A Study of Fractional-Order Memristive Ant Colony Algorithm: Take Fracmemristor into Swarm Intelligent Algorithm

Author:

Zhu Wuyang1,Pu Yifei1

Affiliation:

1. College of Computer Science, Sichuan University, Chengdu 610065, China

Abstract

As the fourth fundamental circuit element, the memristor may execute computations while storing data. Fracmemristor takes advantage of the fractional calculate’s long-term memory, non-locality, weak singularity, and the memristor’s storage–computational integration. Since the physical structure of the fracmemristor is similar to the topology of the ant transfer probability flow in ACO, we propose the fractional-order memristive ant colony algorithm (FMAC), which uses the fracmemristor physical system to record the probabilistic transfer information of the nodes that the ant will crawl through in the future and pass it to the current node of the ant, so that the ant acquires the ability to predict the future transfer. After instigating the optimization capabilities with TSP, we discovered that FMAC is superior to PACO-3opt, the best integer-order ant colony algorithm currently available. FMAC operates substantially more quickly than the fractional-order memristor ant colony algorithm due to the transfer probability prediction module based on the physical fracmemristor system (FACA).

Funder

National Natural Science Foundation of China

China South Industries Group Corporation (Chengdu) Fire Control Technology Center Project

National Key Research and Development Program Foundation of China

Publisher

MDPI AG

Subject

Statistics and Probability,Statistical and Nonlinear Physics,Analysis

Reference49 articles.

1. Dorigo, M. (1992). Optimization, Learning and Natural Algorithms. [Ph.D. Thesis, Politecnico di Milano].

2. Dorigo, M., and Caro, G.D. (1999, January 6–9). Ant colony optimization: A new meta-heuristic. Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406), Washington, DC, USA.

3. Ant colony system: A cooperative learning approach to the traveling salesman problem;Dorigo;IEEE Trans. Evol. Comput.,1997

4. The ant system applied to the quadratic assignment problem;Maniezzo;IEEE Trans. Knowl. Data Eng.,1999

5. Ant system: Optimization by a colony of cooperating agents;Dorigo;IEEE Trans. Syst. Man Cybern. Part B Cybern.,1996

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