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Journal articles on the topic 'Aggregate production planning'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Ning, Yufu, Jianjun Liu, and Limei Yan. "Uncertain aggregate production planning." Soft Computing 17, no. 4 (2012): 617–24. http://dx.doi.org/10.1007/s00500-012-0931-4.

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2

Rusindiyanto, Rr. Rochmoeljati, Yekti Condro Winursito, Isna Nugraha, and Hafid Syaifullah. "Production Planning and Control of Flooring Using Aggregate Planning Method." Technium: Romanian Journal of Applied Sciences and Technology 16 (October 29, 2023): 397–404. http://dx.doi.org/10.47577/technium.v16i.10018.

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PT. X a is a private company engaged in the wood processing industry. To avoid production excesses or shortages in the company, production planning using the Aggregate Planning Method can be utilized to meet all consumer demands. The variables used include demand data, production costs, setup costs, and manufacturing time. Through this research, the company can fulfill consumer demands and minimize production costs by implementing aggregate planning. Additionally, the company can forecast future demand, enabling them to anticipate fluctuations in consumer demand. By using aggregate production

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3

Matondang, Abdul Rahim, and Widodo Widodo. "PERENCANAAN DAN PENGENDALIAN KAPASITAS PRODUKSI PRODUK RAKITAN RADIO TIPE SOUNESS SNI 4250." Jurnal Sistem Teknik Industri 20, no. 1 (2018): 40–47. http://dx.doi.org/10.32734/jsti.v20i1.383.

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Production system take an important role in industries, especially in manufacturing industries. This role determine the keys of successful company. Production process is an activity which produce finished product from raw material that involve machine, energy, and technique knowledge. Production process is real activity and can be seen by human being. The problems those always be faced in indutries management’s are the arrangement of production schedule, such lack of inventory or overstock once the settlement of production process isn’t on time. Production planning and control is activity to d

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4

Stockton, D. J., and L. Quinn. "Aggregate Production Planning Using Genetic Algorithms." Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture 209, no. 3 (1995): 201–9. http://dx.doi.org/10.1243/pime_proc_1995_209_074_02.

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An aggregate plan is a statement of future resources and finished goods inventory levels that must be made available to enable a manufacturing organization to meet its forecast sales demand. The aggregate planning process must enable the strategic business objectives of a manufacturing organization to be quickly converted into short-term operational plans that are economical to implement. This link between strategy and the day-to-day activities of an organization is becoming increasingly important in enabling organizations to cope with the faster rate at which business objectives must be chang

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5

Bushuev, Maxim. "Convex optimisation for aggregate production planning." International Journal of Production Research 52, no. 4 (2013): 1050–58. http://dx.doi.org/10.1080/00207543.2013.831998.

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6

PENLESKY, RICHARD J., and RAJESH SRIVASTAVA. "Aggregate production planning using spreadsheet software." Production Planning & Control 5, no. 6 (1994): 524–32. http://dx.doi.org/10.1080/09537289408919526.

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7

Shen, Randolph F. C. "Aggregate production planning by stochastic control." European Journal of Operational Research 73, no. 2 (1994): 346–59. http://dx.doi.org/10.1016/0377-2217(94)90270-4.

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8

Nam, Sang-jin, and Rasaratnam Logendran. "Modified production switching heuristics for aggregate production planning." Computers & Operations Research 22, no. 5 (1995): 531–41. http://dx.doi.org/10.1016/0305-0548(94)00034-6.

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9

WANG, Jing, Nobuto NAKAMURA, and Tetsuro SHlNGU. "A study of aggregate production planning in an uncertain production situation. The performance of typical aggregate production planning methods." Transactions of the Japan Society of Mechanical Engineers Series C 54, no. 504 (1988): 1983–89. http://dx.doi.org/10.1299/kikaic.54.1983.

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10

Leseure, Michel. "From Aggregate Production Planning to Aggregate Energy Industrial Consumption Plans." Energies 17, no. 24 (2024): 6388. https://doi.org/10.3390/en17246388.

