The aim of this paper is to develop a parallel Scatter Search metaheuristic for solving the Feature Subset Selection Problem in classification. Given a set of instances characterized by several features, the classification problem consists of assigning a class to each instance. Feature Subset Selection Problem selects a relevant subset of features from the initial set in order to classify futur...

The symbiotic organisms search (SOS), which has been recently introduced, is a robust powerful metaheuristic global optimizer. This nature-inspired algorithm imitates the symbiotic interaction strategies in an ecosystem exercised by organisms involved in interrelationships to survive and reproduce. One of the main beneficial features of the SOS in contrast to many other competent metaheuristic ...

Nature-inspired algorithms are among the most powerful algorithms for optimization. This paper intends to provide a detailed description of a new Firefly Algorithm (FA) for multimodal optimization applications. We will compare the proposed firefly algorithm with other metaheuristic algorithms such as particle swarm optimization (PSO). Simulations and results indicate that the proposed firefly a...

This paper presents an exact algorithm, a constructive heuristic algorithm, and a metaheuristic for the Hamiltonian p-Median Problem (HpMP). The exact algorithm is a branch-and-cut algorithm based on an enhanced p -median based formulation, which is proved to dominate an existing p -median based formulation. The constructive heuristic is a giant tour heuristic, based on a dynamic programming fo...

The corridor allocation problem is one of assigning a given set of facilities in two rows along a straight corridor so as to minimize a weighted sum of the distances between every pair of facilities. This problem has practical applications in arrangements of rooms in offices and in hospitals. The problem is NP-hard. In this paper, we present two population based metaheuristic implementations fo...

This paper presents a novel biologically inspired metaheuristic algorithm called seven-spot ladybird optimization (SLO). The SLO is inspired by recent discoveries on the foraging behavior of a seven-spot ladybird. In this paper, the performance of the SLO is compared with that of the genetic algorithm, particle swarm optimization, and artificial bee colony algorithms by using five numerical ben...

Reliability based optimization (RBO) is one of the most appropriate methods for structural design under uncertainties. It searches for the best compromise between cost and safety while considering system uncertainties by incorporating reliability measures within the optimization. Despite the advantages of RBO, its application to practical engineering problem is still quite challenging. In this ...

This paper introduces a new social metaheuristic for the Max-Cut problem applied to a weighted undirected graph. This problem consists in finding a partition of the nodes into two subsets, such that the sum of the weights of the edges having endpoints in different subsets is maximized. This NP-hard problem for non planar graphs has several application areas such as VLSI and ASICs CAD. The hiera...

This paper presents an efficient metaheuristic approach for optimizing the generalized ratio problems such as sum and multiplicative of linear or nonlinear objective function with affine constraints. focuses on significance hybrid techniques, which are implemented by using GA ER-WCA to increase efficiency robustness solving problems. Initially, starts initial random population it is processed g...

High power consumption efficiency in wireless sensor networks is always desirable. One way to deal with this issue is using a linear integer programming model based upon a schedule of sensor allocation plans in multiple time intervals subject to coverage and connectivity constraints. The Generate-and-Solve (GS) methodology is a hybrid approach that combines a metaheuristic component with an exa...