An Interactive Fuzzy Satisficing Method for Multiobjective Stochastic Integer Programming Problems through Simple Recourse Model

Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective stochastic integer programming problems are transformed into deterministic ones. As a fusion of stochastic programming and fuzzy one, after introducing fuzzy goals to reflect the ambiguity of the decision maker's judgments for objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for the decision maker by updating the reference membership levels

An interactive fuzzy satisficing method for multiobjective linear-programming problems and its application,

Abstract-Two major approaches to deal with randomness or impression involved in mathematical programming problems have been developed. The one is called stochastic programming, and the other is called fuzzy programming. In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in constraints. Using the concept of simple recourse, such multiobjective stochastic integer programming problems are transformed into deterministic ones. As a fusion of stochastic programming and fuzzy one, after introducing fuzzy goals to reflect the ambiguity of the decision maker's judgments for objective functions, we propose an interactive fuzzy satisficing method to derive a satisficing solution for the decision maker by updating the reference membership levels

HLA-DQB1*03 Confers Susceptibility to Chronic Hepatitis C in Japanese: A Genome-Wide Association Study

<div><p>Hepatitis C virus (HCV) establishes a chronic infection in 70-80% of infected individuals. Many researchers have examined the effect of human leukocyte antigen (HLA) on viral persistence because of its critical role in the immune response against exposure to HCV, but almost all studies have proven to be inconclusive. To identify genetic risk factors for chronic HCV infection, we analyzed 458,207 single nucleotide polymorphisms (SNPs) in 481 chronic HCV patients and 2,963 controls in a Japanese cohort. Next, we performed a replication study with an independent panel of 4,358 cases and 1,114 controls. We further confirmed the association in 1,379 cases and 25,817 controls. In the GWAS phase, we found 17 SNPs that showed suggestive association (<i>P</i> < 1 × 10^-5). After the first replication study, we found one intronic SNP in the <i>HLA-DQ</i> locus associated with chronic HCV infection, and when we combined the two studies, the association reached the level of genome-wide significance. In the second replication study, we again confirmed the association (<i>P</i>_combined = 3.59 × 10⁻¹⁶, odds ratio [OR] = 0.79). Subsequent analysis revealed another SNP, rs1130380, with a stronger association (OR=0.72). This nucleotide substitution causes an amino acid substitution (R55P) in the HLA-DQB1 protein specific to the <i>DQB1*03</i> allele, which is common worldwide. In addition, we confirmed an association with the previously reported <i>IFNL3-IFNL4</i> locus and propose that the effect of <i>DQB1*03</i> on HCV persistence might be affected by the <i>IFNL4</i> polymorphism. Our findings suggest that a common amino acid substitution in HLA-DQB1 affects susceptibility to chronic infection with HCV in the Japanese population and may not be independent of the <i>IFNL4</i> genotype.</p> </div

Linkage disequilibrium structure around the HLA-DQ region based on <i>D</i>’ using HapMap-JPT Data.

<p>P-value plot and genomic structure of the GWAS stage. Blue lines represent the LD block containing the <i>HLA-DQA2</i> and <i>HLA-DQB2</i> loci. Black lines represent two LD blocks containing the <i>HLA-DQA1</i> and <i>HLA-DQB1</i> loci, and the black dotted line represents the boundary between them. The red line represents the most strongly associated SNP, rs9275572, which is located within the <i>HLA-DQB1</i> locus. The LD maps were created using HaploView software.</p