• Journal of Korean Society for Quality Management
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• v.20 no.2
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• pp.1-10
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• 1992

In this paper, we study a joint lot sizing and inspection policy under an EPQ(Economic Production Quantity) model where a random proportion of units are defectives. Those units can be discovered only through costly inspection. The problem is thus bivariate : both lot size and fraction to inspect are to be chosen. We first analyze a model in which the only penalty for uninspected defectives is financial, and then consider a model where defectives units cannot be used and thus must be replaced by non-defective ones. As a result it can be proved that this inspection policy costs economically and is to be decided effectively for the Economic Production Quantity constraining the fraction to inspect.

• 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.

• Management Science and Financial Engineering
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• v.11 no.1
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• pp.63-78
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• 2005

Disassembly scheduling is the problem of determining the ordering and disassembly schedules of used or end-of-life products while satisfying the demand of their parts or components over a certain planning horizon. This paper considers the case of the assembly product structure for the cost-based objective of minimizing the sum of purchase, setup, inventory holding, and disassembly operation costs. To represent and solve the problem optimally, this paper presents an integer programming model, which is a reversed form of the multi-level lot sizing formulation. Computational experiments on an example derived from the literature and a number of randomly generated test problems are done and the results are reported.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.32 no.3
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• pp.110-117
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• 2009

This paper introduces a case study for efficient generation of production schedules in a tube manufacturing system. The considered scheduling problem consists of two sub problems : lot sizing for a job and Job sequencing. Since these problems require simulation optimization in which the performance measures are obtained by simulation execution, the trade-off between solution quality and computation time is an important issue. In this study, the optimal lot size for every product type is determined from simulation experiments. Then, target production quantity for each product type is transformed to several jobs such that a Job consists of determined lot size. To obtain the good solution for a Job sequence in a reasonable time, a number of alternatives are generated from heuristic rules developed by intuition and analysis of the considered system, and a job sequence is selected from simulation experiments.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.11
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• pp.956-962
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• 2005

This paper presents an integrated analysis of production and financing decisions. We assume that a cash storage unit is installed to manage the cash flows related with production activities such as raw material procurement, process operating setup, Inventory holding cost and finished product sales. Temporarily financial investments are allowed for more profit. The production plant is modeled by the Batch-Storage Network with Recycle Streams in Yi and Reklaitis (2003). The objective function of the optimization is minimizing the opportunity costs of annualized capital investment and cash/material inventory while maximizing stockholder's benefit. No depletion of all the material and cash storage units is major constraints of the optimization. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the cash and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems and analytical lot sizing equations under a mild assumption about the cash flow pattern of stockholder's dividend. The first subproblem is a separable concave minimization network flow problem whose solution yields the average material flow rates through the networks. The second subproblem determines the decisions about financial Investment. Finally, production and financial transaction lot sizes and startup times can be determined by analytical expressions as far as the average flow rates are calculated. The optimal production lot and storage sizes considering financial factors are smaller than those without such consideration. An illustrative example is presented to demonstrate the results obtainable using this approach.

• 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.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.363-370
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• 2002

This paper presents a production planning algorithm for minimizing the costs of production and subcontracting in SCM (supply chain management) environment. In our SCM environment, the several local plants that aye dispersed geographically produce parts and products. In this environment, we have to decide the production volumes of both parts and products considering the BOM (bill-of-material) structure to meet the fixed order quantity or forecasted demand quantity. Each plant produces the specified parts of product with finite production capacity. There exist subcontracting decisions relevant to the production capacity of each plant except the core process plant, and when we use the subcontractor's capacities we should be charged for the fixed subcontracting fees. The objective of this study is to solve the production planning problem, which minimizes the total costs of production, inventory, setup, and subcontracting under constraints of production and subcontracting capacity. For this problem, an integrated production planning model based on the multi-level capacitated lot sizing problem was formulated, and efficient decomposition algorithm was proposed. The experimental investigation shows that the proposed heuristic generates quite good solutions at very low computational costs.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.81-89
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• 1990

Transfer pricing mechanism is applied to the problem of input buffer size in the context of interfacing a flexible manufacturing system with multiple following production lines. The size of the input buffers can be determined economically by using non-linear transfer pricing either in a decentralized organization or in a centralized organization. Under the certain conditions, input buffer size determined from this non-linear transfer pricing is more economical than the traditional economic lot size model. The benefit comes from transferring part of FMS' inventory to the following production lines. And this non-linear transfer pricing makes sense if the FMS' unit inventory holding cost is high enough.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.9
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• pp.932-940
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• 2011

This paper presents an integrated analysis of supply chain and financing decisions of multi-national corporation. We construct a model in which multiple currency storage units are installed to manage the currency flows associated with multi-national supply chain activities such as raw material procurement, process operation, inventory control, transportation and finished product sales. Core contribution of this study is to quantitatively investigate the influence of macroscopic economic factors such as exchange rates and taxes on operational decisions. The supply chain is modeled by the Process-Storage Network with recycle streams. The objective function of the optimization is minimizing the opportunity costs of annualized capital investments and currency/material inventories minus the benefit to stockholders interpreted by home currency. The major constraints of the optimization are that the material and currency storage units must not be depleted. A production and inventory analysis formulation, the periodic square wave (PSW) model, provides useful expressions for the upper/lower bounds and average levels of the currency and material inventory holdups. The expressions for the Kuhn-Tucker conditions of the optimization problem are reduced to a subproblem and analytical lot sizing equations. The procurement, production, transportation and financial transaction lot sizes can be determined by analytical expressions after the average flow rates are already known. We show that, when corporate income tax is taken into consideration, the optimal production lot and storage sizes are smaller than is the case when such factors are not considered typically by 20 %.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.2
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• pp.19-27
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• 2016

Maritime transport is now regarded as one of the main contributors to global climate change by virtue of its $CO_2$ emissions. Meanwhile, slow steaming, i.e., slower ship speed, has become a common practice in the maritime industry so as to lower $CO_2$ emissions and reduce bunker fuel consumption. The practice raised various operational decision issues in terms of shipping companies: how much ship speed is, how much to bunker the fuel, and at which port to bunker. In this context, this study addresses an operation problem in a shipping companies, which is the problem of determining the ship speed, bunkering ports, and bunkering amount at the ports over a given ship route to minimize the bunker fuel and ship time costs as well as the carbon tax which is a regulatory measure aiming at reducing $CO_2$ emissions. The ship time cost is included in the problem because slow steaming increases transit times, which implies increased in-transit inventory costs in terms of shippers. We formulate the problem as a nonlinear lot-sizing model and suggest a Lagrangian heuristic to solve the problem. The performance of the heuristic algorithm is evaluated using the data obtained from reliable sources. Although the problem is an operational problem, the heuristic algorithm is used to address various strategic issues facing shipping companies, including the effects of bunker prices, carbon taxes, and ship time costs on the ship speed, bunkering amount and number of bunkering ports. For this, we conduct sensitivity analyses of these factors and finally discuss study findings.