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Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Bal...

Metaheuristics are used as very good optimization methods and they imitate natural, biologic, social and cultural process. In this work, we evaluate and compare three different metaheuristics which are population-based: ...

In this paper we present a comparative study of four trajectory metaheuristics or single-solution based metaheuristics (S-meta heuristics): Iterated Local Search (ILS), Greedy Randomized Adaptive Search Procedure (GRASP)...

The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software E...

The resolution of optimization problems is of great interest nowadays and has encouraged the development of various information technology methods to attempt solving them. There are several problems related to Software E...

This article presents the empirical evaluation of several simple metaheuristics applied to solve the Generalized Steiner Problem (GSP). This problem models the design of high-reliability communication networks, demanding...

The article describes the proposition and implementation of a demonstration, learning and decision support system for the resolution of combinatorial optimization problems under multiple objectives. The system brings tog...

Operations Research, Management Science or Business Analytics is a technology that helps improve business decision making. This book is focused on linear, integer, nonlinear and multiobjective programming, as well as mul...

Metaheuristics based on swarm intelligence simulate the behavior of a biological social system like as a flock of birds or a swarm of bees, and they have achieved important advances for solving optimization problems. In ...

The immense amount of data managed during the diagnosis process overwhelms, by far, the clinicians’ processing capabilities. Artificial intelligence methods like Multi-Layer Perceptrons come to help by providing a seco...

Abstract The Eocene–Oligocene transition was the crucial turning point when Earth’s climate shifted to its current icehouse state. Understanding how the marine biosphere responded during this transition is not well-c...

This paper presents an encoding scheme adapted for Fiber Bragg Grating (FBG) optimization using metaheuristics. The proposed encoding scheme uses spline approximations in order to build softened refractive index profiles...

Introduction. Metaheuristic algorithms are effective for solving complex power system optimization problems characterized by nonlinearity, multimodality, and high dimensionality. Nature-inspired strategies based on adapt...

In the past, numerous approaches have been formulated either for approximating Pareto-optimal alternatives or supporting the decision making process with an interactive multi criteria decision aiding methodology. The art...

Two powerful metaheuristics being used successfully since their creation for the resolution of optimization problems are Cellular Genetic Algorithm (cGA) and Particle Swam Optimization (PSO). Over the last years, interes...

This work studies the solution space topology of the Traveling Salesman Problem or TSP, as a bi-objective optimization problem. The concepts of category and range of a solution are introduced for the first time in this ...

It is known that the Minimum Weight Triangulation problem is NP-hard. Also the complexity of Minimum Weight Pseudo-Triangulation problem is unknown, suspecting that it is also a NP-hard problem. Therefore we focused on ...

The Flow Shop Scheduling Problem have been tackled using different techniques which goes from mathematical techniques like Branch and Bound to metaheuristics like evolutionary algorithms (EAs). Although in the real worl...

Ant Colony Optimization algorithms are intrinsically distributed algorithms where independent agents are in charge of building solutions. Stigmergy or indirect communication is the way in which each agent learns from the...

Given the large number of optimization problems that mankind faces, metaheuristics are very important strategies for the resolution of these problems. These strategies assess the suitability of the individuals, which rep...

Subjects / keywords: Metaheuristics; Operations research; Combinatorial optimization; Approximation theory

BackgroundLast-mile logistics accounts for approximately 28% of total logistics costs and is a major contributor to urban carbon emissions. The integration of drones with electric trucks offers a path toward more efficie...

Early applications of Ant Colony Optimization (ACO) have been mainly concerned with solving ordering problems (e.g., the Traveling Salesperson Problem). More recently, promising results were obtained for solving the Mult...

Subjects / keywords: machine learning, scheduling, internet of things, metaheuristics, optimization, network security; Technology: Technology (General): Industrial engineering. Management engineering: Information technology