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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...

The Estimation Distribution Algorithms (EDAs) compose an evolutionary metaheuristic whose main characteristic is the construction of solutions in randomly form, using a distribution of probabilities that evolves during t...

Historically Functional Programming FP for short has been associated with a small scope of applications mainly academic The computer science community did not pay enough attention to its potential perhaps due t...

Over the past few years, a continually increasing number of research efforts have investigated the application of evolutionary computation techniques for the solution of scheduling problems. Scheduling problems can pose...

The Ant Colony Optimization (ACO) metaheuristic is a bio-inspired approach for hard combinatorial optimization problems for stationary and non-stationary environments. In the ACO metaheuristic, a colony of artificial ant...

A new issue for combinatorial optimization problems is to incorporate local search into the framework of evolutionary algorithms, leading to hybrid evolutionary algorithms. With the hybrid approach, evolutionary algorith...

La técnica Optimización de Colonias de Hormigas (ACO) puede ser aplicada a problemas de optimización combinatorios duros en ambientes estacionarios y no estacionarios. En dicha metaheurística, las hormigas artificial...

The choice of a search algorithm can play a vital role in the success of a scheduling application. Evolutionary algorithms (EAs) can be used to solve this kind of combinatorial optimization problems. Compared to conventi...

El presente trabajo trata la problemática que se presenta, cuando al inicio de cada ciclo lectivo, una institución educativa realiza las asignación de sus recursos disponibles (docentes, aulas, asignaturas, etc…), t...

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

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...

Interesting real world combinatorial problems are NP-complete and many of them are hard to solve by using traditional methods. However, several heuristic methods have been developed in order to obtain timely suboptimal s...

Protein Folding is an important open problem in the eld of Computational Biology Due to its com binatorial nature exact polynomial algorithms to solve it could not exist and so approximation algorithms and heurist...

Multiple crossover per couple (MCPC) is a newly introduced crossover method which in contrast with the single crossover per couple approach (SCPC), permits more than one crossover operation for each mating pair. MCPC was...

This paper presents an Ant Colony Optimisation (ACO) model for the Multiple Knapsack Problem (MKP). The ACO algorithms, as well as other evolutionary metaphors, are being applied successfully to diverse heavily constrain...