Distributed Domain Propagation

This is the final version. Available on open access from the publisher via the DOI in this record16th International Symposium on Experimental Algorithms (SEA 2017), 21-23 June 2017, London, UKPortfolio parallelization is an approach that runs several solver instances in parallel and terminates when one of them succeeds in solving the problem. Despite it’s simplicity portfolio parallelization has been shown to perform well for modern mixed-integer programming (MIP) and boolean satisfiability problem (SAT) solvers. Domain propagation has also been shown to be a simple technique in modern MIP and SAT solvers that effectively finds additional domain reductions after a variables domain has been reduced. This paper investigates the impact of distributed domain propagation in modern MIP solvers that employ portfolio parallelization. Computational experiments were conducted for two implementations of this parallelization approach. While both share global variable bounds and solutions they communicate differently. In one implementation the communication is performed only at designated points in the solving process and in the other it is performed completely asynchronously. Computational experiments show a positive performance impact of communicating global variable bounds and provide valuable insights in communication strategies for parallel solvers.German Federal Ministry of Education and Researc

SCIP-Jack—a solver for STP and variants with parallelization extensions

This is the author accepted manuscript. The final version is available from Springer Verlag via the DOI in this record The Steiner tree problem in graphs is a classical problem that commonly arises in practical applications as one of many variants. While often a strong relationship between different Steiner tree problem variants can be observed, solution approaches employed so far have been prevalently problemspecific. In contrast, this paper introduces a general-purpose solver that can be used to solve both the classical Steiner tree problem and many of its variants without modification. This versatility is achieved by transforming various problem variants into a general form and solving them by using a state-ofthe-art MIP-framework. The result is a high-performance solver that can be employed in massively parallel environments and is capable of solving previously unsolved instances.German Federal Ministry of Education and Researc

Sequencing and Analysis of Approximately 40 000 Soybean cDNA Clones from a Full-Length-Enriched cDNA Library

A large collection of full-length cDNAs is essential for the correct annotation of genomic sequences and for the functional analysis of genes and their products. We obtained a total of 39 936 soybean cDNA clones (GMFL01 and GMFL02 clone sets) in a full-length-enriched cDNA library which was constructed from soybean plants that were grown under various developmental and environmental conditions. Sequencing from 5′ and 3′ ends of the clones generated 68 661 expressed sequence tags (ESTs). The EST sequences were clustered into 22 674 scaffolds involving 2580 full-length sequences. In addition, we sequenced 4712 full-length cDNAs. After removing overlaps, we obtained 6570 new full-length sequences of soybean cDNAs so far. Our data indicated that 87.7% of the soybean cDNA clones contain complete coding sequences in addition to 5′- and 3′-untranslated regions. All of the obtained data confirmed that our collection of soybean full-length cDNAs covers a wide variety of genes. Comparative analysis between the derived sequences from soybean and Arabidopsis, rice or other legumes data revealed that some specific genes were involved in our collection and a large part of them could be annotated to unknown functions. A large set of soybean full-length cDNA clones reported in this study will serve as a useful resource for gene discovery from soybean and will also aid a precise annotation of the soybean genome

A Grid-Aware Branch, Cut and Price Implementation

This paper presents a grid-enabled system for solving large-scale optimization problems. The system has been developed using Globus and MPICH-G2 grid technologies, and consists of two BCP solvers and of an interface portal. After a brief introduction to Branch, Cut and Price optimization algorithms, the system architecture, the solvers and the portal user interface are described. Finally, some of the tests performed and the obtained results are illustrated