• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.6 s.312
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• pp.1-8
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done recently. Informations from various sensors can be used to find obstacles and plan feasible path. In spite of many solutions of finding optimal path, each can be applied in only a constrained condition. This means that it is difficult to find university good algorithm. An optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose an algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers and cumulative numbers. It has an advantage of fast planning time and completeness of path if one exists. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in dynamic environments. Using the information of the start and destination position, the RAS can be performed for collision-free navigation by reforming feasible paths repeatedly in dynamic environments.

• Journal of Electrical Engineering and Technology
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• v.4 no.1
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• pp.55-65
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• 2009

Due to the rapid increase of electricity demand, consideration of environmental constraints in optimal power flow (OPF) problems is increasingly important. In Algeria, up to 90% of electricity is produced by thermal generators (vapor, gas). In order to keep the emission of gaseous pollutants like sulfur dioxide (SO2) and Nitrogen (NO2) under the admissible ecological limits, many conventional and global optimization methods have been proposed to study the trade-off relation between fuel cost and emissions. This paper presents an efficient decomposed Parallel GA to solve the multi-objective environmental/economic dispatch problem. At the decomposed stage the length of the original chromosome is reduced successively and adapted to the topology of the new partition. Two subproblems are proposed: the first subproblem is related to the active power planning to minimize the total fuel cost, and the second subproblem is a reactive power planning design based in practical rules to make fine corrections to the voltage deviation and reactive power violation using a specified number of shunt dynamic compensators named Static Var Compensators (SVC). To validate the robustness of the proposed approach, the algorithm proposed was tested on the Algerian 59-bus network test and compared with conventional methods and with global optimization methods (GA, FGA, and ACO). The results show that the approach proposed can converge to the near solution and obtain a competitive solution at a critical situation and within a reasonable time.

• ETRI Journal
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• v.40 no.4
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• pp.471-482
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• 2018

This paper proposes the necessity of a walking period in footstep planning and details situations in which it should be considered. An optimization-based fast footstep planner that takes the walking period into consideration is also presented. This footstep planner comprises three stages. A binary search is first used to determine the walking period. The front stride, side stride, and walking direction are then determined using the modified rapidly-exploring random tree algorithm. Finally, particle swarm optimization (PSO) is performed to ensure feasibility without departing significantly from the results determined in the two stages. The parameters determined in the previous two stages are optimized together through the PSO. Fast footstep planning is essential for coping with dynamic obstacle environments; however, optimization techniques may require a large computation time. The two stages play an important role in limiting the search space in the PSO. This framework enables fast footstep planning without compromising on the benefits of a continuous optimization approach.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.479-486
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• 2021

This study aims to explore the relationships between strategic planning, strategic maneuverability, and firm performance in the current dynamic business environment. It employs a quantitative research method and reports on a survey, using a questionnaire, of service companies in Indonesia's oil and gas industry. Of the 337 companies selected by simple random sampling from a vendor database, responses were received from 70 companies. The analysis was performed using Partial Least Square Structural Equation Modeling and SmartPLS software. The analysis consisted of descriptive statistics, evaluation of the measurement model, evaluation of the structural model, and hypotheses testing. The results show that both strategic planning and strategic maneuverability have a positive relationship with firm performance. In addition, there is a positive relationship between strategic planning and firm performance through the mediating role of strategic maneuverability. The findings suggest that the organizational agility, organizational flexibility, and organizational responsiveness that constitute strategic maneuverability have a positive direct and indirect effect on firm performance, namely financial performance, customer performance, internal process performance, and learning and growth. This study contributes to the strategic management literature and the theory of maneuvers by providing empirical evidence on the relationship between strategic planning, strategic maneuverability, and firm performance.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.8-19
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• 2023

This paper presents advancement in multi- unmanned aerial vehicle (UAV) cooperative area surveillance, focusing on optimizing UAV route planning through the application of genetic algorithms. Addressing the complexities of comprehensive coverage, two real-time dynamic path planning methods are introduced, leveraging genetic algorithms to enhance surveillance efficiency while accounting for flight constraints. These methodologies adapt multi-UAV routes by encoding turning angles and employing coverage-driven fitness functions, facilitating real-time monitoring optimization. The paper introduces a novel path planning model for scenarios where UAVs navigate collaboratively without predetermined destinations during regional surveillance. Empirical evaluations confirm the effectiveness of the proposed methods, showcasing improved coverage and heightened efficiency in multi-UAV path planning. Furthermore, we introduce innovative optimization strategies, (Foresightedness and Multi-step) offering distinct trade-offs between solution quality and computational time. This research contributes innovative solutions to the intricate challenges of cooperative area surveillance, showcasing the transformative potential of genetic algorithms in multi-UAV technology. By enabling smarter route planning, these methods underscore the feasibility of more efficient, adaptable, and intelligent cooperative surveillance missions.