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The increasing use of renewable energy sources in national electricity networks is challenging because of intermittence, i.e., the fact that the availability of the fuel (e.g., solar irradiance, wind) is volatile. This is a new challenge for the energy sector that has led to much research about energy storage. In the manufacturing sector, dealing with the volatility of demand is not a new problem and is addressed by the application of aggregate production planning techniques. Solving an aggregate production planning problem is about finding the best trade-off because capacity and inventory uti

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11

BEHNEZHAD, ALI R., and BEHROKH KHOSHNEVIS. "Integration of machine requirements planning and aggregate production planning." Production Planning & Control 7, no. 3 (1996): 292–98. http://dx.doi.org/10.1080/09537289608930355.

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12

Wang, Shih-Chang, and Ming-Feng Yeh. "Applying Differential Evolution to Aggregate Production Planning." Universal Journal of Industrial and Business Management 2, no. 7 (2014): 164–72. http://dx.doi.org/10.13189/ujibm.2014.020704.

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13

A. Gasim, Monim. "Aggregate Production Planning Using Goals Programming(ENG)." AL-Rafdain Engineering Journal (AREJ) 21, no. 3 (2013): 78–89. http://dx.doi.org/10.33899/rengj.2013.75564.

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14

Lin, Tsung-Ming, and Tien-Fu Liang. "AGGREGATE PRODUCTION PLANNING WITH MULTIPLE FUZZY GOALS." Journal of the Chinese Institute of Industrial Engineers 19, no. 4 (2002): 39–47. http://dx.doi.org/10.1080/10170660209509211.

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15

Rosen, L. Drew, and Cem Canel. "Aggregate production planning — a multiple objective approach." Journal of Statistics and Management Systems 12, no. 2 (2009): 287–303. http://dx.doi.org/10.1080/09720510.2009.10701390.

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16

Akinc, Umit, and Gary M. Roodman. "A New Approach to Aggregate Production Planning." IIE Transactions 18, no. 1 (1986): 88–94. http://dx.doi.org/10.1080/07408178608975334.

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17

Pradenas, Lorena, Fernando Peñailillo, and Jacques Ferland. "Aggregate production planning problem. A new algorithm." Electronic Notes in Discrete Mathematics 18 (December 2004): 193–99. http://dx.doi.org/10.1016/j.endm.2004.06.031.

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18

Wang, Reay-Chen, and Tien-Fu Liang. "Aggregate production planning with multiple fuzzy goals." International Journal of Advanced Manufacturing Technology 25, no. 5-6 (2004): 589–97. http://dx.doi.org/10.1007/s00170-003-1885-6.

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19

Ward, T. L., P. A. S. Ralston, and J. A. Davis. "Fuzzy logic control of aggregate production planning." Computers & Industrial Engineering 23, no. 1-4 (1992): 137–40. http://dx.doi.org/10.1016/0360-8352(92)90082-u.

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20

Oliff, Michael D., Holly S. Lewis, and Robert E. Markland. "Aggregate planning in crew-loaded production environments." Computers & Operations Research 16, no. 1 (1989): 13–25. http://dx.doi.org/10.1016/0305-0548(89)90048-8.

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21

Rosyidi, Moh Ririn, and Fitri Fairus Zabadi. "Perencanaan Produksi pada Produk Hollow dengan Ukuran 15 mm X 35 mm X 0.30 mm." Jurnal Rekayasa Sistem Industri 8, no. 1 (2019): 27–38. http://dx.doi.org/10.26593/jrsi.v8i1.3099.27-38.

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PT Mulcindo is a manufacturing and service industry company works in the production of processed iron. This company produces corrugated steel sheet, iron canal, ceiling hanging guard rail, and partition frame. However, the demand for this company was fluctuating. Due to this fluctuation, PT Mulcindo Steel Industry has some problems such as product shortages or on the other hand product overload (over stock). This company is trying to find better production activities planning to fulfill market demand by using the right production planning. The results of the aggregate planning method in planni

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22

Dai, L., L. Fan, and L. Sun. "AGGREGATE PRODUCTION PLANNING UTILIZING A FUZZY LINEAR PROGRAMMING." Journal of Integrated Design and Process Science: Transactions of the SDPS, Official Journal of the Society for Design and Process Science 7, no. 4 (2003): 81–95. http://dx.doi.org/10.3233/jid-2003-7407.

