This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minim...

the air transport industry is seeking to manage risks in air travels. its main objective is to detect abnormal behaviors in various flight conditions. the current methods have some limitations and are based on studying the risks and measuring the effective parameters. these parameters do not remove the dependency of a flight process on the time and human decisions. in this paper, we used an hmm...

We consider the problem of estimating an upper bound on capacity a memoryless channel with unknown law and continuous output alphabet. A novel data-driven algorithm is proposed that exploits dual representation where maximization over input distribution replaced minimization reference output. To efficiently compute required divergence between conditional distribution, we use modified mutual inf...

The EM algorithm heavily relies on the interpretation of observations as incomplete data but it does not have any control on the uncertainty of missing data. To effectively reduce the uncertainty of missing data, we present a regularized EM algorithm that penalizes the likelihood with the mutual information between the missing data and the incomplete data (or the conditional entropy of the miss...

This paper addresses the issue of matching rigid 3D object points with 2D image points through point registration based on maximum likelihood principle in computer simulated images. Perspective projection is necessary when transforming 3D coordinate into 2D. The problem then recasts into a missing data framework where unknown correspondences are handled via mixture models. Adopting the Expectat...