• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.27-34
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• 2017

Highly informative admissible heuristics can help to conduct more efficient search for optimal solutions. However, in general, more informative ones of heuristics from planning problems requires lots of computational effort. To address this problem, we propose an Delete Relaxation based Action Costs-based Planning Graph(ACPG) and Action Costs-based Heuristics for solving optimal planning problems more efficiently. The ACPG is an extended one to be applied to can find action costs between subgoal & goal conditions from the Relaxed Planning Graph(RPG) which is a common means to get heuristics for solving the planning problems, Action Costs-based Heuristics utilizing ACPG can find action costs difference between subgoal & goal conditions in an effective way, and then consider them to estimate the goal distance. In this paper, we present the heuristics algorithm to compute Action Costs-based Heuristics, and then explain experimental analysis to investigate the efficiency and the accuracy of the Action Costs-based Heuristics.

• IE interfaces
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• v.18 no.3
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• pp.350-360
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• 2005

This paper considers a strategy for planning of rework in semiconductor monitoring burn-in test process. The equipment error in monitoring burn-in test process generates many defects. These defects are transformed into good products by rework process, i.e. retest. Rework has the advantage of saving production costs. But rework increases holding costs and incurs rework costs. In monitoring burn-in test process, rework depends on operator's experience with no pre-defined specification. In practice, a number of rework activities are performed with respect to the product importance and inventory quantity. Moreover, disregard for order jobs schedule have caused due date penalties. So a strategy for planning of rework by which order jobs schedule are not affected is suggested. Futhermore, production costs, rework costs and inventory costs for planning of rework are considered.

• Journal of KIBIM
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• v.13 no.4
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• pp.106-114
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• 2023

In this study, we developed a method to quantify urban social costs using mobile sensing data, providing a novel approach to urban planning. By collecting and analyzing extensive mobile data over time, we transformed travel patterns into measurable social costs. Our findings highlight the effectiveness of big data in urban planning, revealing key correlations between transportation modes and their associated social costs. This research not only advances the use of mobile data in urban planning but also suggests new directions for future studies to enhance data collection and analysis methods.

• Journal of KIBIM
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• v.6 no.2
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• pp.19-28
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• 2016

Social costs analysis seeks to reveal the environmental effects of transportation policy. It delivers a sense of the effects of the public's daily travel and the costs that are or would be incurred from individual trips. Moreover, the accumulated total number of trips will uncover the effects of travel on society. This article shows the quantitative analysis of the economic outcomes of travel using social costs estimation methods. In order to support urban planning tasks, this research implemented analysis tool for social costs estimation by travel behavior. For a case study, a jave based application which can convert people's trip data into social costs is developed. the application used for simulating student-housing effects by estimating social costs changes. The analysis included the attributes, building scale and locational changes of the student housing as well as transforms of the students' trips.

• Journal of Electrical Engineering and Technology
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• v.5 no.1
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• pp.21-27
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• 2010

This paper examines the long-run social welfare maximization problems facing public utilities, which includes consideration of the cost of capital or other fixed costs of production, from which it derives optimal investment decisions in a reliability differentiated pricing based market. Reliability differentiated pricing policies lead to straightforward mathematical results on optimal investment decisions in generation and transmission expansion planning. This paper presents the mathematical conditions for optimal investment decisions.

• The Journal of Asian Finance, Economics and Business
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• v.10 no.2
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• pp.267-280
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• 2023

The relationship between the state and taxation starts from the establishment of the state. The most important element is the concept of "tax compliance". Tax compliance can be considered as the harmony of state-society relations. However, the concept of tax non-compliance occurs when taxpayers do not fulfill their tax-related tasks as required. Tax noncompliance is just one of the costs that occur in tax systems, and is named "tax compliance cost" in the literature. This study focuses on tax compliance costs because tax compliance costs are the ones taxpayers are personally obliged to deal with. For this purpose, the study investigates costs accruing from tax systems, including efficiency, planning, application, and compliance costs. According to the analysis results, it was concluded that the main reason for fraud in the tax systems is high compliance costs and that tax compliance directly impacts social wealth. Besides, the existence of conditions conducive to tax evasion and tax avoidance in a country, short-term tax policies, belief in the unfairness and inequality of tax systems, inadequacy of audits conducted by tax authorities, insufficiency of pressure and deterrence mechanisms, constantly changing legislation, and the attitudes and perceptions regarding the illegitimacy of the government determine tax compliance.

• Transactions on Electrical and Electronic Materials
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• v.18 no.2
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• pp.111-118
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• 2017

The increased diversity of different types of energy sources requires moving towards smart distribution networks. This paper proposes a probabilistic DG (distributed generation) units planning model to determine technology type, capacity and location of DG units while simultaneously allocating ESS (energy storage systems) based on pre-determined capacities. This problem is studied in a wind integrated power system considering loads, prices and wind power generation uncertainties. A suitable method for DG unit planning will reduce costs and improve reliability concerns. Objective function is a cost function that minimizes DG investment and operational cost, purchased energy costs from upstream networks, the defined cost to reliability index, energy losses and the investment and degradation costs of ESS. Electrical load is a time variable and the model simulates a typical radial network successfully. The proposed model was solved using the DICOPT solver under GAMS optimization software.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.1-18
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• 1993

The family disaggregation model of hierarchical production planning (HPP) is the problem of (0 -1) mixed integer programming that minimizes the total sum of setup costs and inventory holding costs over the planning horizon. This problem is hard in a practical sense since optimal solution algorithms have failed to solve it within reasonable computation times. Thus effective familoy disaggregation algorithm should be developed for HPP. The family disaggregation algorithm developed in this paper consists of the first stage of finding initial solutions and the second stage of improving initial solutions. Some experimental results are given to verify the effectiveness of developed disaggregation algorithm.

• The Journal of Society for e-Business Studies
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• v.7 no.2
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• pp.143-156
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• 2002

The objective of supply chain planning is to satisfy the requirements for minimizing inventory costs, transportation costs, and lead times throughout the supply, production and distribution stage dispersed geographically. Therefore, the supply chain planning system should have functionalities to resolve complex optimization problems that have characteristics of multi-stage and multi-product. Ant the system should also support collaborative decision making among distributed business partners. In this study, we proposed a distributed architecture for the supply chain planning system. To do this, we analyzed functional requirements by using IDEF-0(ICAM Definition-0) methodology, defined required components, and designed each component by using object-oriented methodology. We implemented a prototype system based on CORBA (Common Object Request Broker Architecture) to show that the proposed distributed architecture based on component technology is feasible and can solve supply chain planning problem collaboratively.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.11
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• pp.2136-2141
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• 2009

Transmission planning is an important part of power system planning to meet an increasing demand for electricity. The objective of transmission expansion is to minimize operational and construction costs subject to system constraints. There is inherent uncertainty in transmission planning due to errors in forecasted demand and fuel costs. Therefore, transmission planning process is not reliable if the uncertainty is not taken into account. The paper presents a systematic method to find the optimal location and amount of transmission expansion using Cross-Entropy (CE) incorporating uncertainties about future power system conditions. Numerical results are presented to demonstrate the performance of the proposed method.