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

Part of the Lecture Notes in Computer Science book series (LNAI,volume 9883)

Abstract

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.

Keywords

  • InterCriteria Analysis
  • Ant Colony Optimization
  • GPS surveying

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Acknowledgments

This work was partially supported by two grants of the Bulgarian National Scientific Fund: DFNI-I02/5 “InterCriteria Analysis – A New Approach to Decision Making”, and by the grant DFNP-176-A1.

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Correspondence to Stefka Fidanova .

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Fidanova, S., Roeva, O., Mucherino, A., Kapanova, K. (2016). InterCriteria Analysis of Ant Algorithm with Environment Change for GPS Surveying Problem. In: Dichev, C., Agre, G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2016. Lecture Notes in Computer Science(), vol 9883. Springer, Cham. https://doi.org/10.1007/978-3-319-44748-3_26

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  • DOI: https://doi.org/10.1007/978-3-319-44748-3_26

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