This paper introduces a new hybrid algorithm for locating all solutions in multimodal optimization problems. This algorithm combines an adaptive sequential niche techniquewith deterministic local optimization to detect all extrema efficiently and reliably. A genetic element of the hybrid algorithm performs W vailable online 9 March 2009

The non-convex behavior presented by nonlinear systems limits the application of classical optimization techniques to solve optimal control problems for these kinds of systems. This paper proposes a hybrid algorithm, namely BA-SD, by combining Bee algorithm (BA) with steepest descent (SD) method for numerically solving nonlinear optimal control (NOC) problems. The proposed algorithm includes th...

In order to further enhance the accuracy of Web information extraction, and overcome the shortcomings of the Hidden Markov Model (HMM) and its hybrid method in parameter optimization, a novel Web extraction algorithm based on a combined and improved particle swarm optimization, ant colony algorithm (IPSO-ACA) and HMM is presented. First, an HMM for information extraction is built. Second, an im...

In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...

one of the problems that sometimes occur in gas allocation optimization is instability phenomenon. this phenomenon reduces the oil production and damages downhole and surface facilities. different works have studied the stability and suggested some solutions to override it, but most of them (such as making the well intelligent) are very expensive and thus they are not applicable to many cases. ...

Concrete is the second most consumed material after water and the most widely used construction material in the world. The compressive strength of concrete is one of its most important mechanical properties, which highly depends on its mix design. The present study uses the intelligent methods with instance-based learning ability to predict the compressive strength of concrete. To achieve this ...

This paper presents an efficient hybrid method, namely fuzzy particleswarm optimization (FPSO) and fuzzy c-means (FCM) algorithms, to solve the fuzzyclustering problem, especially for large sizes. When the problem becomes large, theFCM algorithm may result in uneven distribution of data, making it difficult to findan optimal solution in reasonable amount of time. The PSO algorithm does find ago...

Partricular features of overpassing local optima and providing near-optimal soultion in practical time has led researchers to apply metaheuristics in several engineering problems. Optimal design of diagrids as one of the most efficient structural systems in tall buildings has been concerned here. Jaya algorithm as a recent paramter-less optimization method is employed to solve the problem using...

A well-known clustering algorithm is K-means. This algorithm, besides advantages such as high speed and ease of employment, suffers from the problem of local optima. In order to overcome this problem, a lot of studies have been done in clustering. This paper presents a hybrid Extended Cuckoo Optimization Algorithm (ECOA) and K-means (K), which is called ECOA-K. The COA algorithm has advantages ...

In this work, a multi-objective hybrid optimizer is presented. The optimizer uses several multi-objective evolutionary optimization algorithms and orchestrates the application of these algorithms to multi-objective optimization problems, using an automatic internal switching algorithm. The switching algorithm is designed to favor those search algorithms that quickly improve the Pareto approxima...