optimization problems using evolutionary algorithms (EAs). However, the presence of equality constraints makes the feasible space … will influence the future research direction for constrained optimization using population based algorithms. The proposed …

Hybridisation of algorithms to develop efficient solution methods for solving various NP-hard problems has been a … exact, heuristic and metaheuristic algorithms to develop better solution methods than the existing ones. In this study we … compared with some recent algorithms available in the literature. The proposed hybrid algorithm is based on the two popular …

We examine the concept of storing all evaluated chromosomes and directly reuse them in Genetic Algorithms (GAs). This …, while the encapsulation of the code facilitates implementation with other Evolutionary Algorithms. Copyright Springer …

a change in methodology can improve tractability, a combination of two techniques, fuzzy logic and genetic algorithms …

a change in methodology can improve tractability, a combination of two techniques, fuzzy logic and genetic algorithms …

-line algorithms, which are (4+epsilon)-competitive in either case. Our preemptive algorithm is 2-competitive, which actually meets the …

insights. In the future, data will automatically be opened and streamed and could be used in using OLSD algorithms. Algorithms … advanced OLSD algorithms. Further research on OLSD may be required in appreciating the impact of OLSD in different settings …

heuristic algorithms. In this article, we apply and investigate a new heuristic approach called Heart algorithm to solve … algorithms and show that the Heart algorithm performs well in finding the shortest distance within the minimum span of time. …

algorithms are computationally inexpensive compared to other more sophisticated methods for combinatorial optimization; this …