• 한국지리정보학회지
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• 제19권1호
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• pp.167-179
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• 2016

최근 범지구적으로 증가하는 이상기후에 의해 SOC 시설물 안전이 지속적으로 위협받고 있다. 재난대응을 위해서는 피난 대피 경로 제시 등과 같은 신속한 의사결정이 필요하며 이는 재난 재해 정보 및 SOC 시설물 정보가 융 복합된 시공간적 정보가 활용되어야 한다. 이러한 정보는 정부 및 유관기관에서 분산적으로 수집되고 있어, 통합적 관리가 이루어지지 않고 있는 실정이다. 신속한 재난대응을 위해서는 분산 수집 관리되고 있는 재난 재해 정보의 통합관리와 SOC 시설물에 대한 안전도와 피해도 등의 정보 생성이 필요하다. 또한 재난 재해 정보 특성상 시공간적 융합이 필요하기 때문에, 관련 정보를 통합한 재해대응 의사결정 지원을 위한 인벤토리 구축이 필요하다. 본 연구에서는 신속한 재난대응의사결정 지원을 위한 시설물 중요도 위험도 피해액 인벤토리 구축 방안을 제시한다. 본 연구를 통해 분산 관리 되고 있는 재난 재해 및 SOC 시설물 관련 데이터를 수집하여 표준화 하고, 시설물의 중요도 위험도 피해액 산정에 필요한 통합 정보를 제공 할 수 있다. 향후 제안된 시스템을 통해 선제적 재난 대응을 위한 의사결정 도구로 활용할 수 있을 것으로 판단된다.

• 산업공학
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• 제11권1호
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• pp.85-95
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• 1998

This study is focussed on an optimal vehicle routing model for multi-supply centers in two-echelon logistic system. The aim of this study is to deliver goods for demand sites with optimal decision. This study investigated an integrated model using step-by-step approach based on relationship that exists between the inventory allocation and vehicle routing with restricted amount of inventory and transportations such as the capability of supply centers, vehicle capacity and transportation parameters. Three sub-models are developed: 1) sector-clustering model, 2) a vehicle-routing model based on clustering and a heuristic algorithm, and 3) a vehicle route scheduling model using TSP-solver based on genetic and branch-and-bound algorithm. Also, we have developed computer programs for each sub-models and user interface with visualization for major inputs and outputs. The application and superior performance of the proposed model are demonstrated by several sample runs for the inventory-allocation and vehicle routing problems.

• 한국국방경영분석학회지
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• 제24권1호
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• pp.176-188
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• 1998

In this paper, it is identified that the optimal level of each performance measures (service and inventory level) is not sensitive to an uncertain environment under JIT Kanban system designed by Moeeni. Moreover, it is proposed that the optimal design method considering multiple performance characteristics is the optimal level decision method according to the relative importance differences of each performance when there exist multiple performance characteristics. The result from the simulation analysis shows that the number of Kanban for stage 3 (final process) and stage 2 is increased at the service level. It is found that the expected loss is minimal when the cycle time decreases and the container size increases. However, the stage 1 is not affected by the number and cycle time of Kanban. It is thus important to consider carefully the cycle time and the container size of the Kanban to satisfy the demand in right time. In case of inventory level, the working inventory level decreases when the container size is decreased and the working inventory level also decreases slightly when the cycle time of the Kankban is increased in stage 1 and 2.

• 품질경영학회지
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• 제13권1호
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• pp.56-64
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• 1985

This paper presents a general algorithm of multi-item continuous review models to obtain simultaneous solutions for ordering quantities and reorder points for each item in an inventory, while satisfying constraints on average inventory investment and reordering workload. Two models are formulated'in each model the heuristic method is utilized, and the partial back-logging is considered. In the first model, the objective function is the minimization of total inventory variable cost. In the second model, the objective function is the minimization of total time-weighted shortages, and the ordering, holding, and stockout costs in this model are independent each other. A numerical example is also solved to present application of each model.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.159-160
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• 2021

