• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.3
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• pp.159-168
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• 2015

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company's profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

• IE interfaces
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• v.3 no.1
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• pp.21-29
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• 1990

This paper presents a linear programming formulation of the aggregate production planning problem for an optical instrument manufacturing company. Taking into account of the various requirements of the company, an L.P model is developed whose objective is to minimize the total cost of production during the planning horizon. The application results and its implications are well understood by the management and expected to be used as a guide line for future production planning.

• Industrial Engineering and Management Systems
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• v.13 no.4
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• pp.369-382
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• 2014

This paper introduces a new multi-product multi-period multi-objective aggregate production planning problem. The proposed problem is modeled using multi-objective mixed-integer mathematical programming. Three objective functions, including minimizing total cost, maximizing customer services level, and maximizing the quality of end-product, are considered, simultaneously. Several constraints such as quantity of production, available time, work force levels, inventory levels, backordering levels, machine capacity, warehouse space and available budget are also considered. Some parameters of the proposed model are assumed to be qualitative and modeled using fuzzy sets. Then, a fuzzy goal programming approach is proposed to solve the model. The proposed approach is applied on a real-world industrial case study of a color and resin production company called Teiph-Saipa. The approach is coded using LINGO software. The efficacy and applicability of the proposed approach are illustrated in the case study. The results of proposed approach are compared with those of the existing experimental methods used in the company. The relative dominance of the proposed approach is revealed in comparison with the experimental method. Finally, a data dictionary, including the way of gathering data for running the model, is proposed in order to facilitate the re-implementation of the model for future development and case studies.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1994.04a
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• pp.421-421
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• 1994

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.1
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• pp.127-138
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• 1993

The Production Switching Heuristic (PSH) develope dby Mellichamp and Love (1978) has been suggested as a more realistic, practical and intuitively appealing approach to aggregate production planning (APP). In this researh, PSH has been modified to present a more sophisticated open grid search procedure for solving the APP problem. The effectiveness of this approach has been demonstrated by determining a better near-optimala solution to the classic paint factory problem. The performance of the modified production switching heuristic is then compared in the context of the paint factory problem with results obtained by other prominent APP models including LDR, PPP, and PSH to conclude that the modified PSH offers a better minimum cost solution than the original PSH model.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.1
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• pp.55-61
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• 1986

Mathematical forecasting models and a practical computer based forecasting system are developed for planning production in a manufacturing and distribution network. The forecasting system works at the highest level of a hierarchical computer-based decision support system consisting of the forecasting system, an aggregate planning system and a shop floor scheduling system. The dynamics of business operations for an actual company have been considered to make this study a unique comprehensive analysis of a real world forecasting problem.

• Journal of Korean Society of Rural Planning
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• v.11 no.4 s.29
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• pp.93-98
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• 2005

A aggregate size distribution of soils is an important in successful crop production in reclaimed tidelands. The aggregate size distribution for this study were determined of 0.1mm, 0.25mm, 0.5mm, 1.0mm, and 2.0mm by wet sieving method. Agricultural activity, period of reclamation showed significant effects on aggregate size distribution in reclaimed tidelands. Aggregate MWD was greater in SS and KH(above 1.0m) than in YSG, GHD, SMG, and DH(below 0.5mm) reclaimed tidelands and tidelands. The percentage of aggregates less than < 2mm for SMG, GHD, and SM reclaimed tidelands and tidelands were ranged 8.9%, 36.7%, and 38.0%, respectively. The percentage of > 0.1mm aggregates for SMG, GHD, and SM reclaimed tidelands were ranged 9.0%, 26.0%, and 48.9%, respectively. Results indicated that aggregate size distribution of reclaimed tidelands and tidelands under various agricultural systems vary with reclamation period and soil type.

• Journal of the Korean Operations Research and Management Science Society
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• v.13 no.2
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• pp.59-65
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• 1988

This paper discusses the problem of coordinating aggregate planning and production schedules, minimizing the combined set-up inventory and capacity costs. In this study, by using the relation of fixed production quantity and the number of set-up we develop a heuristirc procedure of solving the discrete demand, fixed production quantity, variable capacity problem. First, we obtain the trade-off between set-up cost and capacity cost, then search the point minimizing the combined inventory and capacity costs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.181-188
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• 2021

In preparing a aggregate production plan(APP), the transportation method generally uses a linear planning(LP) software package for TSM(transportation simplex method), which seeks initial solutions with either NCM, LCM, or VAM specialized in transportation issues and optimizes them with either SSM or MODI. On the other hand, this paper proposes a transportation method that easily, quickly, and accurately prepares a APP without software package assistance. This algorithm proposed simply assigned to least cost-first, and minimized the inventory periods. Applying the proposed algorithm to 6-benchmarking data, this algorithm can be obtained better optimal solution than VAM or LP for 4 data, and we obtain the same results for the remained 2 data.

• Economic and Environmental Geology
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• v.57 no.2
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• pp.129-141
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• 2024

This study derived production-production multipliers using a regional input-output table and estimated the induced effect of aggregates through the non-metallic minerals sector and the concrete products sector. In deriving the induced effect of aggregates, it is difficult to use the regional input-output table due to the sector classification problem. This study analyzed the non-metallic mineral sector, including aggregates, as aggregates sector, and the concrete products sector, which uses most of the aggregate production. By analyzing this, we attempted to alleviate difficulties caused by sector classification restrictions. In the process of estimating the induced effect, it was assumed that there was a decrease in aggregate production, and in the process of analyzing the concrete products sector, the effect of the decrease in concrete product production due to the decrease in aggregate production, that is, the decrease in production of one unit of aggregate was 0.8511 in the concrete product sector. The analysis was conducted on the premise of a decrease in unit production. Inducing effects within and between regions were calculated for the 17 metropolitan cities and provinces classified by the regional input-output table. The employment effect was also calculated, assuming a 10% production decrease to show differences according to the size of the aggregate and concrete product sectors in each region.