Wongwirat, Olarn
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Wongwirat, Olarn
Alternative Name
Wongwirat, O.
Wongwirat, Olam
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olarn.wo@kmitl.ac.th
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Item type:Publication, A learning mechanism for adaptive fitness function in auto 3D graphics layout using genetic algorithm(2001-01-01); ; Burintramart, I.In computer-aided drafting and designing area, interactive graphics are used for designing components, systems, layouts, and structures. There are several approaches using for automated graphical layout tools in designing the graphic currently. Our research work aims to reduce design-working time, to learn user preferences, and to generate 3D graphical layout design automatically. An attempt to enable computers to generate 3D graphical layout design and presentation automatically by using Genetic Algorithm (GA) has been discussed for a decade. An effective use of GA in automated graphical layout design relies on how close to define a fitness function that can be reflected the user preferences. In this paper, we introduce the methods to define chromosome structures and fitness functions and of the selected objects. A learning mechanism is employed to adjust the fitness values of the objects in the selected layout choosing by the users. By this approach, the fitness functions can be changed adaptively reflecting the selection and user preferences. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An application of ant algorithm for searching energy-efficient route a mobile robot takes using energy as a weighting factor(2014-12-10); ; A problem related to energy consumption of a mobile robot involves finding out what route the robot can take that uses the least energy. An ant colony optimization algorithm (ACO) can solve this problem. However, it is applicable only for route on a flat terrain. This paper proposes an adapted ant colony optimization (adapted ACO) algorithm that is applicable for route on a rough terrain as well. This adaptation introduces a weight that is the energy expended on a route that may have upward slopes, downward slopes, and flat surfaces. Experiments were conducted to test the algorithm. The experimental results show that our adapted ACO did successfully find a route that expended the least energy, though it was not the shortest one. We also found the following interesting facts: an energy-efficient route has more downward slopes than upward ones; the energy expended increases with the steepness of the slopes along a route; and the energy expended is likely to be lower if the robot’s velocity is not constrained to be constant throughout the route. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Performance evaluation of compromised synchronization control mechanism for distributed virtual environment (DVE)(2005-12-01); Ohara, ShigeyukiSynchronization in a distributed virtual environment (DVE) involves mechanisms to ensure a consistent view of a virtual world for all participants. Most applications in the DVE are related to collaborative activities that include non-contention and contention cases. Using transmission of update messages is suitable enough to support synchronization for only non-contention activity. The contention activity requires an additional mechanism to control accessing a common object for synchronization. In this paper, we present the compromised synchronization control mechanism to support both non-contention and contention activities. The mechanism employs frequent update event and multiple-lock checking to control the synchronization. Frequent update event is used to support a dynamic virtual world for non-contention activity. Multiple-lock checking is embedded to ensure consistency when accessing the common object is required simultaneously for the contention event. Performance measurement of the compromised synchronization is provided by simulation in terms of locking time, sampling event, number of logical processes, and traffic tolerance. Prototype application is also implemented to compare the result in a small scale level. Based on the simulation and experimental results, the compromised sychronization control mechanism is capable to support up to 100 participants for the non-contention activity. It provides a good performance of supporting the contention activity in a small scale. The mechanism is considered suitable for collaborative application where contention is considered a critical event. © Springer-Verlag London Limited 2005. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Performance Measurement of Energy Optimal Path Finding for Waste Collection Robot Using ACO Algorithm(2022-01-01); ; ; Kuchii, ShigeruIndoor waste collection that utilizes mobile robots can solve the labor cost and manpower shortage but has the problem of limited energy resources, making it difficult to operate for long periods of time. Therefore, it is important to reduce the energy consumption for efficient waste collection. The waste collection robot can be modeled as a Capacitated Vehicle Routing Problem (CVRP), where heuristics algorithms can be deployed to search for the most energy-efficient path. This paper proposes the Ant Colony Optimization (ACO) algorithm for finding the optimal path of the waste collection robot. Energy consumption of the robot depends not only on the travel path but also on the weight of the waste it carries. Therefore, the proposed ACO algorithm utilizes the path distance and waste weight as the visibility. The travel distance and energy consumption are also used to determine the updated pheromone. Whereas the conventional and adapted ACO algorithms use only either the path distance or the waste weight as the visibility, respectively. The simulation experiments are conducted to compare the travel distance and the energy consumption that the waste collection robot takes by using the conventional, adapted, and proposed ACO algorithms. In the simulation experiments, the number of nodes, the waste weight, and the carrying capacity are used as parameters to verify the performance under the determined environment. The simulation results express that the proposed ACO algorithm provides a better energy optimal path in terms of travel distance and energy consumption than the conventional and adapted ACO algorithms.