• Coupled systems mechanics
• /
• v.13 no.3
• /
• pp.219-229
• /
• 2024

By introducing optimization algorithms into the machining process, product quality can be improved, time saved, and costs reduced. The cutting speed and feed can be handled by the turning machine. The approach of optimizing is used to manage pyrotechnics, Lawler's, greedy, bacterial colony, elephant herding, ant lion, spiral, auction, and pattern search for these ten odd ways. Ten artificial optimization methodologies were used to investigate the time and cost of a turning machine. It has been discovered how to create the optimal turning machine procedure. The best solution approach for the turning machine process problem is found, and the results are verified using ANSYS.

• Journal of Advanced Navigation Technology
• /
• v.18 no.1
• /
• pp.44-49
• /
• 2014

In recent, watermarking technology have been paying attention to methods avoiding illegal use and reproduce of digital contents. Then, in order to protect the right of digital contents, a watermark image is inserted into original images. In different watermarking methods, several technologies using Ant Colony Algorithm have been studied. In this paper, we propose a watermarking method using a discrete optimization method in the ants colony algorithm. This proposed method resembls the process that ants follow the pheromone traps to find out food. And when a watermark image is inserted into original images, the proposed method considers the deployment of obstacles or the balance between cells in the entire digital image. Simulation results show that the proposed method is increased in robustness of watermarked image and is decreased in the perceptibility of watermarking compared to the previous methods.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.1
• /
• pp.74-90
• /
• 2014

Routing in mobile wireless sensor networks (MWSNs) is an extremely challenging issue due to the features of MWSNs. In this paper, we present a novel bio-inspired trusted routing protocol (B-iTRP) based on artificial immune system (AIS), ant colony optimization (ACO) and Physarum optimization (PO). For trust mechanism, B-iTRP monitors neighbors' behavior in real time and then assesses neighbors' trusts based on AIS. For routing strategy, each node proactively finds routes to the Sink based on ACO. When a backward ant is on the way to return source, it senses the energy residual and trust value of each node on the discovered route, and calculates the link trust and link energy of the route. Moreover, B-iTRP also assesses the availability of route based on PO to maintain the route table. Simulation results show how B-iTRP can achieve the effective performance compared to existing state-of-the-art algorithms.

• The Journal of the Korea Contents Association
• /
• v.11 no.10
• /
• pp.41-48
• /
• 2011

In feature selection, the selective evaluation scheme for Ant Colony Optimization(ACO) has recently been proposed, which reduces computational load by excluding unnecessary or less promising candidate solutions from the actual evaluation. Its superiority was supported by experimental results. However the experiment seems to be not statistically sufficient since it used only one dataset. The aim of this paper is to analyze convergence characteristics of the selective evaluation scheme and to make the conclusion more convincing. We chose three datasets related to handwriting, medical, and speech domains from UCI repository whose feature set size ranges from 256 to 617. For each of them, we executed 12 independent runs in order to obtain statistically stable data. Each run was given 72 hours to observe the long-time convergence. Based on analysis of experimental data, we describe a reason for the superiority and where the scheme can be applied.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.4B
• /
• pp.346-353
• /
• 2011

Routing schemes that service applications with various delay times, maintaining the long network life time are required in wireless sensor & actor networks. However, it is known that network lifetime and hop count of trees used in routing methods have the tradeoff between them. In this paper, we propose a Pareto Ant Colony Optimization algorithm to find the Pareto tree set such that it optimizes these both tradeoff objectives. As it enables applications which have different delay times to select appropriate routing trees, not only satisfies the requirements of various multiple applications but also guarantees long network lifetime. We show that the Pareto tree set found by proposed algorithm consists of trees that are closer to the Pareto optimal points in terms of hop count and network lifetime than minimum spanning tree which is a representative routing tree.

• Journal of Navigation and Port Research
• /
• v.38 no.5
• /
• pp.493-501
• /
• 2014

An automated lifting vehicle(ALV) used in an automated container terminal is a type of unmanned vehicle that can self-lift a container as well as self-transport it to a destination. To operate a fleet of ALVs efficiently, one needs to be able to determine a minimum-time route to a given destination whenever an ALV is to start its transport job. To find a route free from any collision or deadlock, the occupation time of the ALV on each segment of the route should be carefully scheduled to avoid any such hazard. However, it is not easy because not only the travel times of ALVs are uncertain due to traffic condition but also the operation times of cranes en route are not predicted precisely. In this paper, we propose a routing method based on an ant colony optimization algorithm that takes into account these uncertainties. The result of simulation experiment shows that the proposed method can effectively find good routes under uncertainty.

• Journal of the Korean Society of Environmental Restoration Technology
• /
• v.22 no.2
• /
• pp.1-12
• /
• 2019

Open space planners and designers should consider scientific and quantified functions of trees when they have to locate where to plant the tree. However, until now, most planners and designers could not consider them because of lack of tool for considering scientific and quantitative tree functions. This study introduces a tree location supporting tool which focuses on the multi-objective including scientific function using ACO (Ant colony optimization). We choose shading effect (scientific function), shielding, and openness as objectives for test application. The results show that when the user give a high weight to a particular objective, they can obtain the optimal results with high value of that objective. When we allocate higher weight for the shading effect, the tree plans provide larger shadow value. Even when compared with current tree plan, the study result has a larger shading effect plan. This result will reduce incident radiation to the ground and make thermal friendly open space in the summer. If planners and designers utilize this tool and control the objectives, they would get diverse optimal tree plans and it will allow them to make use of the many environmental benefits from trees.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.20 no.3
• /
• pp.441-453
• /
• 2017

In this paper, a new type of weapon-target assignment(WTA) problem has been suggested that reflects realistic constraints for sharing target with other weapons and shooting double rapid fire. To utilize in rapidly changing actual battle field, the computation time is of great importance. Several metaheuristic methods such as Simulated Annealing, Tabu Search, Genetic Algorithm, Ant Colony Optimization, and Particle Swarm Optimization have been applied to the real-time WTA in order to find a near optimal solution. A case study with a large number of targets in consideration of the practical cases has been analyzed by the objective value of each algorithm.

• Structural Engineering and Mechanics
• /
• v.45 no.6
• /
• pp.723-740
• /
• 2013

This paper presents a parametric study of reinforced concrete bridge tall piers with hollow, rectangular sections. Such piers are typically used in railway construction of prestressed concrete viaducts. Twenty one different piers have been studied with seven column heights of 40, 50, 60, 70, 80, 90 and 100 m and three types of 10-span continuous viaducts, whose main span lengths are 40, 50 and 60 m. The piers studied are intermediate columns placed in the middle of the viaducts. The total number of optimization design variables varies from 139 for piers with column height of 40 m to 307 for piers with column height of 100 m. Further, the results presented are of much value for the preliminary design of the piers of prestressed concrete viaducts of high speed railway lines.

• Advances in Computational Design
• /
• v.2 no.4
• /
• pp.313-331
• /
• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.