BackgroundThe haplotype phasing problem tries to screen for phenotype associated genomic variations from millions of candidate data. Most of the current computer programs handle this problem with high requirements of computing power and memory. By replacing the computation-intensive step of constructing the maximum spanning tree with a heuristics of estimated initial haplotype, we released the WinHAP algorithm version 1.0, which outperforms the other algorithms in terms of both running speed and overall accuracy.ResultsThis work further speeds up the WinHAP algorithm to version 2.0 (WinHAP2) by utilizing the divide-and-conquer strategy and the OpenMP parallel computing mode. WinHAP2 can phase 500 genotypes with 1,000,000 SNPs using just 12.8 MB in memory and 2.5 hours on a personal computer, whereas the other programs require unacceptable memory or running times. The parallel running mode further improves WinHAP2's running speed with several orders of magnitudes, compared with the other programs, including Beagle, SHAPEIT2 and 2SNP.ConclusionsWinHAP2 is an extremely fast haplotype phasing program which can handle a large-scale genotyping study with any number of SNPs in the current literature and at least in the near future.
Most companies survive the pain of cost and schedule overruns because of inaccurate project activity time settings. In order to deliver a project with a target cost and on schedule, this research proposes an inverse optimal value approach to optimize activity durations and the corresponding worker assignments synchronously to make the optimal project cost infinitely close to an ideal cost. The leader model reflects cost orientation and adjustability of activity durations, the follower model reflects the complexity of activity sequence, critical path completion time, cost pressure, skill matching, energy consumption, and other costs. Through upper-level and lower-level feedback and interaction of activity durations and worker assignments it is possible to deliver a project with an ideal cost. With considerations of the mathematical model characteristics of bi-level programming, nonlinearity, NP hard, and MAX functions, an improved genetic algorithm combining adaptive artificial fish swarms is designed. From the comparison results of random examples and an actual example, the error rate of the optimal value of the improved algorithm is acceptable. Numerical experiments show that the inverse optimal approach can deliver a project without delay and with an ideal cost. The inverse optimization method is more in line with the idea of target management, and can help managers achieve the purpose of cost control.
This paper explores the logistics strategy selection of a manufacturer that uses two sales channels (resale and agency channels) to sell the same product through an E-commerce platform. The agency channel offers two logistic strategies, low-quality logistics services provided by third-party enterprises (Strategy N) and high-quality logistics services provided by the platform (Strategy S). When the manufacturer opts for Strategy S, a portion of the market share of the resale channel shifts to the agency channel, which results in the platform logistics effect. We developed a game-theoretic model to investigate the equilibrium results of a manufacturer under different logistics strategies. The results show that there exists a threshold for the platform logistics effect. When the platform logistics effect is lower than this threshold, the manufacturer prefers Strategy N. Otherwise, the manufacturer prefers Strategy S. However, when the platform logistics price reaches a certain level, the manufacturer will always prefer Strategy N. Our study provides valuable insights for manufacturers and e-commerce platforms to optimize their operational decisions based on different logistics strategies. It also helps manufacturers make rational choices about logistics strategies.
Through analyzing the value of the construction about service system of Fitness for all in new countryside, we established the evaluation index system for it by using document-research method, Delphi method etc. This system contains six first-level indices, fifteen second-level indices and forty seven third-indices. We hope to provide scientific theory for the evaluation on service system of fitness for all in new countryside of China.
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