Shuffled frog leaping algorithm is a new kind of swarm intelligence optimization algorithm. Due to the local search of the basic shuffled frog leaping algorithm which is the only by the worst frog to search and jump, searching ability of which was limited; therefore it had the low precision, slow convergence speed and easy premature convergence etc. Therefore, in order to enhance the ability of...

Recommendation systems are a powerful tool that is an integral part of great many websites. Most often, recommendations presented in the form list generated by using various recommendation methods. Typically, however, these methods do not generate identical recommendations, and their effectiveness varies between users. In order to solve this problem, application aggregation techniques was sugge...

The field of parallel metaheuristics is continuously evolving as a result of new technologies and needs that researchers have been encountering. In the last decade, new models of algorithms, new hardware for parallel execution/communication, and new challenges in solving complex problems have been making advances in a fast manner. We aim to discuss here on the state of the art, in a summarized ...

The reconstruction of DNA sequences from DNA fragments is one of the most challenging problems in computational biology. In recent years the specific problem of DNA sequencing by hybridization has attracted quite a lot of interest in the optimization community. Despite the fact that well-working constructive heuristics are often the basis for well-working metaheuristics, only two constructive h...

Metaheuristics are techniques that use approximate and intuitive strategies to quickly find near-optimal solutions of complex optimization problems. A number of outstanding examples belong to evolutionary computation, the class of methods inspired to biological and evolutionary phenomena. These techniques have been extensively and successfully applied to feature-based image registration in medi...

Abstract Initialization of metaheuristics is a crucial topic that lacks comprehensive and systematic review the state art. Providing such requires in‐depth study knowledge advances challenges in broader field metaheuristics, especially with regard to diversification strategies, order assess proposed methods provide insights for initialization. Motivated by aforementioned research gap, we relate...

In this paper three metaheuristics are used to solve a smart grid multi-objective energy management problem with conflictive design: how to maximize profits and minimize carbon dioxide (CO2) emissions, and the results compared. The metaheuristics implemented are: weighted particle swarm optimization (W-PSO), multi-objective particle swarm optimization (MOPSO) and non-dominated sorting genetic a...

The aim of this paper is to compare different metaheuristics for the graph bisection problem. For this purpose, the Bui and Moon’s genetic algorithm adaptation for graph bisection is used. A second genetic algorithm adaptation for graph bisection is also presented. These algorithms are compared to an implementation of the iterated local search metaheuristic for graph bisection. All these metahe...