On the Resilience of Ant Algorithms. Experiment with Adapted MMAS on TSP

Elena Nechita, Gloria Cerasela Crişan, Laszlo Barna Iantovics and Yitong Huang
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Elena Nechita: Department of Mathematics and Informatics, Vasile Alecsandri University of Bacău, 600115 Bacău, Romania
Gloria Cerasela Crişan: Department of Mathematics and Informatics, Vasile Alecsandri University of Bacău, 600115 Bacău, Romania
Laszlo Barna Iantovics: Department of Electrical Engineering and Information Technology, George Emil Palade University of Medicine, Pharmacy, Science and Technology of Târgu Mureş, 540139 Târgu Mureş, Romania
Yitong Huang: Computer Science Department, Illinois Institute of Technology, Chicago, IL 60616, USA

Mathematics, 2020, vol. 8, issue 5, 1-20

Abstract: This paper focuses on the resilience of a nature-inspired class of algorithms. The issues related to resilience fall under a very wide umbrella. The uncertainties that we face in the world require the need of resilient systems in all domains. Software resilience is certainly of critical importance, due to the presence of software applications which are embedded in numerous operational and strategic systems. For Ant Colony Optimization (ACO), one of the most successful heuristic methods inspired by the communication processes in entomology, performance and convergence issues have been intensively studied by the scientific community. Our approach addresses the resilience of MAX–MIN Ant System (MMAS), one of the most efficient ACO algorithms, when studied in relation with Traveling Salesman Problem (TSP). We introduce a set of parameters that allow the management of real-life situations, such as imprecise or missing data and disturbances in the regular computing process. Several metrics are involved, and a statistical analysis is performed. The resilience of the adapted MMAS is analyzed and discussed. A broad outline on future research directions is given in connection with new trends concerning the design of resilient systems.

Keywords: resilience; nature-inspired algorithm; Ant Colony Optimization; MAX–MIN Ant System; Traveling Salesman Problem (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
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