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Uncertainties and imprecise information regarding customer demands, production, inventory, and MRP are very common in performing aggregate production-planning (APP) for the manufacturing in real world. This study presents a fuzzy linear programming approach for managing the uncertainties and imprecise information involved in industrial APP applications. Detailed discussions are given to the establishment of the Fuzzy Linear Programming approach with converting the fuzzy constraints of uncertain and imprecise items into deterministic equivalents. A mathematical model is developed for APP practi

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23

Kurniawan, Shelvy, and Steven Sanjaya Raphaeli. "Optimizing Production Process through Production Planning and Inventory Management in Motorcycle Chains Manufacturer." ComTech: Computer, Mathematics and Engineering Applications 9, no. 2 (2018): 43. http://dx.doi.org/10.21512/comtech.v9i2.4723.

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Based on the data, there were still shortages of production from year to year and demand wereunstable in motorcycle chains manufacturer in Indonesia. To overcome these problems, the purpose of this research was to make production planning and inventory control consisting of forecasting, aggregate planning, Master Production Schedule (MPS), and Material RequirementsPlanning (MRP). Forecasting used the additive decomposition method (average of all data), multiplicative decomposition (centered on moving average), and winter method (additive and multiplicative). Aggregate planning used chase strat

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24

Magdalena, Riana. "Analysis of the Aggregate Heuristic Planning for Planning and Controlling the Amount of Production to Minimize Costs." Operations Research: International Conference Series 1, no. 1 (2020): 1–12. http://dx.doi.org/10.47194/orics.v1i1.18.

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PT.XYZ is one of the companies engaged in the automotive manufacturing industy, where it produces spare parts for cars, motorcycles and trucks. Along with marketing and producing the products, PT.XYZ continues to implement customer satisfaction and the quality of spare parts produced. The company must anticipate the possibility of production capacity limitations; this must be done as well as possible at the minimum cost. For that, the aggregate heuristic planning is proposed for planning the establishment of a level for production capacity to meet the level of demand obtained from orders with

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25

Miranda-Meza, Erick, Iván Derpich, and Juan M. Sepúlveda. "An Icon-Based Methodology for the Design of a Prototype of a Multi-Process, Multi-Product, Aggregated Production Planning Software." Mathematics 12, no. 2 (2024): 336. http://dx.doi.org/10.3390/math12020336.

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This paper proposes an icon-based methodology for the design of prototype aggregated production planning software that addresses the complexity of multi-process and multi-product production. Aggregate planning is a critical task in production management, which involves coordinating the production of multiple products in different processes to meet demand efficiently. The approach focuses on the use of visual icons to represent key elements of the production process, such as products, processes, resources, and constraints. These icons allow an intuitive representation of information and facilit

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26

Rizqi, Zakka Ugih, Tommy Aries Kurniawan, and Adinda Khairunisa. "Application of Fuzzy Time Series (FTS) Algorithm in Production Planning of Indonesia’s Oil Refining Company." Indonesian Scholars Scientific Summit Taiwan Proceeding 3 (July 11, 2021): 16–23. http://dx.doi.org/10.52162/3.2021108.

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Forecasting and aggregate planning are crucial phases in production planning especially for oil refining company that takes expensive production cost. Accurate forecasting greatly influences the success of production planning since it is the starting point of production planning. Whereas aggregate planning becomes important because it functions to bridge between the demand or production target with the existing resource requirements. Seeing the importance of accurate forecasting and aggregate planning, this research emphasizes the use of Fuzzy Time Series (FTS) Algorithm to forecast Premium sa

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27

YÜCESAN, Melih, and Hilmi ZENGİN. "APPLICATION OF AGGREGATE PRODUCTION PLANNING IN A FIRM." INTERNATIONAL REFEREED JOURNAL OF RESEARCH ON ECONOMICS MANAGEMENT, no. 9 (September 30, 2016): 25. http://dx.doi.org/10.17373/uheyad.2016922040.

