Skip to content
Research Article Open access CC BY 4.0

Discrete Artificial Dragonflies Algorithm in Agent Based Modelling for Exact Boolean kSatisfiability Problem

Hamza Abubakar, Sagir Abdu M., Surajo Yusuf, Yusuf Abdurrahman

Journal of Advances in Mathematics and Computer Science · pp. 115–134 · Published 7 Jul 2020

10.9734/jamcs/2020/v35i430275

Abstract

The development of metaheuristics and Boolean Satisfiability representation plays an important part in a neural network (NN) and Artificial Intelligence (AI) communities. In this paper, a new hybrid discrete version of the artificial dragonfly algorithm (DADA) applying a minimum objective function in agent-based modelling (ABM) obeying a specified procedure to optimize the states of neurons, for optimal Boolean Exact Satisfiability representation on NETLOGO as a dynamic platform. We combined the artificial dragonfly algorithm for its random searching ability that encourages diverse solutions and formation of static swarm’s mechanism to stimulus computational problems to converge to the best global optimal search space. The global performance of the proposed DADA was compared with genetic algorithm (GA)  that are available in the literature based on the global minimum ratio (gM), Local Minimum Ratio (yM), Computational time (CPU) and Hamming distance (HD).  The final results showed good agreement between the proposed DADA and discrete version of GA to efficiently optimize the Exact-kSAT problem.  It found that DADA-ABM has high potentiality for optimizing or modelling a network that is very hard or often impossible to capture by exact or traditional optimization modelling techniques such as Boolean satisfiability problem is better than existing methods in the literature.

Logic program artificial dragonfly algorithm Boolean Satisfiability Problem (SAT) exact ksatisfiability agent-based modelling

References (26)

  1. 1 Dragonfly algorithm: a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems [DOI]
  2. 2 Metaheuristics in Combinatorial Optimization [DOI]
  3. 3 Agent Based Modelling and Simulation tools: A review of the state-of-art software [DOI]
  4. 4 Model-based methods for continuous and discrete global optimization [DOI]
  5. 5 Algorithms for Secretary Problems on Graphs and Hypergraphs [DOI]
  6. 6 Improving ant colony optimization algorithm with epsilon greedy and Levy flight [DOI]
  7. 7 Generation dispatch of combined solar thermal systems using dragonfly algorithm [DOI]
  8. 8 A Novel Method for Multilevel Color Image Segmentation Based on Dragonfly Algorithm and Differential Evolution [DOI]
  9. 9 Exact Algorithms via Monotone Local Search [DOI]
  10. 10 GPU parallelization strategies for metaheuristics: a survey [DOI]
  11. 11 An Improved DA-PSO Optimization Approach for Unit Commitment Problem [DOI]
  12. 12 A Dragonfly Algorithm for Solving Traveling Salesman Problem [DOI]
  13. 13 Radial basis function neural network for 2 satisfiability programming [DOI]
  14. 14 Comparative study of genetic and discrete firefly algorithm for combinatorial optimization [DOI]
  15. 15 An algorithm for counting maximum weighted independent sets and its applications [DOI]
  16. 16 An Exact Fast Algorithm for Minimum Hitting Set [DOI]
  17. 17 Wavelength Selection for NIR Spectroscopy Based on the Binary Dragonfly Algorithm [DOI]
  18. 18 Learning in the Recurrent Hopfield Network [DOI]
  19. 19 An effective hybrid imperialist competitive algorithm and tabu search for an extended flexible job shop scheduling problem [DOI]
  20. 20 Finding All Solutions of the Boolean Satisfiability Problem, If Any, via Boolean Equation Solving [DOI]
  21. 21 Combinatorial optimization of permutation-based quadratic assignment problem using optics inspired optimization [DOI]
  22. 22 Exact Graph Coloring Algorithms of Getting Partial and All Best Solutions.
  23. 23 Toward Securing Cyber-Physical Systems Using Exact Cover Set [DOI]
  24. 24 Immune Based Genetic Algorithm to Solve a Combinatorial Optimization Problem: Application to Traveling Salesman Problem [DOI]
  25. 25 Solution of traveling salesman problem by hybrid imperialist competitive algorithm [DOI]
  26. 26 Preface: advances in theoretical and practical combinatorial optimization [DOI]

Cited by 3

Simulation Study on Modified Weibull Distribution for Modelling of Investment Return

Hamza Abubakar, Shamsul Rijal Muhammad Sabri · Pertanika Journal of Science and Technology · 2021

Showing 1 of 3 known citations — external sources report more than can currently be individually listed.

Article metrics

Real usage data collected on this platform.

41

Page views

0

PDF downloads

14

Outbound clicks

3

Citations

Views over time

Views by country

Approximate, from request IP at view time — not citizenship or institution. Countries with fewer than 5 views are grouped as "Other".

Traffic sources

Referring site, by host.

Views and downloads exclude known bots/crawlers. Citations combines this platform's own DOI-resolved index with each external source's own reported total — see Cited by above for individually listed citing works. Last refreshed 0 seconds ago.