The one-dimensional cutting stock problem, has so many applications in lots of industrial processes and during the past few years has attracted so many researchers’ attention all over the world. In this paper a meta-heuristic method based on ACO is presented to solve this problem. In this algorithm, based on designed probabilistic laws, artificial ants do select various cuts and then select the...

In cloud computing tasks scheduling problem is NP-hard, furthermore it does onerous for attaining an optimum resolution. Extremely quick optimization algorithms are used to proximate the optimum resolution, like ACO (ant colony optimization) algorithm. In cloud computing, in consideration to solve the problem of task scheduling, a period ACO (PACO)-based arranging algorithmic rule has been used...

1M.Tech. Scholar, Department of Computer Science & Applications, Kurukshetra University, Haryana, India 2Assistant Professor, Department of Computer Science & Applications, Kurukshetra University, Haryana, India -------------------------------------------------------------------------***-----------------------------------------------------------------------AbstractThe distributed architecture o...

A distinctive optimization technique known as Ant Colony Optimization (ACO) has gained huge popularity in these recent years due to its flexibility and the ability to avoid reaching local optima. This optimization approach has become a candidate approach for many optimization problems. Unfortunately, this attractive algorithm suffers several downsides including stagnation and slow convergence t...

The Bounded Diameter Minimum Spanning Tree problem (BDMST) and the Hop Constrained Minimum Spanning Tree problems (HCMST) are NP-hard combinatorial optimization problems which have their main application in network design. In this thesis an existing relax-and-cut approach for finding lower bounds and approximate solutions to those problems is enhanced and extended, and a hybrid algorithm based ...

Ant Colony Optimization (ACO) a nature-inspired metaheuristic algorithm has been successfully applied in the traveling salesman problem (TSP) and a variety of combinatorial problems. In fact, ACO can effectively fit to discrete optimization problems and exploit pre-knowledge of the problems for a faster convergence. We present an improved version of ACO with a kind of Genetic semi-random-restar...