely available HAPLOGRASP approach which we assessed in terms of simulated and real data. Our findings are highly encouraging.Radosław Suchecki, Pierre Chardaire, Katharina T. Hube

A PROBE-Based Heuristic for Graph Partitioning

A new heuristic algorithm, PROBE_BA, which is based on the recently introduced metaheuristic paradigm population- reinforced optimization-based exploration (PROBE), is proposed for solving the Graph Partitioning Problem. The "exploration" part of PROBE_BA is implemented by using the differential-greedy algorithm of Battiti and Bertossi and a modification of the Kernighan-Lin algorithm at the heart of Bui and Moon's genetic algorithm BFS _GBA. Experiments are used to investigate properties of PROBE and show that PROBE_BA compares favorably with other solution methods based on genetic algorithms, randomized reactive tabu search, or more specialized multilevel partitioning techniques. In addition, PROBE_BA finds new best cut values for 10 of the 34 instances in Walshaw's graph partitioning archive