• Journal of Korean Society for Quality Management
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• v.17 no.1
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• pp.116-124
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• 1989

A multi-period production-inventory scheduling model, which extends the customary dynamic lot sizing model to the one for deteriorating items, is developed. The amount of deterioration during a period is assumed to be proportional to the on-hand inventory at the end of the period. It is futher assumed that the deterioration rates vary from period to period. In addtion, an expediting cost due to the delay of outstanding order is included and it is allowed to offset the order release date in advance, instead, in order to avoid incurring the cost. Finally, a quasi-WW algorithm corresponding to the Wagar-Whitin algorithm is proposed to obtain the optimal production-inventory schedules.

• Journal of Korean Institute of Industrial Engineers
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• v.24 no.1
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• pp.157-165
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• 1998

This paper considers the single-product production and transportation problem with discrete time, dynamic demand and finite time horizon, an extension of classical dynamic lot-sizing model. In the model, multiple freight container types are allowed as the transportation mode and each order (product) placed in a period is shipped immediately by containers in the period. Moreover, each container has type-dependent carrying capacity restriction and at most one container type is allowed in each shipping period. The unit freight cost for each container type depends on the size of its carrying capacity. The total freight cost is proportional to the number of each container type employed. Such a freight cost is considered as another set-up cost. Also, it is assumed in the model that production and inventory cost functions are dynamically concave and backlogging is not allowed. The objective of this study is to determine the optimal production policy and the optimal transportation policy simultaneously that minimizes the total system cost (including production cost, inventory holding cost, and freight cost) to satisfy dynamic demands over a finite time horizon. In the analysis, the optimal solution properties are characterized, based on which a dynamic programming algorithm is derived. The solution algorithm is then illustrated with a numerical example.

• Industrial Engineering and Management Systems
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• v.7 no.3
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• pp.257-265
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• 2008

This paper deals with the joint decisions on pricing and ordering for a monopolistic retailer who sells perishable goods with a fixed lifetime or demand period. The newsvendor-typed problem is formulated as a two-period inventory system where the first period represents the inventory of fresh or new-arrival items and the second period represents the inventory of items that are older but still usable. Demand may be for either fresh items or for somewhat older items that exhibit physical decay or deterioration. The retailer is allowed to adjust the selling price of the deteriorated items in the second period, which stimulates demand and reduces excess season-end or stale inventory. This paper develops a stochastic dynamic programming model that solves the problem of preseason decisions on ordering-pricing and a within-season decision on markdown pricing. We also develop a fixed-price model as a benchmark against the dual-price dynamic model. To illustrate the effect of the dual-price policy on expected profit, we conduct a comparative study between the two models. Extension to a generalized multi-period model is also discussed.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.13-34
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• 1993

By operating on many part of a software system concurrently, the parallel processing computers may provide several orders of magnitude more computing power than traditional serial computers. If the Lagrangean approximation procedure is applied to a large scale manufacturing problem which is decomposable into many subproblems, the procedure is a perfect candidate for parallel processing. By distributing Lagrangean subproblems for given multiplier to multiple processors, concurrently running processors and modifying Lagrangean multipliers at the end of each iteration of a subgradient method,a parallel processing of a Lagrangean approximation procedure may provide a significant speedup. This purpose of this research is to investigate the potential of the parallelized Lagrangean approximation procedure (PLAP) for certain combinational optimization problems in manufacturing systems. The framework of a Plap is proposed for some combinatorial manufacturing problems which are decomposable into well-structured subproblems. The synchronous PLAP for the multistage dynamic lot-sizing problem is implemented on a parallel computer Alliant FX/4 and its computational experience is reported as a promising application of vector-concurrent computing.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.147-150
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• 2000

본 논문은 단일설비로 다종제품을 생산하는 생산시스템에서 생산준비비용의 절감효과를 고려한 동적생산계획 모형을 다룬다. 이 모형에서 각 제품에 대한 수요는 유한계획기간에서 동적으로 발생하고 추후조달은 허용되지 않으며 투입자원은 한 종류가 사용된다. 또한, 생산기간마다 생산설비는 다종제품을 동시에 생산하고 이때 각 제품의 생산량은 전체 투입자원량의 일정비율로 생산된다. 이 모형에서 총비용은 생산준비 비용의 절감을 위한 투자비용, 생산준비비용, 각 제품별 재고유지비용으로 구성된다. 본 논문에서는 절감된 생산준비비용 하에서의 최적생산계획과 생산준비비용의 절감을 위한 최적투자액을 동시에 결정할 수 있는 휴리스틱 알고리즘를 제시한다. 또한, 선형 및 지수 감소함수 형태의 생산준비비용 절감함수 하에서 다양한 문제들을 대상으로 한 시뮬레이션 실험을 통해 제시한 휴리스틱 알고리즘의 효율성을 검증한다.