Search Results - (( java implementation based algorithm ) OR ( solving problems ant algorithm ))

Ant colony optimization in dynamic environments by Chen, Fei Huang

“…In order to achieve this objective, six ant algorithms namely Ant System (AS), Ant Colony System (ACS), Best-Worst Ant System (BWAS), Elitist Ant System (EAS), Max-Min Ant System (MMAS) and Rank-Based Ant System (RBAS) were implemented to solve a dynamic optimization problem in the form of the dynamic Traveling Salesman Problem (TSP). …”
Get full text
Get full text
Get full text

Ant colony optimization algorithm for dynamic scheduling of jobs in computational grid by Ku-Mahamud, Ku Ruhana, Ramli, Razamin, Yusof, Yuhanis, Mohamed Din, Aniza, Mahmuddin, Massudi

“…In computational grid, job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem is classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Among different optimization algorithms for job scheduling, ant colony system algorithm is a popular meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This research focuses on a new heuristic function where information about recent ants’ discoveries has been considered.The new heuristic function has been integrated into the classical ant colony system algorithm.Furthermore, the enhanced algorithm has been implemented to solve the travelling salesman problem as well as in scheduling of jobs in computational grid.A simulator with dynamic environment feature to mimic real life application has been development to validate the proposed enhanced ant colony system algorithm. …”
Get full text
Get full text

Enhancement of Ant System Algorithm for Course Timetabling Problem by Djamarus, Djasli

“…As a member of the NP Problem, an exact algorithm to solve the course scheduling problem is not available to date. …”
Get full text
Get full text
Get full text

Ant Colony Optimization With Look Forward Ant In Solving Assembly Line Balancing Problem by Sulaiman, Mohd Nor Irman, Choo, Yun Huoy, Chong, Kuan Eng

“…An improved ant colony optimization with look forward ant is proposed to solve the simple assembly line balancing problem of type 1 (SALBP-1). …”
Get full text
Get full text
Get full text

A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…Classification rule induction is one of the problems solved by the Ant-miner algorithm, a variant of ACO, which was initiated by Parpinelli in 2001. …”
Get full text
Get full text
Get full text
Get full text

Application of ant colony optimisation algorithms in solving facility layout problems formulated as quadratic assignment problems: a review by See, Phen Chiak, Wong, Kuan Yew

“…This paper is aimed to provide a comprehensive review of the concepts of ACO and its application in solving QAPs. In addition, the various ACO algorithms or variants developed to solve them are critically analysed and discussed. …”
Get full text
Get full text

Modification of the ant colony optimization algorithm for solving multi-agent task allocation problem in agricultural application by Hardhienata, Medria Kusuma Dewi, Priandana, Karlisa, Putra, Daffa Rangga, Sriatun, Mamiek, Wulandari, Buono, Agus, Mohamed, Raihani

“…Simulation results showed that the proposed ACO algorithm with the modified efficiency factor improved the performance of basic ACO algorithm for solving task allocation problem in terms of the average total travel cost for each agent. …”
Get full text
Get full text
Get full text

A hybrid ant colony algorithm for solving facility layout problems formulated as quadratic assignment problems by See, Phen Chiak

Get full text

New heuristic function in ant colony system for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
Get full text
Get full text
Get full text

An Ant Colony Search Algorithm (ACSA) approach for unit commitment problem / Mohamad Masri Mohamad Jaib by Mohamad Jaib, Mohamad Masri

“…This thesis presents an Ant Colony Search Algorithm (ACSA) to solve unit commitment problem. …”
Get full text
Get full text

Comparison between ant colony and genetic algorithm using traveling salesman problem by Abduljabbar, Zaid Ammen, Khalefa, Mustafa S., A. Jabar, Marzanah

“…In ant colony algorithm each individual ant constructs a part of the solution using an artificial pheromone which reflects its experience accumulated while solving the problem and heuristic information dependent on the problem. …”
Get full text
Get full text
Get full text

