GPU-based Approaches for Multiobjective Local Search Algorithms. A Case Study: the Flowshop Scheduling Problem

International audienceMultiobjective local search algorithms are efficient methods to solve complex problems in science and industry. Even if these heuristics allow to significantly reduce the computational time of the solution search space exploration, this latter cost remains exorbitant when very large problem instances are to be solved. As a result, the use of GPU computing has been recently revealed as an efficient way to accelerate the search process. This paper presents a new methodology to design and implement efficiently GPU-based multiobjective local search algorithms. The experimental results show that the approach is promising especially for large problem instances

Impaired CFTR-dependent amplification of FSH-stimulated estrogen production in cystic fibrosis and PCOS

Context: Estrogens play important roles in a wide range of physiological and pathological processes, and their biosynthesis is profoundly influenced by FSH that regulates the rate-limiting enzyme aromatase-converting estrogens from androgens. Abnormal estrogen levels are often seen in diseases such as ovarian disorders in polycystic ovarian syndrome (PCOS), an endocrine disorder affecting 5-10% ofwomenof reproductive age, and cystic fibrosis (CF), acommongenetic disease caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR). Objectives: We undertook the present study to investigate the mechanism underlying these ovarian disorders, which is not well understood. Results: FSH-stimulated cAMP-responsive element binding protein phosphorylation, aromatase expression, andestradiol production are found to be enhanced by HCO 3 - and a HCO 3 - sensor, the soluble adenylyl cyclase, which could be significantly reduced by CFTR inhibition or in ovaries or granulosa cells of cftr knockout/ΔF508 mutant mice. CFTR expression is found positively correlated with aromatase expression in humangranulosacells,supportingits role in regulating estrogen production in humans. Reduced CFTR and aromatase expression is also found in PCOS rodent models and human patients. Conclusions: CFTR regulates ovarian estrogen biosynthesis by amplifying the FSH-stimulated signal via the nuclear soluble adenylyl cyclase. The present findings suggest that defective CFTR-dependent regulation of estrogen production may underlie the ovarian disorders seen in CF and PCOS. Copyright © 2012 by The Endocrine Society

Data mining using parallel multi-objective evolutionary algorithms on graphics processing units

An important and challenging data mining application in marketing is to learn models for predicting potential customers who contribute large profits to a company under resource constraints. In this chapter, we first formulate this learning problem as a constrained optimization problem and then convert it to an unconstrained multi-objective optimization problem (MOP), which can be handled by some multi-objective evolutionary algorithms (MOEAs). However, MOEAs may execute for a long time for theMOP, because several evaluations must be performed. A promising approach to overcome this limitation is to parallelize these algorithms. Thus we propose a parallel MOEA on consumer-level graphics processing units (GPU) to tackle the MOP. We perform experiments on a real-life direct marketing problem to compare the proposed method with the parallel hybrid genetic algorithm, the DMAX approach, and a sequential MOEA. It is observed that the proposed method is much more effective and efficient than the other approaches