Search Results - (( using factor (problems OR problem) algorithm ) OR ( evolution optimisation based algorithm ))

Optimal placement, sizing and power factor of distributed generation: A comprehensive study spanning from the planning stage to the operation stage by Huy P.D., Ramachandaramurthy V.K., Yong J.Y., Tan K.M., Ekanayake J.B.

Performance evaluation and benchmarking of an extended computational model of ant colony system for DNA sequence design by Zuwairie, Ibrahim, Mohd Falfazli, Mat Jusof, Mohd Zaidi, Mohd Tumari

“…Ant colony system (ACS) algorithm is one of the biologically inspired algorithms that have been introduced to effectively solve a variety of combinatorial optimisation problems. …”
Get full text
Get full text
Get full text

A competitive co-evolutionary approach for the nurse scheduling problem by Mohamad Nazri, Maizatul Farhana, Mohd Yusoh, Zeratul Izzah, Basiron, Halizah, Daud, Azlina

“…The competitive approach further exhibits smoother convergence behaviour across generations, indicating stronger optimisation dynamics and improved robustness. These findings demonstrate that competitive co-evolution provides an effective and practical alternative to static fitness-based evolutionary methods for nurse scheduling, with broader applicability to healthcare scheduling and constraint optimisation problems.…”
Get full text
Get full text
Get full text

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

“…As the requirement of the Ant System Algorithm, the problem is modeled as a graph that can be used by the ant to deliver its pheromone. …”
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

A new cryptographic algorithm based on decomposition problem in elliptic curve cryptography / Hilyati Hanina Zazali by Hilyati Hanina, Zazali

“…Since subexponential-time algorithm is known for ordinary discrete logarithm problem and integer factorization problem and not for elliptic curve discrete logarithm problem, the algorithm presented for the digital signature in this study has substantially greater strength per key bit than in other digital signature algorithm…”
Get full text
Get full text
Get full text
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

Factors and types of error that contributes to the difficulties in solving Mathematical problems among Year 5 pupils in SK Goebilt, Kuching / Hardi Rasidi by Rasidi, Hardi

“…The objectives of this research are to identify the factors and types of algorithm error that contributes to difficulties in solving mathematical word problems. …”
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, Fakhrud Din, Shah Khalid, Kamal Zuhairi Zamli, Aftab Alam

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
Get full text
Get full text
Get full text

Multi-objective constrained algorithm (MCA) and non-dominated sorting genetic algorithm (NSGA-ii) for solving multi-objective crop planning problem by Jarin, Sams, Khatun, Mst Khaleda, Shafie, Amir Akramin

“…In this paper, we formulate a crop planning problem as a multiobjective optimization model and try to solve two different versions of the problem using two different optimization algorithms MCA and NSGA. …”
Get full text
Get full text
Get full text
Get full text

Three-term backpropagation algorithm for classification problem by Saman, Fadhlina Izzah

“…Standard Backpropagation Algorithm (BP) is a widely used algorithm in training Neural Network that is proven to be very successful in many diverse application. …”
Get full text
Get full text

Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

“…Finally, two novel hybrid optimization algorithms namely, FLP-QOJaya algorithm for single objective OPF problems and MFLP-QOMJaya algorithm for MOOPF problems are proposed. …”
Get full text
Get full text

Tiki-taka algorithm: a novel metaheuristic inspired by football playing style by Mohd Fadzil Faisae, Ab Rashid

“…The algorithm was tested using 19 benchmark functions and five engineering design problems. …”
Get full text
Get full text
Get full text

A hyper-heuristic based strategy for image segmentation using multilevel thresholding by Luqman, ., Fakhrud, Din, Shah, Khalid, Kamal Z., Zamli, Alam, Aftab

“…EMCQ uses four low-level heuristic sets adopted from the teaching learning-based optimisation (TLBO) algorithm, flower pollination algorithm (FPA), genetic algorithm (GA), and Jaya algorithm. …”
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

Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems by Waqas Haider Bangyal, Kashif Nisar, Ag. Asri Bin Ag. Ibrahim, Muhammad Reazul Haque, Joel J. P. C. Rodrigues, Danda B. Rawat

“…Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. …”
Get full text
Get full text
Get full text
Get full text
Get full text

An alternative method to solve combined economic emission dispatch problems using flower pollination algorithm by Hong, Mee Song

“…To simplify the programming, objective of economic dispatch (ED) and emission dispatch (EmD) are combined into a single function by price penalty factor and analysed using weighted sum method to choose the best compromising result. …”
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

Parallel metaheuristic algorithm for route planning using CUDA by Looi, Daniel Jun Jie

“…Area of Study: Massively Parallel Computing, Combinatorial Optimization Keywords: Parallel Metaheuristic Algorithm, Travelling Salesman Problem, CUDA, GPU, Genetic Algorithm…”
Get full text
Get full text

Methodology to develop heuristic for re-entrant flow shop with two potential dominant machines using bottleneck approach by Bareduan, Salleh Ahmad, Hasan, Sulaiman

“…Each algorithm has specific correction factor which was used to ensure the accuracy of the makespan computation. …”
Get full text
Get full text