• International conference on construction engineering and project management
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• 2009.05a
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• pp.676-684
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• 2009

Decision making at the early stages of a construction project has a significant impact on the project, and various scenarios created based on the owner's requirements should be considered for the decision making. At the early stages of a construction project, the information regarding the project is usually limited and uncertain. As such, it is difficult to plan and manage the project (especially cost planning). Thus, in this study, a cost model that could be varied according to the owner's requirements was developed. The cost model that was developed in this study is based on the case-based reasoning (CBR) methodology. The model suggests cost estimation with the most similar historical case as a basis for the estimation. In this study, the optimization process was also conducted, using genetic algorithms that reflect the changes in the number of project characteristics and in the database in the model according to the owner's decision making. Two optimization parameters were established: (1) the minimum criteria for scoring attribute similarity (MCAS); and (2) the range of attribute weights (RAW). The cost model proposed in this study can help building owners and managers estimate the project budget at the business planning stage.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2004.11a
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• pp.515-520
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• 2004

Manufacturing Production System (MPS) has been widely accepted in construction area for the productivity improvement. However, the MPS does not always provide cost and time saving. It often caused more delays and increased project cost. Therefore the use of the MPS technique, systematic decision-making process is needed by reviewing various project parameters such as cost and time. This study includes extensive literature reviews and case studies on MPS. As a result, a decision-making model is proposed. The decision-making flowchart and decision-making model are developed in three steps: (1) identification and categorization of decision-making factors; (2) calculations of benefits, cost, and duration in accordance with the location and the production capacity of the factory; (3) comparisons of MPS and on-site assembly by varying the locations and sizes of the factory

• Journal of the Korea Safety Management & Science
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• v.11 no.2
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• pp.153-158
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• 2009

An optimal selection problem of SCM system is one of the critical issues for the company's competitiveness and performance under global economy. This paper presents a hierarchy model consisted of characteristic factors for introducing SCM system and an AHP (Analytic Hierarchy Process) based decision-making model for SCM system evaluation and selection. The proposed model can systematically construct the objectives of SCM system selection to meet the business goals. This paper focuses on selecting an optimal SCM system considering both all decision factors and sub-decision factors of a hierarchy model. Especially, the benefit/cost analysis is applied to choose SCM system. A case study shows the feasibility of the proposed model and the model can help a company to make better decision-making in the SCM system selection problem.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.111-125
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• 2011

Smartphone is becoming as a core device of mobile environment. The purpose of this study is to investigate the factors affecting customer's buying decision on smartphone. Based on prior studies and cases, this study identifies network effect, switching cost, function, design, brand, after service, price as affecting factors of customer's buying decision on smartphone. It also aims to investigate the relationship between network effect/switching cost and re-purchasing. Result shows that network effect brand, after service are significantly related to customer's buying decision on smartphone by device types, but switching cost, function, design, price are not. Network effect also was found to be significantly related to the re-purchasing. The result of this study may provide a guideline of supply strategy with smartphone suppliers.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.642-652
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• 2007

Many contracting firms and project managers in the construction industry have started to utilize multi objective optimization methods to handle multiple conflicting goals for completing the project within the stipulated time and budget with required quality and safety. These optimization methods have increased the pressure on decision makers to search for an optimal resources utilization plan that optimizes simultaneously the total project cost, completion time, and crashing cost by considering indirect cost, contractual penalty cost etc., practically charging them in terms of direct cost of the project which is fuzzy in nature. This paper presents a multiple fuzzy goal programming model (MFGP) that supports decision makers in performing the challenging task. The model incorporates the fuzziness which stems from the imprecise aspiration levels attained by the decision maker to these objectives that are quantified through fuzzy linear membership function. The membership values of these objectives are then maximized which forms the fuzzy decision. The problem is solved using LINGO 8 optimization solver and the best compromise solution is identified. Comparison between solutions of MFGP, fuzzy multi objective linear programming (FMOLP) and multiple goal programming (MGP) are also presented. Additionally, an interactive decision making process is developed to enable the decision maker to interact with the system in modifying the fuzzy data and model parameters until a satisfactory solution is obtained. A case study is considered to demonstrate the feasibility of the proposed model for optimization of project network parameters in the construction industry.

• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.91-99
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• 2011

Bayesian network is a form of probabilistic graphical model. It incorporates human reasoning to deal with sparse data availability and to determine the probabilities of uncertain cases. In this research, bayesian network is adopted to model the problem of construction project cost. General information, time, cost, and material, the four main factors dominating the characteristic of construction costs, are incorporated into the model. This research presents verify a model that were conducted to illustrate the functionality and application of a decision support system for predicting the costs. The Markov Chain Monte Carlo (MCMC) method is applied to estimate parameter distributions. Furthermore, it is shown that not all the parameters are normally distributed. In addition, cost estimates based on the Gibbs output is performed. It can enhance the decision the decision-making process.

• Korean Management Science Review
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• v.34 no.1
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• pp.1-13
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• 2017

The percentage of 3PL (Third-party Logistics), which uses third party businesses to outsource elements of the company's distribution and fulfillment services, is increasing steadily. To provide 3PL service to the customers, it is needed to estimate the total transportation cost and propose the unit cost to the customers. In this paper, we develop a decision support system for estimation of transportation cost of 3PL provider considering various transportation services, such as direct transportation, multi point visiting transportation, and cross docking. The system supports route planning of vehicles by using algorithms based on tabu search and dynamic programming.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.14 no.2
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• pp.134-142
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• 2002

LCC (Life-Cycle Cost) analysis is a practical method and a guideline for evalua-ting the economic performance of building service systems. By using the LCC analysis, the most cost-effective design decision can be made, which has the lowest LCC during the project study period among the various design alternatives. The present case shows an example of appro-priate use of the LCC analysis, by demonstrating the procedures of decision making among at-tarnative building HVAC systems at community center and congress hall of a local government.

• The Journal of Fisheries Business Administration
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• v.45 no.2
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• pp.85-95
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• 2014

Fish stocking is important element of land-based aquaculture management. To maintain constant stocking rate considering biological and economic condition is a convenient strategy in intensive aquaculture. This study is aimed to analyze the effect of over-stocking(more than aquaculture capacity) for certain periods of time. This study make the mathematical decision making model that finds the value of decision variable to minimize cost that sums up the water pool usage cost and sorting cost under critical standing corp constraint. The proposed mathematical decision making model was applied to 12 sample combination of sorting cost and the number of fish on the Oliver flounder culture farms. If a immature fish can be sold for high price than farming cost, restricted over-stocking resulted in a improvement of economic performance. When extensive comparable biological and market data become available, analysis model can be widely applied to yield more accurate results.

• Korean Journal of Hydrosciences
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• v.8
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• pp.31-40
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• 1997

Flow carrying capacity of water distribution systems is getting reduced by deterioration of pipes in the systems. The objective of this paper is to present a managerial decision-making model for the rehabilitation of water distribution systems with a mininum cost. The decisions made by the model also satisfy the requirements for discharge and pressure at demanding nodes in the systems. Replacement cost, pipe break repair cost, and pumping cost are considered in the economic evaluation of the decision along with the break rate and the interest rate to determine the optimal replacement time for each pipe. Then, the hydraulic integrity of the water distribution system is checked for the decision by a pipe network simulator, KYPIPE, if discharge and pressure requirements are satisfied. In case the system does not satisfy the hydraulic requirements, the decision made for the optimal replacement time is revised until the requirments are satisfied. The model is well applied to an existing water distribution system, the Seoul Metropolitan Water Supply System (1st Phase). The results show that the decisions for the replacement time determined by the economic analysis are accepted as optimal and hydraulic integrity of the system is in good condition.