• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.3
• /
• pp.232-239
• /
• 2006

This paper is for applying interactive fuzzy linear programming for the problem of product mix planning, which is one of the aggregate planning problem. We developed a modified algorithm, which has two-phase approach for interactive fuzzy linear programming to get a better solution. Adding two-phase method, we expect to obtain not only the highest membership degree, but also a better utilization of each constrained resource.

• IE interfaces
• /
• v.3 no.1
• /
• pp.21-29
• /
• 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
• /
• v.13 no.4
• /
• pp.369-382
• /
• 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.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.6 no.8
• /
• pp.63-71
• /
• 1983

Aggregate planning coordinate the control variable over long-term to apply a demand variable and forcasting. In order to necessary the goal that doesn't make an inter-contradiction and explicitly defined. We made a considerable point of system approach for scheduling establishment. It include the control variables of aggregate planning : 1) employment 2) over time working and idle time 3) inventory 4) delivery delay S) subcontract 61 long - term facility capacity. Each variables composed of pure strategy as like a decision of inventory level, a change of employment level, etc. md alternative costs make a computation on the economic foundation. But the optimum alternative costs represent the mixed pure strategy. The faults of this method doesn't optimum guarantee a special scheduling as well as increasing a number of alternative combination. Theoretical, Linear Decision Rule make an including all variables, but it is almost impossible for this model to develope actually And also make use of the aggregate planning problem for developing system approach : LDR, heuristic model, Search Decision Rule, all kind of computers, simulation. But these models are very complex, each variables get an extremely inter-dependence. So this study be remained by theory level, some approach methods has not been brought the optimum solution to apply in every cases.

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

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

• Journal of the Korean Operations Research and Management Science Society
• /
• v.18 no.1
• /
• pp.127-138
• /
• 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
• /
• v.12 no.1
• /
• pp.55-61
• /
• 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.

• IE interfaces
• /
• v.17 no.1
• /
• pp.71-77
• /
• 2004

At the present time, container transportation plays a key role in the international logistics and the efforts to increase the productivity of container logistics become essential for Korean trucking companies to survive in the domestic as well as global competition. This study suggests an approach for determining fleet size for container road transportation with dynamic demand. Usually the vehicles operated by the transportation trucking companies in Korea can be classified into three types depending on the ways how their expenses occur; company-owned truck, mandated truck which is owned by outsider who entrust the company with its operation, and rented vehicle (outsourcing). Annually the trucking companies should decide how many company-owned and mandated trucks will be operated considering vehicle types and the transportation demands. With the forecasted monthly data for the volume of containers to be transported a year, a heuristic algorithm using tabu search is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost. The idea of the algorithm is based on both the aggregate production planning (APP) and the pickup-and-delivery problem (PDP). Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 2002.05a
• /
• pp.171-178
• /
• 2002

At the present time, container transportation plays a key role in the international logistics and the efforts to increase the productivity of container logistics become essential for Korean trucking companies to survive in the domestic as well as global competition. This study suggests an approach for determining fleet size for container road transportation with dynamic demand. Usually the vehicles operated by the transportation trucking companies in Korea can be classified into three types depending on the ways how their expenses occur; company-owned truck, mandated truck which is owned by outsider who entrust the company with its operation, and rented vehicle (outsourcing). Armually the trucking companies should decide how many company-owned and mandated trucks will be operated considering vehicle types and the transportation demands. With the forecasted monthly data for the volume of containers to be transported a year, a heuristic algorithm using tabu search is developed to determine the number of company-owned trucks, mandated trucks, and rented trucks in order to minimize the expected annual operating cost The idea of the algorithm is based on both the aggregate production planning (APP) and the pickup-and-delivery problem (PDP). Finally the algorithm is tested for the problem how the trucking company determines the fleet size for transporting containers.