Finding Minimal Addition Chains with a Particle Swarm Optimization Algorithm

Energy Efficient Wireless Communication Using Genetic Algorithm Guided Faster Light Weight Digital Signature Algorithm (Gadsa)

“…In [1, 4096]), is presented in order to compare the results with respect to earlier [11,12,14,15] and proposed GADSA and some other heuristic [13] and deterministic [3,4,5,9] algorithms that has been proposed so far. Table 1 represents the optimal value and the best results reached by proposed GADSA and existing heuristics and deterministic approaches.…”

“…In the range of [1, 1024], [1,2000], [1,2048], [1,4096] proposed GADSA has obtained the best results compare to the other existing methods. Table 1 Comparison of best results obtained by the former version of (GA [11,12], PSO [14]), AIS [13], Quaternary, Binary and proposed GADSA Table 3 shows average length of addition chain for proposed GADSA vs. Binary, Quaternary technique where GADSA obtained shortest addition chain in exponent size compare to the Binary and Quaternary techniques. Table 3 Average length of addition chain for proposed GADSA vs. Binary, Quaternary method Table 4 shows addition chains for some of the special class of exponent.…”

Collective Intelligence for Evaluating Synergy in Collaborative Innovation

“…A collective intelligence approach, particle swarm optimization is selected to evaluate the collaborative synergy since it has the social component in parallel with the knowledge based evaluation [11]. However, the fact that the classical particle swarm method is based on balancing the exploration and exploitation at the particle level [12] would mean individual success of each company. An advanced new particle swarm algorithm, foraging search is based on creating balance of exploitation and exploration at the swarm level as well as particle level, which allows us to calculate the collaborative success [13].…”

A Review on Heuristics for Addition Chain Problem: Towards Efficient Public Key Cryptosystems

“…ACP is an NPhard, while its generic ASP is proven as NP-complete problem (Downey et al, 1981). Therefore, heuristic (Bos and Coster, 1990;Gelgi and Onus, 2006;Koc, 1995;Lee et al, 2006;Park et al, 1999) and metaheuristic (Cruz-Cortés et al, 2005;2008;Jose-Garcia et al, 2011;León-Javier et al, 2009;Osorio-Hernández et al, 2009;Dominguez-Isidro and Mezura-Montes, 2011;Dominguez-Isidro et al, 2015) have become alternative approaches in searching for near optimal solution for the ACP.…”

“…An even more optimal result is realized consequent to the mentioned improvements. Nedjah and Mourelle (2004;2006) applied distributed multi-agent ant system ACO, while León-Javier et al (2009) use the PSO. Both are similar to GA.…”