A Hybrid Simulated Annealing Algorithm for Container Loading Problem

This paper presents a hybrid simulated annealing algorithm for container loading problem with boxes of different sizes and single container for loading. A basic heuristic algorithm is introduced to generate feasible solution from a special structure called packing sequence. The hybrid algorithm uses basic heuristic to encode feasible packing solution as packing sequence, and searches in the encoding space to find an approximated optimal solution. The computational experiments on 700 weakly heterogeneous benchmark show that our algorithm outperforms all previous methods in average

A tight lower bound for job scheduling with cancellation

Abstract The Job Scheduling with Cancellation problem is a variation of classical scheduling problems in which jobs can be cancelled while waiting for execution. In this paper we prove a tight lower bound of 5 for the competitive ratio of any deterministic online algorithm for this problem, for the case where all jobs have the same processing time

Food-sorting jet arrays and target impact properties

This thesis uses numerical techniques and analysis to study the development and interactions between multiple in-line slender air jets. Consideration is given to two-and three-dimensional flow regimes, but the emphasis is on the latter. The applications (and mechanisms) involved in high-speed machine sorting of small food items, such as grains of rice, are explained. The underpinning mathematics required to develop the mathematical model are stated. In Chapter 2 an analytical solution for the two-dimensional steady jet is demonstrated and used to provide a far-downstream asymptote for validation of the numerical scheme, for steady and unsteady jets. A numerical scheme is demonstrated to be versatile and reasonably accurate. Small-distance analysis complements the numerical scheme and limitations are discussed. A comprehensive small-time analysis is undertaken, results from which support later work on three-dimensional jets. Interference between inline jets is considered in Chapter 3, which applies methods previously used to study two-dimensional in-parallel wakes. The conclusions from this chapter support and help explain results in later chapters. The numerical scheme is extended to three-dimensional steady and unsteady jets. Issuing nozzles of various cross-sections are considered with the aim of obtaining pressure data for comparison with physical data. Small-distance analysis is again investigated, enabling a weakness in the numerical solution to be highlighted. Potential flow theory is used to model interference aspects of multiple in-line unsteady three-dimensional jets. The emphasis is placed on jets from nozzles of either circular or rectangular cross-section but, in fact, the analysis applies for any cross-section. The impact properties of a typical jet when it hits one of the particles such as a grain of rice being sorted are discussed briefly, and final comments are made

IDBA-tran: a more robust de novo de Bruijn graph assembler for transcriptomes with uneven expression levels

published_or_final_versio

A Robust and Accurate Binning Algorithm for Metagenomic Se- quences with Arbitrary Species Abundance Ratio

ABSTRACT Motivation: With the rapid development of next-generation sequencing techniques, metagenomics, also known as environmental genomics, has emerged as an exciting research area which enables us to analyze the microbial environment in which we live. An important step for metagenomic data analysis is the identification and taxonomic characterization of DNA fragments (reads or contigs) resulting from sequencing a sample of mixed species. This step is usually referred to as "binning". Binning algorithms that are based on sequence similarity and sequence composition markers rely heavily on the reference genomes of known microorganisms or phylogenetic markers. Due to the limited availability of reference genomes and the bias and low availability of markers, these algorithms may not be applicable in all cases. Unsupervised binning algorithms which can handle fragments from unknown species provide an alternative approach. However, existing unsupervised binning algorithms only work on datasets either with balanced species abundance ratios or rather different abundance ratios, but not both. Results: In this paper, we present MetaCluster 3.0, an integrated binning method based on the unsupervised top-down separation and bottom-up merging strategy, which can bin metagenomic fragments of species with very balanced abundance ratios (say 1:1) to very different abundance ratios (e.g. 1:24) with consistently higher accuracy than existing methods. Availability: MetaCluster 3.0 can be downloaded a