Abstract Grey Wolf Optimizer (GWO) is a recently developed meta-heuristic search algorithm
inspired by grey wolves (Canis lupus), which simulate the social stratum and hunting …

Ant lion optimizer (ALO) is a newly developed population-based search algorithm inspired
by hunting mechanism of antlions and based on five steps of hunting the ants, ie, the …

Hybridization in optimization methods plays a very vital role to make it effective and efficient.
Different optimization methods have different search tendency and it is always required to …

In evolutionary algorithms, elites are crucial to maintain good features in solutions. However,
too many elites can make the evolutionary process stagnate and cannot enhance the …

Moth flame optimization algorithm is novel nature inspired heuristic paradigm inspired by
navigation method of moths in nature and based on the concept that the moth eventually …

This paper proposes a new hybrid metaheuristique algorithm based on the hybridization of
Biogeography-based optimization with the Differential Evolution for solving the optimal …

Abstract Biogeography Based Optimization (BBO) algorithm is a population-based algorithm
based on biogeography concept, which uses the idea of the migration strategy of animals or …

Traveling Salesman Problem (TSP) is an NP-hard combinatorial optimization problem with a
wide variety of applications. Biogeography-Based Optimization Algorithm (BBO) is a new …

Abstract Development of solutions to optimisation problems (including electrical power
systems) has remained an active research area in the recent decades, with interests in the …

Multi objective non-convex economic dispatch problems of a thermal power plant are of
grave concern for deciding the cost of generation and reduction of emission level for …