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of Technology, Thammasat university, Pathumthani 12121, Thailand.  \nCorresponding author, E-mail: [pisal@siit.tu.ac.th](pisal@siit.tu.ac.th)  \nReceived 26 Jul 2001 Accepted 6 Feb 2002  \nABSTRACT Among existing aggregate production planning (APP) approaches, the spreadsheet solver approach is found to be the most applicable for industries due to the following reasons: (1) the solveron spreadsheet software is readily available on virtually all personal computers,(2) the APP model is relatively easy to formulate in a spreadsheet format, and (3) the results are easy to interpret. This paper presents an APP model and a guideline to develop an optimal aggregate production plan using the spreadsheet solver approach. A manufacturing case study is presented to demonstrate how the guideline can be applied. The developed APP model is also evaluated whether it is satisfactory and can lead to immediate implementation.  \nKEYWORDS: Aggregate Production Planning (APP), Application in Industries, Spreadsheet Solver, Optimization, Case Study.  \nINTRODUCTION  \nAggregate production planning (APP) is a medium term capacity planning that determines minimum cost workforce and production plans to meet customer demands. Its aim is to determine the production quantity and inventory level in an aggregate term. The aggregate production plan usually covers a time period ranging from 12 to 24 months. Data in the aggregate plan usually are monthly or quarterly data. APP has a strong need when a demand pattern is highly seasonal.  \nThere are many techniques that can solve APP problems such as trial-and-error, linear and nonlinear programming, linear decision rule, and simulation search.1-4 Some of these techniques yield the optimum solution, while others give only acceptable ones. Additionally, some require models that are easy to formulate, while others require complicated models. Spreadsheet software is one of the powerful and practical tools for developing an aggregate production plan since it has a good user interface and optimization capability.  \nSpreadsheet software has many useful applications in production planning and control. For example, a spreadsheet template can provide multiple regression options.5 It is helpful in solving forecasting problems when the dependent variable is binary. The spreadsheet models are also used to perform a sensitivity analysis of performance measures in manufacturing  \nenvironment.6 It can be used to determine whether available capacity and inventory is above the maximum level or below the minimum level.7 Kharab also developed a macro program in the spreadsheet software to solve linear programming problems.8  \nThe trial-and-error technique for solving APP problem can be performed faster if it is applied on the spreadsheet software. This technique is practical and very easy to understand since it does not require an extensive mathematical background. Since the trials are subjectively determined by a user, it usually takes relatively long time to obtain a feasible and satisfactory solution. Moreover, the solution may not be the optimal one. There are some papers demonstrating the way in which APP problems can be solved using the trial-and-error technique on the spreadsheet software.9-11  \nThe spreadsheet solver is an add-in feature found in recent versions of the spreadsheet software such as Lotus 1-2-3, Microsoft Excel, and Borland’s Quattro Pro.12 This feature is capable of optimally solving linear and nonlinear programming problems. Albright et al. demonstrated the use of spreadsheetsolver to solve small examples of APP problems.13 Crandall varied some parameters such as inventory holding cost, back order cost, and hiring and laying off costs, and determined effects of individual parameters on ","cbCaig392BUhF1yb","https://ap.wps.com/l/cbCaig392BUhF1yb","pdf",662617,10,"English","# Introduction\n## Aggregate production planning (APP) scope and data characteristics\n## Existing APP solution techniques\n## Spreadsheet software as a practical tool","[{\"question\":\"Why is the spreadsheet solver approach considered suitable for industries in aggregate production planning?\",\"answer\":\"It is readily available on most personal computers, the APP model is easy to formulate in spreadsheets, and the results are easy to interpret.\"},{\"question\":\"What objectives does the paper state for its spreadsheet-based APP approach?\",\"answer\":\"To propose a spreadsheet APP model, to provide a guideline for developing an optimal aggregate plan using spreadsheet solver, and to evaluate the approach by checking whether the plan is satisfactory and ready for immediate implementation.\"},{\"question\":\"What role does aggregate production planning play and what time horizon does it cover?\",\"answer\":\"APP is medium-term capacity planning that determines workforce and production plans to meet demand, typically covering 12 to 24 months with monthly or quarterly data.\"}]","Aggregate Production Planning Using Spreadsheet Solver - Model and Case Study | PDF",1790372379]