This paper considers a joint problem for blood inventory planning at hospitals and blood delivery planning from blood centers to hospitals, in order to alleviate the blood service imbalance between big and small hospitals being occurred in practice. The joint problem is to determine delivery timing, delivery quantity, delivery means such as medical drones and legacy blood vehicles, and inventory level to minimize inventory and delivery costs while satisfying hospitals’ blood demand over a planning horizon. This problem is formulated as a mixed integer programming model by considering practical constraints such as blood lifespan and drone specification. To solve the problem, this paper employs a Lagrangian relaxation technique and suggests a time efficient Lagrangian heuristic algorithm. The performance of the suggested heuristic is evaluated by conducting computational experiments on randomly-generated problem instances, which are generated by mimicking the real data of Korean Red Cross in Seoul and other reliable sources. The results of computational experiments show that the suggested heuristic obtains near-optimal solutions in a shorter amount of time. In addition, we discuss the effect of changes in the length of blood lifespan, the number of planning periods, the number of hospitals, and drone specifications on the performance of the suggested Lagrangian heuristic.

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material . In the experimental implementation of our rule-based inventory planning, Company ‘S’ reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker’s continuing support and attention even without seeing any upcoming business crisis.

Auto part industry supplies production for auto manufacturer and after market. These company have inventory for delivery. High inventory level can be good for delivery, but cost will be increase. Low inventory level can be customer unsatisfaction for delivery late. Low inventory level also is reason of low productivity by decreasing product batch size. These article suggest model for calculation a proper inventory level and prove a effect by simulation of some company.

다른 제조 업체에 부품을 공급하는 부품 기업에서는 고객 수요를 대응하기 위해 운 영하기 위해 완제품이나 반제품 재고를 운영하고 있다. 재고는 많으면 고객 대응도가 좋아질 수 있지만 운영 비용이 늘어나고, 재고가 너무 적으면 고객 대응이 지연되어 고객 불만족을 초래하게 될 것이다. 또한 재고 수준이 적으면 고객 수요에 대한 생산 회수가 증가하여 배치 생산으로 생산성을 높이는 것이 어렵게 된다. 따라서 고객 수요 대응에 대한 만족도를 최대한 유지하고 운영 비용이나 생산 비용을 절감시키는 방안 에 대해서 시뮬레이션을 통해 제시하고자 한다.

본 논문은 (1 : 1 : N) 재고모형에 대한 복수제품의 순환생산 및 배송 일정계획을 수립하는 연구를 수행하였다. 세부적으로 공급자가 원자재를 생산자에게 배송하면, 생산자는 순환생산방식을 활용하여 복수의 제품을 생산하여 N 구매자에게 배송하는 상황을 고려하고 있다. 본 연구의 목적은 공급자, 생산자, 구매자를 포함하는 시스템 전체의 비용을 최소화하는 계획을 수립하는 것이다. 최적해가 가지는 몇 가지 특성들을 분석하고, 이를 통해서 단계적인 휴리스틱 절

As competition in manufacturing enterprise is contested, the scope of safely production planning, manufacturing enterprise should ensure, has been reduced. The more upstream of SCM, the more reduction of scope of production planning. As a result, order fluctuation is more sharply contested. Through improving the logistics network, it is best way that the end user's demand information is conveyed to upstream of SCM, but it is difficult in fact. In this paper, it mention the way of robustic adjustment, in the suppliers' point of view, the end user's demand information is dammed up, as they postpone responding the customer's order as a possible. And it will show the result of appling the way, as a case study.