The study of greedy approximation in the context convex optimization is becoming a promising research direction as algorithms are actively being employed to construct sparse minimizers for functions with respect given sets elements. In this paper we propose unified way analyzing certain kind greedy-type minimization on Banach spaces. Specifically, define class Weak Biorthogonal Greedy Algorithm...

Studying the theoretical properties of optimization algorithms such as genetic and evolutionary strategies allows us to determine when they are suitable for solving a particular type problem. Such study consists three main steps. The first step is considering Stochastic Global Optimization Algorithms (SGoals ), i.e., iterative algorithm that applies stochastic operations set candidate solutions...

although lot streaming scheduling is an active research field, lot streaming flexible flow lines problems have received far less attention than classical flow shops. this paper deals with scheduling jobs in lot streaming flexible flow line problems. the paper mathematically formulates the problem by a mixed integer linear programming model. this model solves small instances to optimality. moreo...

Nowadays, cross-docking is one of the main concepts in supply chain management in which products received to a distribution center by inbound trucks which are directly to lead into outbound trucks with a minimum handling and storage costs as the main cost of a cross-docking system. According to the literature, several metaheuristics and heuristics are attempted to solve this optimization model....

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...