본 연구의 의사결정지원 모형을 대상으로 한 시뮬레이션 결과에 의하면 맥주 산업의 조정을 기반으로 한 빅 데이터 협업 플랫폼 하에서 공급망 운영 조건을 동원하고, 공급망 직접 물류 재고는 상대적으로 안정적인 가치를 유지하며 재고가 없거나 심각한 부족도 발생하지 않는다. 따라서 전통적인 맥주 공급망 운영과 같은 재고 상황에서 맥주의 심각한 공급 부족으로 인해 체인 재고 수준 보고서로 인한 수요 정보 확장 상황을 피할 수 있다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2023년도 춘계학술대회
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• pp.254-255
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• 2023

This paper discovers a robust managerial strategy for a stochastic inventory of perishable products, where the model experiences changing factors including inner parameters and an external disturbance with unknown form. An analytical solution for the optimization problem can be obtained by applying the Hamilton-Bellman-Jacobi equation, however the policy result cannot completely suppress the oscillation from the external disturbance. Therefore, an intelligent approach named Radial Basis Function Neural Networks is applied to estimate the unknown disturbance and provide a robust controller to manipulate the inventory level more effective. The final results show the outstanding performance of RBFNN controller, where both the estimation error and control error are guaranteed in the predefined limit.

• 벤처창업연구
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• 제9권2호
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• pp.81-86
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• 2014

본 논문에서는 그룹교체 정책과 예비품 재고정책을 동시에 고려하여 최적화하는 방안을 제시한다. 일반적으로 보전정책들은 예비품의 재고가 늘 가용하다고 가정하고 있으나 예비품의 재고 확보 여부에 의해 보전활동은 영향을 받을 수밖에 없다. 동일한 여러 유닛들이 동시에 운용될 때 이용되는 그룹교체정책을 바탕으로 이를 지원하기 위한 최적 재고수준을 결정한다. 일정한 개수의 유닛이 고장 나는 시점에서 그룹교체를 수행한다. 예비품의 재고는 일정 횟수의 그룹교체를 할 만큼 주문하여 유지한다. 보전비용과 재고비용 등 운용비용을 최소화할 수 있는 최적의 그룹교체 주기와 재고수준을 구한다.

• 대한산업공학회지
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• 제2권1호
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• pp.93-100
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• 1976

Given a fixed production process and facility capacity, the ability to respond to market fluctuations in terms of changes in production, work force, and inventory is the major task of production management. The costs involved are primarily payroll (regular and overtime), inventory carrying, and hiring and firing. The magnitude of these costs is usually a significant portion of the operating costs of the firm and consequently a small percentage saving due to astute aggregate scheduling can mean substantial absolute saving. At least three demonstrably optimal techniques have been developed for solving this aggregate scheduling problem. These three optimal are apparently LDR, PPP, and SDR. By combining these three different approaches, another optimal solution was obtained by me. I call this CDR (Combined Decision Rule). This approach appears to be useful. This approach may be generalizable to aggregate scheduling involving a short term resources.

• 한국경영과학회지
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• 제29권3호
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• pp.111-127
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• 2004

We consider a supply chain model with a make-to-order production facility and a single supplier. The model we treat here is a special case of a two-echelon inventory model. Unlike classical two-echelon systems, the demand process at the supplier is affected by production process at the production facility as well as customer order arrival process. In this paper, we address that how the demand variability impacts on the optimal replenishment policy. To this end, we incorporate Erlang and phase-type demand distributions into the model. Formulating the model as a Markov decision problem, we investigate the structure of the optimal replenishment policy. We also implement a sensitivity analysis on the optimal policy and establish its monotonicity with respect to system cost parameters.

• 경영과학
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• 제32권4호
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• pp.19-28
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• 2015

This study presents a mathematical programming model to develop production planning in the manufacturing processes for photovoltaic silicon ingots and wafers. The model is formulated as a linear programming model that maximizes total growth margin, which is composed of production cost, inventory cost, shortage cost, and sales profit while considering the constraints associated with the production environments of photovoltaic materials. In order to demonstrate the utility of the model for production planning, we run operations for a planning horizon of a year for a case study. When the primary results of this mathematical programming are compared with the historical records, the model could have resulted in the considerable increase of the total growth margin by effectively reducing inventory cost if a decision maker had employed the model as a decision support system with perfect information for sales demand.