• Proceedings of the Korea Information Processing Society Conference
• /
• 2015.10a
• /
• pp.1281-1284
• /
• 2015

Multi-day trip itinerary planning is complex and time consuming task, from selecting a list of worth visiting POIs to arranging them into an itinerary with various constraints and requirements. In this paper, we present CYTRIP, a multi-day trip itinerary planning system that engages human computation (i.e. crowd recommendation) to collaboratively recommend POIs by providing a shared workspace. CYTRIP takes input the collective intelligence of crowd (i.e. recommended POIs) to build a multi-day trip itinerary taking into account user's preferences, various time constraints and locations. Furthermore, we explain how we engage crowd in our system. The planning problem and domain are formulated as AI planning using PDDL3. The preliminary empirical experiments show that our domain formulation is applicable to both single-day and multi-day trip planning.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.774-777
• /
• 2019

지능형 서비스 로봇의 불확실한 작업 환경과 작업에 대한 요구사항의 증가는 작업 계획(task planning)의 어려움을 증가시킨다. 이러한 문제를 해결하기 위한 방법으로 PRS (Procedural Reasoning System)를 이용한 작업 계획이 제안되어 작업 환경의 동적 변화에는 효율적으로 대응할 수 있게 되었으나, 작업의 요구사항의 증가에 따른 하위 계획의 복잡성은 아직도 해결해야 할 문제로 남아 있다. 본 논문에서는 요구된 작업의 하위 목표(sub-goals)와 속성을 고려하여 계획 후보들의 예상 유용성을 계산할 수 있는 유틸리티 함수를 기반으로, 보다 간결한 방식의 작업 계획을 수립하는 방법을 제안한다. 또한 제안한 작업 계획의 적용 가능성을 확인하기 위하여 로봇 서비스 시나리오를 구성하고 실험을 통하여 그 유용성을 검증한다.

• Proceedings of the KIEE Conference
• /
• 2003.07a
• /
• pp.139-141
• /
• 2003

The outage cost has very important position for determination of the optimal level or optimal range of reliability in power system expansion planning. Establishing the worth of service reliability is a very difficult and subjective task. This paper addresses the role, need and assessment algorithm and methodology of the outage cost on power system expansion planning. Furthermore outage cost has been assessed using macro approach for our country 15years(1986-2001) in the case study.

• Proceedings of the KIEE Conference
• /
• 2003.11a
• /
• pp.479-483
• /
• 2003

The outage cost has very important position for determination of the optimal level or optimal range of reliability in power system expansion planning. Establishing the worth of service reliability is a very difficult and subjective task. This paper suggests strategies for the role, need and assessment algorithm and methodology of the outage cost in power system expansion planning. Organization, data collections and method about D/B for outage cost assessment is proposed in the this study.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.1
• /
• pp.274-283
• /
• 2016

The study of maintenance planning is important in military weapon systems because it can improve their availability and reduce the operational and maintenance cost during the total life cycle. In maintenance planning, it is important to determine the preventive maintenance task and its optimal interval. This paper focuses on the hard time task, which is one of the preventive maintenance tasks. A hard time task removes an item or restorative action before some specified maximum age limit to prevent functional failure. The Monte-Carlo simulation model was proposed to help understand the cost effectiveness of a hard time task. In the simulation, various shape parameters of the Weibull distribution and cost ratio of corrective maintenance to preventive maintenance were assumed. Using a Monte-Carlo simulation, a quantified cost saving effect and optimal preventive maintenance interval were suggested.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• autumn
• /
• pp.541-544
• /
• 2003

The Information System(IS) planning for construction project management must be performed through decomposing the construction management business process upon considering the information technology in a construction company. Following this background, this paper proposes a model for evaluating the expected value of IS planning for construction project management. The model is made to analyze the effectiveness and to evaluate the opportunity of IS planning for task and information, then finally to quantify the value. Lastly, this model can be used to plan IS for construction project management.

• The Journal of Korea Robotics Society
• /
• v.6 no.4
• /
• pp.344-352
• /
• 2011

A mobile manipulator is a system with a robotic manipulator mounted on top of a mobile base. It has both indoor and outdoor applications for transporting or transferring materials. When a user gives commands, they are usually at high levels such as "move the object to the table," or "tidy the room." By intelligently decomposing these complex commands into several subtasks, the mobile manipulator can perform the tasks with a greater efficiency. One of the crucial subtasks for these commands is the pick-and-place task. For the mobile manipulator, selection of a good base position and orientation is essential to accomplishing this task. This paper presents an algorithm that determines one of the position and orientation of a mobile manipulator in order to complete the pick-and-place task without human intervention. Its effectiveness are shown for a mobile manipulator with 9 degrees-of-freedom in simulation.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.24 no.4
• /
• pp.13-26
• /
• 1999

When we try to design a production planning system for a manufacturing company, it is a time consuming task to analyze various planning activities and identify inter-relationship among a lot of decisions made for the production planning. Most of the research efforts have been concentrated to well-organized independent decision-making problems that may usually be identified only after analyzing the characteristics of the decision-making process as a whole. In this paper, a methodology is suggested to characterize the whole process of the production planning for a manufacturing company and reduce the complexity of decision-making problems. The methodology is based on an experience of developing a production planning software for an automobile component manufacturer in korea. First, it is explained how to identify and represent the dependency among various decision-making variables. And a methodology is proposed to analyze the identified dependency among decision variables and identify decision-making process. Lastly, a practical example is provided to illustrate the analysis procedure in this paper.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.47-52
• /
• 2023

With the growing data size and the increased computing load in machine learning, energy-efficient resource planning in IoT systems is becoming increasingly important. In this paper, we suggest a new resource planning policy for real-time workloads that can be fluctuated over time in IoT systems. To handle such situations, we categorize real-time tasks into fixed tasks and variable tasks, and optimize the resource planning for various workload conditions. Based on this, we initiate the IoT system with the configuration for the fixed tasks, and when variable tasks are activated, we update the resource planning promptly for the situation. Simulation experiments show that the proposed policy saves the processor and memory energy significantly.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2014.05a
• /
• pp.4-5
• /
• 2014

Planning earthmoving haul-route must be preceded for appropriate equipment fleet assignment. However, traditional haul-route planning methods have limitations relative to practical usage because multiple variables (e.g., grade/rolling resistance, length, equipment's weight etc.) should be considered at a time. Genetic algorithm(GA) was introduced to improve these traditional methods. However, GA based haul-route planning method still remains in inefficiency relative to computation performance. This study presents a new haul-route searching method that computes an optimal haul-route using GA. The system prototype is developed by using MATLAB(ver. 2008b). The system identifies an optimal haul-route by considering equipment type, soil type, and soil condition.