The relevant literature showed that many heuristic techniques have been investigated for constrained portfolio optimization problem but none of these studies presents multi-objective Scatter Search approach. In this work, we present a hybrid multi-objective population-based evolutionary algorithm based on Scatter Search with an external archive to solve the constrained portfolio selection probl...

Scatter search is an evolutionary method that, unlike genetic algorithms, operates on a small set of solutions and makes only limited use of randomization as a proxy for diversification when searching for a globally optimal solution. The scatter search framework is flexible, allowing the development of alternative implementations with varying degrees of sophistication. In this paper, we test th...

In this paper we discuss the application of a metaheuristic approach based on the Scatter Search to deal with robust optimization of the planning problem in the deploying of the Dense Wavelength Division Multiplexing (DWDM) technology on an existing optical fiber network taking into account, in addition to the forecasted demands, the uncertainty in the survivability requirements. Keyword: Netwo...

The problem of finding a global optimum of an unconstrained multimodal function has been the subject of intensive study in recent years, giving rise to valuable advances in solution methods. We examine this problem within the framework of adaptive memory programming (AMP), focusing particularly on AMP strategies that derive from an integration of Scatter Search and Tabu Search. Computational co...

In the paper, two evolutionary approaches to the general DNA sequencing problem, assuming both negative and positive errors in the spectrum, are compared. The older of them is based on the idea of genetic approach and is enhanced by a greedy algorithm. The newly proposed algorithm combines the tabu search and the scatter search methods. After conducting experiments with random and coding DNA se...

Multi-dimensional Visual Tracking (MVT) problems include visual tracking tasks where the system state is defined by a high number of variables corresponding to multiple model components and/or multiple targets. A MVT problem can be modeled as a dynamic optimization problem. In this context, we propose an algorithm which hybridizes Particle Filters (PF) and the Scatter Search (SS) metaheuristic,...

Scatter search is a population-based method that has recently been shown to yield promising outcomes for solving combinatorial and nonlinear global optimization problems. Based on formulations originally proposed in the 1960s for combining decision rules and problem constraints, such as in generating surrogate constraints, scatter search uses strategies for combining solution vectors that have ...

Article history: Received December 10, 2014 Received in revised format: January 4, 2015 Accepted February 20, 2015 Available online February 24 2015 This paper presents a new search methodology for different sizes of 0-1 Knapsack Problem (KP). The proposed methodology uses a modified scatter search as a meta-heuristic algorithm. Moreover, rough set theory is implemented to improve the initial f...