InterCriteria Analysis of Ant Algorithm with Environment Change for GPS Surveying Problem

Stefka Fidanova (1) , Olympia Roeva (1) , Antonio Mucherino (2) , K. Kapanova (1)

1 BAS - Bulgarian Academy of Sciences
2 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics

In this paper we apply InterCriteria Analysis (ICrA), which is based on the apparatus of Index Matrices and Intuitionistic Fuzzy Sets. We apply ICrA on the well-known Ant Colony Optimization (ACO) general framework including environment change. The environment is simulated by means of the Logistic map, that is used in ACO for perturbing the update of the pheromone trails. We compare different levels of perturbation of the one of the most important parameters in ACO – the pheromone. Based on ICrA we examine the obtained identification results and discuss the conclusions about existing relations and dependencies between defined criteria, defined in terms of ICrA.

Domaines: Recherche opérationnelle [math.OC]

Stefka Fidanova, Olympia Roeva, Antonio Mucherino, K. Kapanova. InterCriteria Analysis of Ant Algorithm with Environment Change for GPS Surveying Problem. 17th International Conference on Artificial Intelligence: Methodology Systems, Applications (AIMSA16), Sep 2016, Varna, Bulgaria. pp.271-278, ⟨10.1007/978-3-319-44748-3_26⟩. ⟨hal-01402412⟩