• Progress in Medical Physics
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• v.34 no.4
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• pp.41-47
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• 2023

Purpose: This study aimed to dosimetrically compare the technique of three-dimensional conformal radiotherapy (3D CRT), which is a traditional prophylactic cranial irradiation method, and the intensity-modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) techniques used in the last few decades with the dynamic conformal arc therapy (DCAT) technique. Methods: The 3D CRT, VMAT, IMRT, and DCAT plans were prepared with 25 Gy in 10 fractions in a Monaco planning system. The target volume and the critical organ doses were compared. A comparison of the body V₂, V₅, and V₁₀ doses, monitor unit (MU), and beam on-time values was also performed. Results: In planned target volume of the brain (PTV_Brain), the highest D99 dose value (P<0.001) and the most homogeneous (P=0.049) dose distribution according to the heterogeneity index were obtained using the VMAT technique. In contrast, the lowest values were obtained using the 3D CRT technique in the body V₂, V₅, and V₁₀ doses. The MU values were the lowest when DCAT (P=0.001) was used. These values were 0.34% (P=0.256) lower with the 3D CRT technique, 66% (P=0.001) lower with IMRT, and 72% (P=0.001) lower with VMAT. The beam on-time values were the lowest with the 3D CRT planning (P<0.001), 3.8% (P=0.008) lower than DCAT, 65% (P=0.001) lower than VMAT planning, and 76% (P=0.001) lower than IMRT planning. Conclusions: Without sacrificing the homogeneous dose distribution and the critical organ doses in IMRTs, three to four times less treatment time, less low-dose volume, less leakage radiation, and less radiation scattering could be achieved when the DCAT technique is used similar to conventional methods. In short, DCAT, which is applicable in small target volumes, can also be successfully planned in large target volumes, such as the whole-brain.

• Progress in Medical Physics
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• v.17 no.2
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• pp.114-122
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• 2006

The two commonly used methods in delivering intensity modulated radiation therapy (IMRT) plan are the dynamic (sliding window) and static (stop and shoot) mode. In this study, the two IMRI delivery techniques are compared by measuring point dose and dose distributions. Using treatment planning system, clinical target volume (CTV) was created as a sphere with various diameter (3 cm, 7 cm, 12 cm). Two IMRT plans were peformed to deliver 200 cGy to the CTV in dynamic and static mode. The two plans were delivered on a phantom and central point dose and dose distributions were measured. The central point dose differences between static and dynamic IMRT delivery were 0.2%, 0.2% and 0.4% when the diameter of CTV was 3 cm, 7 cm, and 12 cm, respectively. The differences In volume receiving 90% of the proscribed dose were 2.7%, 2.2%, and 2.9% for the diameter of CTV was 3 cm, 7 cm, and 12 cm, respectively. For lung cancer patients, the differences in central point dose were 0.2%, 0.2%, and 0.4% when the volume of CTV was 35.5 cc, 296.8 cc, and 903.5 cc, respectively. The differences in volume receiving 90% of the prescribed dose were 2.7%, 4.8%, and 9.1% when the volume of CTV was 35.5 cc, 296.8 cc, and 903.5 cc, respectively. In conclusion, it was possible to deliver IMRT plans using dynamic mode of MLC operation although the loaves are In motion during radiation delivery.

• Journal of Korean Society for Quality Management
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• v.14 no.1
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• pp.61-66
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• 1986

Many papers have suggested various models how to decide an optimal time for replacing equipment. In this study, Dynamic Programming is applied to establish a model of replacing equipment and a new algorithm is developed for computerization to meet the increased number of variables. It is possible to predict the real situation with higher accuracy by employing the proposed model including more variables such as planning horizon, original cost, salvage value, decreasing rate, operating and maintenance costs, increasing rate, and so on.

• 대한방사선방어학회:학술대회논문집
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• 2011.04a
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• pp.80-81
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• 2011

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.1
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• pp.27-36
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• 1990

This study deals with the dynamic transportation-inventory model for a single product from which the optimal procurement quantities and the transportation modes are determined simultaneously over a finite planning horizon. Moreover, it covers the situation where quantity discounts are applied to the transportation cost as well as the purchase cost and disposals of the excess are possible at the end of each period. For a relevant mathematical model formulated, the theorems and properties of an optimal solution are discussed to present the efficient algorithm. A numerical example is solved to illustrate the algorithm developed.