Ant colony optimization is a metaheuristic approach belonging to the model based search algorithm. It is a paradigm for designing metaheuristic algorithm for combinatorial problem. In this paper we discuss the Ant colony system. Ant colony system is one of the best algorithm of ant colony optimization. First we discuss the optimization,and one of the optimization problem is combinatiorial probl...

An improved method for adaptive noise canceller (ANC) is proposed for noisy speech signal in case of random noise. In this approach, ANC is implemented through four different metaheuristic techniques. A comparative study of the performance of various metaheuristic techniques such as Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), Cuckoo Search (CS) and Modified Cuckoo Search (MC...

<div align="left"><span lang="EN-US">An investment portfolio implies the assortment of assets invested in commodity market and equity funds across global markets. The critical issue associated with any under its optimization entails achievement an optimal Sharpe ratio related to risk-return. This turns complex when risk budgeting other investor preferential constraints are weighed i...

Metaheuristic algorithms are one of the most widely used stochastic approaches in solving optimization problems. In this paper, a new metaheuristic algorithm entitled Billiards Optimization Algorithm (BOA) is proposed and designed to be applications. The fundamental inspiration BOA design behavior players rules billiards game. Various steps described then its mathematical model thoroughly expla...

Mathematical optimization can be a useful strategy for minimizing energy usage while designing low-energy buildings. To handle building challenges, this study provides an effective hybrid technique based on the pelican algorithm (POA) and single candidate optimizer (SCO). The suggested (POSCO) benefits from both robust local search power of method efficient global capabilities optimization. con...

Increasing nature-inspired metaheuristic algorithms are applied to solving the real-world optimization problems, as they have some advantages over the classical methods of numerical optimization. This paper has proposed a new nature-inspired metaheuristic called Whale Swarm Algorithm for function optimization, which is inspired by the whales’ behavior of communicating with each other via ultras...

This paper proposes a two-phase metaheuristic approach to planning daily farm work for agriculture production corporations. The two-phase metaheuristic contains the optimization of resources assignment and searching schedule based on Genetic Algorithm and hybrid Petri nets model. In the experiment, the effect on optimizing the resource assignment and priority list, initializing population of GA...

We propose a new nature inspired metaheuristic approach based on the V flight formation of the migrating birds which is proven to be an effective formation in energy saving. Its performance is tested on quadratic assignment problem instances arising from a real life problem and very good results are obtained. The quality of the solutions we report are better than simulated annealing, tabu searc...

In recent years, several optimization methods especially metaheuristic optimization methods have been developed by scientists. People have utilized power of nature to solve problems. Therefore, those metaheuristic methods have imitated physical and biological processes of nature. In 2007, Big Bang Big Crunch optimization algorithm based on evolution of universe and in 2009, Gravitational Search...