Flight-scheduling optimization and automation for AnadoluJet

AnadoluJet, a leading Turkish domestic airline carrier provides high-service, low-price flights to 28 locations within Turkey. Each winter and summer, AnadoluJet typically generates a new flight schedule. The company's primary scheduling concerns are aircraft fleet utilization and the waiting times of transfer passengers. Balancing the trade-off between these two criteria in a flight schedule is crucial for AnadoluJet's profitability. In this paper, we present the results of our study of AnadoluJet's flight-scheduling process. We provide a mathematical model that addresses this problem and then extend our studies and implement a heuristic algorithm for the development of a decision support system for the company. The objectives of the models we generated are to maximize fleet utilization, minimize waiting times for the majority of transfer passengers, and generate flight schedules subject to various constraints. The schedules that result from our models are superior to those that AnadoluJet's generated using its previous manual process. AnadoluJet currently uses our decision support system in its flight-scheduling process. © 2016 INFORMS

CPEL Redesigns Its Land Express Network

The China Postal Express and Logistics Corporation (CPEL), Chinas largest corporation in the express delivery industry, is restructuring its nationwide land express network after completing its reorganization. In this redesign project, we proposed a network design framework and developed a decision support system (MMHHSNDDSS) to integrate and optimize the topology structure and functional configuration of CPELs intermodal and multilayered network. Our model seeks to minimize operations and investment costs, constrained by the delivery time limits of CPELs service products. Using MMHHSNDDSS, CPELs senior management team can determine the optimal network by incorporating soft constraints, such as the experience of CPELs decision makers, into a series of solutions. According to an evaluation based on data gathered in 2009, CPEL expects the new network to improve service levels and provide savings of more than 20 percent in annual operations costs. The implementation of our proposed solution began in 2010. In addition, the quantitative methods applied in this project have changed the companys attitude toward applying operations research methods to strategic decision-making processes

Abundance and diversity of endogenous retroviruses in the chicken genome

Long terminal repeat (LTR) retrotransposons are autonomous eukaryotic repetitive elements which may elicit prolonged genomic and immunological stress on their host organism. LTR retrotransposons comprise approximately 10 % of the mammalian genome, but previous work identified only 1.35 % of the chicken genome as LTR retrotransposon sequence. This deficit appears inconsistent across birds, as studied Neoaves have contents comparable with mammals, although all birds contain only one LTR retrotransposon class: endogenous retroviruses (ERVs). One group of chicken-specific ERVs (Avian Leukosis Virus subgroup E; ALVEs) remain active and have been linked to commercially detrimental phenotypes, such as reduced lifetime egg count, but their full diversity and range of phenotypic effects are poorly understood. A novel identification pipeline, LocaTR, was developed to identify LTR retrotransposon sequences in the chicken genome. This enabled the annotation of 3.01 % of the genome, including 1,073 structurally intact elements with replicative potential. Elements were depleted within coding regions, and over 40 % of intact elements were found in clusters in gene sparse, poorly recombining regions. RNAseq analysis showed that elements were generally not expressed, but intact transcripts were identified in four cases, supporting the potential for viral recombination and retrotransposition of non-autonomous repeats. LocaTR analysis of seventy-two additional sauropsid genomes revealed highly lineage-specific repeat content, and did not support the proposed deficit in Galliformes. A second, novel bioinformatic pipeline was constructed to identify ALVE insertions in whole genome resequencing data and was applied to eight elite layer lines from Hy-Line International. Twenty ALVEs were identified and diagnostic assays were developed to validate the bioinformatic approach. Each ALVE was sequenced and characterised, with many exhibiting high structural intactness. In addition, a K locus revertant line was identified due to the unexpected presence of ALVE21, confirmed using BioNano optic maps. The ALVE identification pipeline was then applied to ninety chicken lines and 322 different ALVEs were identified, 81 % of which were novel. Overall, broilers and non-commercial chickens had a greater number of ALVEs than were found in layers. Taken together, these two analyses have enabled a thorough characterisation of both the abundance and diversity of chicken ERVs