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28

Ketviriyakit, Chatchaphon, Lakkana Ruekkasaem, Supalux Jairueng, and Phamorn Silapan. "Aggregate Production Planning of Galangal Manufacturing in Thailand." International Journal of Engineering Trends and Technology 70, no. 7 (2022): 122–29. http://dx.doi.org/10.14445/22315381/ijett-v70i7p213.

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29

Prakash, Satya, Gunjan Soni, Vipul Jain, Gaurav Kumar Badhotiya, and Murari Lal Mittal. "Multisite aggregate production and distribution planning: a review." International Journal of Enterprise Network Management 9, no. 3/4 (2018): 407. http://dx.doi.org/10.1504/ijenm.2018.094680.

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30

Prakash, Satya, Gunjan Soni, Vipul Jain, Gaurav Kumar Badhotiya, and Murari Lal Mittal. "Multisite aggregate production and distribution planning: a review." International Journal of Enterprise Network Management 9, no. 3/4 (2018): 407. http://dx.doi.org/10.1504/ijenm.2018.10015859.

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31

RUSSELL, ROBERT. "Decision support for multi-family aggregate production planning." Production Planning & Control 4, no. 1 (1993): 35–45. http://dx.doi.org/10.1080/09537289308919417.

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32

FEIRING, BRUCE R., and RAYMOND MAK. "Linking aggregate production planning with marketing pricing decisions." Production Planning & Control 6, no. 2 (1995): 170–75. http://dx.doi.org/10.1080/09537289508930266.

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33

Silva, Joao Paulo, Joao Lisboa, and Philip Huang. "A labour-constrained model for aggregate production planning." International Journal of Production Research 38, no. 9 (2000): 2143–52. http://dx.doi.org/10.1080/002075400188546.

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34

Oliff, Michael D., and G. Keong Leong. "A DISCRETE PRODUCTION SWITCHING RULE FOR AGGREGATE PLANNING." Decision Sciences 18, no. 4 (1987): 582–97. http://dx.doi.org/10.1111/j.1540-5915.1987.tb01548.x.

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35

Tang, Jiafu, Dingwei Wang, and Richard Y. K. Fung. "Fuzzy formulation for multi-product aggregate production planning." Production Planning & Control 11, no. 7 (2000): 670–76. http://dx.doi.org/10.1080/095372800432133.

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36

Tang, Jiafu, Richard Y. K. Fung, and Kai-Leung Yung. "Fuzzy modelling and simulation for aggregate production planning." International Journal of Systems Science 34, no. 12-13 (2003): 661–73. http://dx.doi.org/10.1080/00207720310001624113.

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37

Abu Bakar, Mohd Rizam, Abdul Jabbar Khudhur Bakheet, Farah Kamil, Bayda Atiya Kalaf, Iraq T. Abbas, and Lee Lai Soon. "Enhanced Simulated Annealing for Solving Aggregate Production Planning." Mathematical Problems in Engineering 2016 (2016): 1–9. http://dx.doi.org/10.1155/2016/1679315.

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Simulated annealing (SA) has been an effective means that can address difficulties related to optimisation problems.SAis now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multiobjective linear programming model for APP and optimised bySA. During the course of optimising for the APP problem, it uncovered that the capability ofSAwas inadequate and its performance was substandard, particularly for a

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38

Aucamp, D. C. "Closing the marketing loop in aggregate production planning." Applied Mathematical Modelling 10, no. 1 (1986): 57–60. http://dx.doi.org/10.1016/0307-904x(86)90010-7.

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39

Baykasoglu, Adil, and Tolunay Gocken. "Multi-objective aggregate production planning with fuzzy parameters." Advances in Engineering Software 41, no. 9 (2010): 1124–31. http://dx.doi.org/10.1016/j.advengsoft.2010.07.002.

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40

Hafezalkotob, Ashkan, Samaneh Chaharbaghi, and Tahmineh Moradi Lakeh. "Cooperative aggregate production planning: a game theory approach." Journal of Industrial Engineering International 15, S1 (2019): 19–37. http://dx.doi.org/10.1007/s40092-019-0303-0.

