Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.The authors wish to thank three anonymous referees for their comments and valuable suggestions to improve the paper. The first author acknowledges Ciˆencia 2007 of FCT (Foundation for Science and Technology) Portugal for the fellowship grant C2007-UMINHO-ALGORITMI-04. Financial support from FEDER COMPETE (Operational Programme Thematic Factors of Competitiveness) and FCT under project FCOMP-01-0124-FEDER-022674 is also acknowledged

Evolutionary Conservation of the Functional Modularity of Primate and Murine LINE-1 Elements

LINE-1 (L1) retroelements emerged in mammalian genomes over 80 million years ago with a few dominant subfamilies amplifying over discrete time periods that led to distinct human and mouse L1 lineages. We evaluated the functional conservation of L1 sequences by comparing retrotransposition rates of chimeric human-rodent L1 constructs to their parental L1 counterparts. Although amino acid conservation varies from ∼35% to 63% for the L1 ORF1p and ORF2p, most human and mouse L1 sequences can be functionally exchanged. Replacing either ORF1 or ORF2 to create chimeric human-mouse L1 elements did not adversely affect retrotransposition. The mouse ORF2p retains retrotransposition-competency to support both Alu and L1 mobilization when any of the domain sequences we evaluated were substituted with human counterparts. However, the substitution of portions of the mouse cys-domain into the human ORF2p reduces both L1 retrotransposition and Alu trans-mobilization by 200–1000 fold. The observed loss of ORF2p function is independent of the endonuclease or reverse transcriptase activities of ORF2p and RNA interaction required for reverse transcription. In addition, the loss of function is physically separate from the cysteine-rich motif sequence previously shown to be required for RNP formation. Our data suggest an additional role of the less characterized carboxy-terminus of the L1 ORF2 protein by demonstrating that this domain, in addition to mediating RNP interaction(s), provides an independent and required function for the retroelement amplification process. Our experiments show a functional modularity of most of the LINE sequences. However, divergent evolution of interactions within L1 has led to non-reciprocal incompatibilities between human and mouse ORF2 cys-domain sequences