• International Journal of Computer Science & Network Security
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• v.21 no.7
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• pp.87-92
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• 2021

Analysis of current state of construction industry functioning in Ukraine allows us to identify a number of problems having negative impact on sustainable development of construction industry, especially in terms of its organization. Therefore, it is absolutely essential to study existing methods of organization system supplying construction sites with necessary material resources. Companies can develop their own logistics departments, which independently solve logistics issues related to transportation organization and management, accounting and inventory management, acquisition and warehousing, intercommunication (ability to obtain both final and intermediate information during transporting materials). Using a complex of methods is substantiated: the hierarchy analysis method (Saati's method), the network method, the defect elimination algorithm DEA, the transportation problem that finds optimal problem solutions for construction sector with the purpose of rational supplying uninterrupted construction with building resources in the designed model "provider-transportation-costs".

• The Journal of Society for e-Business Studies
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• v.6 no.3
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• pp.197-207
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• 2001

The industrial structure comes to be complicated and for the production of the enterprise the rational and scientific forecast is necessary. The demand forecast has been widely used to linear regression, and up to now the linear regression was sharp the relationskp between then dependent variable and the independent variables. But, The real society demands accurate demand forecast from uncertain environment and subjective concept. This paper proposes the demand quantity forecast method to using of the fuzzy linear regression in uncertain and vague environment. Also, the optimum decision making of the demand quantity forecast uses integral calculus of the Sugeno to reflecting with the expert's (inventory manager) opinion.

• Industrial Engineering and Management Systems
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• v.10 no.1
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• pp.74-83
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• 2011

In this paper, we consider a new lot-sizing and scheduling problem (LSSP) that minimizes the sum of production cost, setup cost and inventory cost. Setup carry-over, setup overlapping, state dependent setup time as well as demand splitting are considered. For this LSSP, we develop a mixed integer programming (MIP) model, of which the size does not increase even if we divide a time period into a number of micro time periods. Also, we develop an efficient heuristic algorithm by combining a decomposition scheme with a local search procedure. Test results show that the developed heuristic algorithm finds a good quality (in practice, even better) feasible solution using far less computation time compared with the CPLEX, a competitive MIP solver.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.548-555
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• 2003

Customer satisfaction level is usually measured in terms of price, quality, customization, after-sale-service, product variety etc. Each finn sets up a distinctive production/marketing strategy to gain competitive advantage by prioritizing the customer satisfaction measures. The market differentiation strategy directly results in supply chain performance such as lead time, inventory, customer fill rate and market share. Product proliferation desirable in customization sense often conflicts the economies of scale effect in production side. This paper focuses the relationship between product variety and market share. Specifically, we investigate how introduction of new product affects the current market share, i.e.,) formation of customer preference and provide some insight into the optimal range of product variety.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.101-112
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• 2004

Customer satisfaction level is usually measured in terms of price, qualify, customization, after-sale-service, product variety etc. Each firm sets up a distinctive production/marketing strategy to gain competitive advantage by Prioritizing the customer satisfaction measures. The market differentiation strategy directly results in supply chain performance such as lead time, inventory, customer fill rate and market share. Product proliferation desirable in customization sense often conflicts the economies of scale effect in production side. This paper focuses the relationship between product variety and market share. Specifically, we investigate how introduction of new product affects the current market share, i.e., formation of customer preference and provide some insight into the optimal range of product variety.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3304-3310
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• 2010

This study solves the decision making problems for TFT-LCD manufacturing supply chain with demand and price uncertainties by establishing robust production and distribution strategies. In order to control the decisions regarding production graded by quality, inventory level and distribution, this study develop scenario model based stochastic mixed integer linear programs (SMILPs) that consider demand and price uncertainties as well as realistic constraints such as capacities etc. The performance of the solution obtained from the SMILPs using robust algorithms will be evaluated through various scenarios.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.311-314
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• 2005

Supply chain optimization is one of the most important components in the optimization of a company's value chain. This paper considers the problem of designing the supply chain for a product that is represented as an assembly bill of material (BOM). In this problem we are required to identify the locations at which different components of the product arc are produced/assembled. The objective is to minimize the overall cost, which comprises production, inventory holding and transportation costs. We assume that production locations are known and that the inventory policy is a base stock policy. We first formulate the problem as a 0-1 nonlinear integer programming model and show that it can be reformulated as a 0-1 linear integer programming model with an exponential number of decision variables.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.47 no.2
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• pp.116-123
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• 2024

In the manufacturing industry, dispatching systems play a crucial role in enhancing production efficiency and optimizing production volume. However, in dynamic production environments, conventional static dispatching methods struggle to adapt to various environmental conditions and constraints, leading to problems such as reduced production volume, delays, and resource wastage. Therefore, there is a need for dynamic dispatching methods that can quickly adapt to changes in the environment. In this study, we aim to develop an agent-based model that considers dynamic situations through interaction between agents. Additionally, we intend to utilize the Q-learning algorithm, which possesses the characteristics of temporal difference (TD) learning, to automatically update and adapt to dynamic situations. This means that Q-learning can effectively consider dynamic environments by sensitively responding to changes in the state space and selecting optimal dispatching rules accordingly. The state space includes information such as inventory and work-in-process levels, order fulfilment status, and machine status, which are used to select the optimal dispatching rules. Furthermore, we aim to minimize total tardiness and the number of setup changes using reinforcement learning. Finally, we will develop a dynamic dispatching system using Q-learning and compare its performance with conventional static dispatching methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.64-73
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• 2019

The manufacturing companies under Make-To-Order (MTO) production environment face highly variable requirements of the customers. It makes them difficult to establish preemptive production strategy through inventory management and demand forecasting. Therefore, the ability to establish an optimal production schedule that incorporates the various requirements of the customers is emphasized as the key success factor. In this study, we suggest a process of designing the simulation model for establishing production schedule and apply this model to the case of a flat glass processing company. The flat glass manufacturing industry is under MTO production environment. Academic research of flat glass industry is focused on minimizing the waste in the cutting process. In addition, in the practical view, the flat glass manufacturing companies tend to establish the production schedule based on the intuition of production manager and it results in failure of meeting the due date. Based on these findings, the case study aims to present the process of drawing up a production schedule through simulation modeling. The actual data of Korean flat glass processing company were used to make a monthly production schedule. To do this, five scenarios based on dispatching rules are considered and each scenario is evaluated by three key performance indicators for delivery compliance. We used B2MML (Business To Manufacturing Markup Language) schema for integrating manufacturing systems and simulations are carried out by using SIMIO simulation software. The results provide the basis for determining a suitable production schedule from the production manager's perspective.

• Journal of Digital Contents Society
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• v.9 no.2
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• pp.295-303
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• 2008

With universality of e-commerce through internet, smaller online shopping malls are increased. A Smaller online shopping mall by nature lacks an extra space to load many inventory quantities. Therefore, it is difficult to response immediately with client request with traditional inventory management method. VMI has a character that supplier can control volume of inventory according to sales of seller. This paper proposes SOHO-VMI that is applied VMI into smaller online shopping mall. Proposed SOHO-VMI supports M $\times$ N structure can interact with multiple suppliers and sellers. And it uses XML/EDI for interaction with EDI documents use to legacy system. Also, This paper proposes logistics statistic prediction algorithm can adjust production and distribution volumes to supplier considering seller's product distribution information and seasonal factor.