In this research application paper, the usefulness of an intelligent mechanism (a cubic spline smoothing technique) for determining when to switch from one algorithm to another within a meta heuristic search process is explored. We concentrated on a typical planning problem for a southern United States forestry company where the net present value of management activities is maximized subject to...

Meta-heuristics are algorithms which are applied to solve problems when conventional algorithms can not find good solutions in reasonable time; evolutionary algorithms are perhaps the most well-known examples of meta-heuristics. As there are many possible meta-heuristics, finding the most suitable meta-heuristic for a given problem is not a trivial task. In order to make this choice, one can de...

Meta-heuristics are high-level approaches developed to discover a heuristic that provides reasonable solution many varieties of optimization problems. The classification problems contain sort problem. Simply, the objective herein is reduce number misclassified instances. In this paper, question whether meta-heuristic methods can be used construct linear models or not answered. To end, Particle ...

Distributed systems such as Grid- and Cloud Computing provision web services to their users in all of the world. One of the most important concerns which service providers encounter is to handle total cost of ownership (TCO). The large part of TCO is related to power consumption due to inefficient resource management. Task scheduling module as a key component can has drastic impact on both user...

this paper addresses a new version of the exible ow line prob- lem, i.e., the budget constrained one, in order to determine the required num- ber of processors at each station along with the selection of the most eco- nomical process routes for products. since a number of parameters, such as due dates, the amount of available budgets and the cost of opting particular routes, are imprecise (fuzz...

Feature selection is vital in the field of pattern classification due to accuracy and processing time considerations.The selection of proper features is of greater importance when the initial feature set is considerably large. Text classification is a typical example of this situation, where the size of the initial feature set may reach to hundreds or even thousands. There are numerous research...

Flow shop scheduling of jobs has always been a popular problem that has found solutions in the number of heuristic and meta-heuristic techniques. In this manuscript, two-machine flow shop scheduling problem has been investigated while optimizing makespan and idle time of machines. Uncertainties in the processing time and set up times of jobs involved are also taken into consideration in the for...