Ant colony system with heuristic function for the travelling salesman problem by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Ant colony system which is classified as a meta-heuristic algorithm is considered as one of the best optimization algorithm for solving different type of NP-Hard problem including the travelling salesman problem.A heuristic function in the Ant colony system uses pheromone and distance values to produce heuristic values in solving the travelling salesman problem.However, the heuristic values are not updated in the entire process to reflect the knowledge discovered by ants while moving from city to city. …”
Get full text
Get full text
Get full text

New heuristic function in ant colony system for job scheduling in grid computing by Ku-Mahamud, Ku Ruhana, Alobaedy, Mustafa Muwafak

“…Job scheduling is one of the main factors affecting grid computing performance. Job scheduling problem classified as an NP-hard problem.Such a problem can be solved only by using approximate algorithms such as heuristic and meta-heuristic algorithms.Ant colony system algorithm is a meta-heuristic algorithm which has the ability to solve different types of NP-hard problems.However, ant colony system algorithm has a deficiency in its heuristic function which affects the algorithm behavior in terms of finding the shortest connection between edges.This paper focuses on enhancing the heuristic function where information about recent ants’ discoveries will be taken into account.Experiments were conducted using a simulator with dynamic environment features to mimic the grid environment.Results show that the proposed enhanced algorithm produce better output in term of utilization and make span.…”
Get full text
Get full text

An Ant Colony Search Algorithm (ACSA) approach for unit commitment problem: article / Mohamad Masri Mohamad Jaib by Mohamad Jaibt, Mohamad Masri

“…This thesis presents an Ant Colony Search Algorithm (ACSA) to solve unit commitment problem. …”
Get full text
Get full text

An Experiment of Ant Algorithms : Case Study of Kota Kinabalu Central Town by Nor Rafidah, Mohamad

“…Shortest path is one of the optimization problems that are difficult to solve. There are many algorithms that used to solve this problem. …”
Get full text
Get full text
Get full text

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
Get full text
Get full text
Get full text

Heuristic factors in ant system algorithm for course timetabling problem by Djamarus, Djasli, Ku-Mahamud, Ku Ruhana

“…This paper presents an algorithm that is based on ant system to solve the course timetabling problem.The problem is modeled using the bipartite graph.Four heuristic factors are derived from the graph characteristic, are used to direct ants as the agent in finding course timetable elements The concept of negative pheromone was also applied to ensure that paths leading to dead ends are not chosen.The performance of this proposed algorithm is promising when comparison of performance was made with the original ant system algorithm. …”
Get full text
Get full text

Scheduling jobs in computational grid using hybrid ACS and GA approach by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

“…Metaheuristics algorithms show very good performance in solving various job scheduling problems in computational grid systems.However, due to the complexity and heterogeneous nature of resources in grid computing, stand-alone algorithm is not capable to find a good quality solution in reasonable time.This study proposes a hybrid algorithm, specifically ant colony system and genetic algorithm to solve the job scheduling problem.The high level hybridization algorithm will keep the identity of each algorithm in performing the scheduling task.The study focuses on static grid computing environment and the metrics for optimization are the makespan and flowtime.Experiment results show that the proposed algorithm outperforms other stand-alone algorithms such as ant system, genetic algorithms, and ant colony system for makespan.However, for flowtime, ant system and genetic algorithm perform better.…”
Get full text
Get full text
Get full text

Solving economic dispatch using ant colony optimization (ACO) / Nur Hazima Faezaa Ismail by Ismail, Nur Hazima Faezaa

“…Ant Colony Optimization (ACO) is a meta-heuristic approach for solving hard combinatorial optimization problems. …”
Get full text
Get full text

Application of Moth-Flame Optimizer and Ant Lion Optimizer to Solve Optimal Reactive Power Dispatch Problems by Rebecca Ng, Shin Mei, M. H., Sulaiman, Hamdan, Daniyal, Zuriani, Mustaffa

“…This paper presents the application of two nature-inspired meta-heuristic algorithms, namely moth-flame optimizer (MFO) and ant lion optimizer (ALO) in obtaining the optimal settings of control variables for solving optimal reactive power dispatch (ORPD) problems. …”
Get full text