Ant colony systems optimization applied to BNF grammars rule derivation (ACORD algorithm)

Abstract

Ant colony systems have been widely employed in optimization issues primarily focused on path flnding optimization, such as travelling salesman problem. The main advantage lies in the choice of the edge to be explored, deflned using pheromone trails. This paper proposes the use of ant colony systems to explore a Backus-Naur form grammar whose elements are solutions to a given problem. Similar models, without using ant colonies, have been used to solve optimization problems or to automatically genérate programs such as grammatical swarm (based on particle swarm optimization) and grammatical evolution (based on genetic algorithms). This workpresents the application of proposed ant colony rule derivation algorithm and benchmarks this novel approach in a well-known deceptive problem, the Santa Fe Trail. Proposed algorithm opens the way to a new branch of research in swarm intelligence, which until now has been almost nonexistent, using ant colony algorithms to genérate solutions of a given problem described by a BNF grammar with the advantage of genotype/phenotype mapping, described in grammatical evolution. In this case, such mapping is performed based on the pheromone concentration for each production rule. The experimental results demónstrate proposed algorithm outperforms grammatical evolution algorithm in the Santa Fe Trail problem with higher success rates and better solutions in terms of the required steps.

Sensitivity of shortest distance search in the ant colony algorithm with varying normalized distance formulas

“…Ant colony algorithm has been developed in order to get optimization so that variations appear [10]. Ant algorithm variations starting from the first version are called ant system (AS), which is applied to TSP, elitist ant system (EAS), rank-based ant system (ASrank), min-max ant system (MMAS), ant colony system (ACS), approximate nondeterministic tree search (ANTS) and hyper-cube framework for ACO [11], [12]. Ant colony algorithm can be used in various disciplines, one of which is Abd-Allah et al [13] ptimizing with ant colony in lightning hazard mitigation at more sensitive points in wind farms and getting results can contribute 1252 in designing the best place for wind farms and can increase capital on protection from lightning in certain areas.…”

Algorítmica Computacional Bioinspirada aplicada a Smart Cities : el Paradigma de la Computación Natural

“…Es reseñable que, entre otras publicaciones, la base teórica sobre Natural Computing ha valido la publicación de [Morales Lucas et al, 2018] (JCR Q2). En la misma línea, ACORD ha merecido la publicación de [de Mingo et al, 2019] (JCR Q2).…”

“…• Inexistencia de estudios actuales que apliquen Ant Colony Optimization (ACO) en el ámbito de GE: A pesar de la existencia de investigaciones que aplican otras técnicas de la Computación Natural en GE, como [Koza, 1989], ninguna toma ventaja de los posibles beneficios de ACO. (Este factor es precisamente conseguido por el Algoritmo ACORD [de Mingo et al, 2019] que propone la presente Tesis Doctoral. )…”

“…It is noteworthy that, among other publications, the theoretical basis on Natural Computing have deserved the publication of [Morales Lucas et al, 2018] (JCR Q2). Along the same lines, ACORD has deserved the publication of [de Mingo et al, 2019] (JCR Q2).…”

“…It is noteworthy that, among other publications, the theoretical basis on Natural Computing have deserved the publication of [Morales Lucas et al, 2018] (JCR Q2). Along the same lines, ACORD has deserved the publication of [de Mingo et al, 2019] (JCR Q2).Finally, once the achievement of the aforementioned goals has been accomplished, the future investigation paths lead by this Ph.D, accompanied with the applicable conclusions will be shown, reinforced with the relevant annexes in order to complement the needed information.…”