Related papers: Accelerating the ANT Colony Optimization By Smart …
Mutation is one of the most important stages of the genetic algorithm because of its impact on the exploration of global optima, and to overcome premature convergence. There are many types of mutation, and the problem lies in selection of…
Genetic Algorithms (GAs) are used to solve search and optimization problems in which an optimal solution can be found using an iterative process with probabilistic and non-deterministic transitions. However, depending on the problem's…
The aim of this paper is to introduce AHCOA to the electromagnetic and antenna community. AHCOA is a new nature inspired meta heuristic algorithm inspired by how there is a hierarchy and departments in the ant hill colonization. It has high…
An automated sizing approach for analog circuits using evolutionary algorithms is presented in this paper. A targeted search of the search space has been implemented using a particle generation function and a repair-bounds function that has…
The issue of optimizing queries is a cost-sensitive process and with respect to the number of associated tables in a query, its number of permutations grows exponentially. On one hand, in comparison with other operators in relational…
This Paper will deal with a combination of Ant Colony and Genetic Programming Algorithm to optimize Travelling Salesmen problem (NP-Hard). However, the complexity of the algorithm requires considerable computational time and resources.…
The Multi-Depot Vehicle Routing Problem (MDVRP) is a real-world model of the simplistic Vehicle Routing Problem (VRP) that considers how to satisfy multiple customer demands from numerous depots. This paper introduces a hybrid 2-stage…
Reinforcement Learning (RL) has demonstrated significant potential in certain real-world industrial applications, yet its broader deployment remains limited by inherent challenges such as sample inefficiency and unstable learning dynamics.…
In spite of the growing computational power offered by the commodity hardware, fast pump scheduling of complex water distribution systems is still a challenge. In this paper, the Artificial Neural Network (ANN) meta-modeling technique has…
Ant-based algorithms are successful tools for solving complex problems. One of these problems is the Linear Ordering Problem (LOP). The paper shows new results on some LOP instances, using Ant Colony System (ACS) and the Step-Back Sensitive…
In order to perceive the behavior presented by the multiphase chemical reactors, the ant colony optimization algorithm was combined with computational fluid dynamics (CFD) data. This intelligent algorithm creates a probabilistic technique…
The hydrophobic-polar (HP) model has been widely studied in the field of protein structure prediction (PSP) both for theoretical purposes and as a benchmark for new optimization strategies. In this work we introduce a new heuristics based…
Colonies of ants can collectively choose the best of several nests, even when many of the active ants who organize the move visit only one site. Understanding such a behavior can help us design efficient distributed decision making…
We return to the geometry optimization problem of Lennard-Jones clusters to analyze the performance dependence of "cut and splice" genetic algorithms (GAs) on the employed population size. We generally find that admixing twinning mutation…
The rapid e-commerce growth has made both business community and customers face a new situation. Due to intense competition on one hand and the customer's option to choose from several alternatives business community has realized the…
The design of spacecraft trajectories for missions visiting multiple celestial bodies is here framed as a multi-objective bilevel optimization problem. A comparative study is performed to assess the performance of different Beam Search…
The performance of GA is measured and analyzed in terms of its performance parameters against variations in its genetic operators and associated parameters. Since last four decades huge numbers of researchers have been working on the…
Metaheuristic algorithms are widely used for solving complex problems due to their ability to provide near-optimal solutions. But the execution time of these algorithms increases with the problem size and/or solution space. And, to get more…
Threat assessment is an important part of level 3 data fusion. Here we study a subproblem of this, worst-case risk assessment. Inspired by agent-based models used for simulation of trail formation for urban planning, we use ant colony…
In this paper, we have to concentrate on implementation of Weighted Clustering Algorithm with the help of Genetic Algorithm (GA).Here we have developed new algorithm for the implementation of GA-based approach with the help of Weighted…