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41

Wang, Reay-Chen, and Tien-Fu Liang. "Applying possibilistic linear programming to aggregate production planning." International Journal of Production Economics 98, no. 3 (2005): 328–41. http://dx.doi.org/10.1016/j.ijpe.2004.09.011.

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42

Tian, Xueying, Yasser Mohamed, and Simaan AbouRizk. "Simulation-based aggregate planning of batch plant operations." Canadian Journal of Civil Engineering 37, no. 10 (2010): 1277–88. http://dx.doi.org/10.1139/l10-071.

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Production and supply of construction materials plays a significant role in the delivery of constructed facilities, especially for concrete and asphalt batch plants. The construction material (e.g., concrete) supply chain presents unique challenges, but is a key factor in successfully delivering facilities. This paper presents the development and application of a simulation-based aggregate planning approach that facilitates modeling and coordination of a batch plant’s supply chain. The tool is applied to a real case of asphalt production operations, where fluctuating demand affects the service

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43

Last, Kabbwelu Himayumbula, and Getrude Mwanza Bupe. "The Effect of Production Planning Practices on Supply Chain Performance: A Case Study of Corteva Agriscience (Z) Ltd." Management Journal for Advanced Research 4, no. 4 (2024): 68–77. https://doi.org/10.5281/zenodo.13368647.

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This Paper investigates the effects of production planning practices on supply chain performance at Corteva Agriscience Zambia, utilizing a case study approach with 60 actively involved employees. The study identifies key production planning practices in use which including Capacity Planning, Aggregate Planning, Operational Planning, Production Scheduling, Inventory Management, and Demand Planning & Forecasting, revealing their widespread adoption. It also examines how these practices assess supply chain performance. A multiple linear regression analysis is performed to gauge their impact,

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44

Pramodya Utami, Anak Agung Istri Riska, and Kastawan Mandala. "Analisis Perencanaan Produksi Agregat pada CV. Pelangi Rex’s di Denpasar." Ekonomis: Journal of Economics and Business 8, no. 1 (2024): 282. http://dx.doi.org/10.33087/ekonomis.v8i1.1337.

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The production function in every company has a very important role in developing a business, especially in the industrial sector. This study aims to determine the aggregate production planning strategy that has the lowest cost at CV. Rainbow Rex's. This type of research uses a quantitative descriptive approach. Data collection methods used are interviews and observation. Data analysis techniques are performed by forecasting demand using the Moving Average and Exponential Smoothing Methods, and the aggregate planning methods used are the Chase Strategy, Level Strategy, and Mixed Strategy. Based

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45

Dwitami, Fadila Antovi, and Sukanta. "Analysis of Aggregate Planning with a Chase Strategy Approach to Reduce Production Costs." JKIE (Journal Knowledge Industrial Engineering) 9, no. 1 (2022): 43–51. https://doi.org/10.35891/jkie.v9i1.2924.

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In Indonesia, there are already many established companies. Starting from a more focused industry/manufacturing, services, and trade. Many companies are starting to look for ways to increase the company's profits. The manufacturing industry sector itself certainly spends a lot on production. Therefore, the company is looking for a method that can minimize production costs. The purpose of this study is to minimize production costs. The method used is the aggregate chase strategy method. The results showed that planning using the aggregate chase strategy method can minimize production costs. Aft

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46

Rashidi, Maria, Alireza Joshaghani, and Maryam Ghodrat. "Towards Eco-Flowable Concrete Production." Sustainability 12, no. 3 (2020): 1208. http://dx.doi.org/10.3390/su12031208.

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Environmental concerns have increased due to the amount of unused/expired plastic medical waste generated in hospitals, laboratories, and other healthcare facilities, in addition to the fact that disposing of such wastes with extremely low degradation levels causes them to remain in the environment for extended periods of time. These issues have led researchers to develop more environmentally friendly alternatives for disposing of plastic medical waste in Australia. This study is an attempt to assess the impacts of using expired plastic syringes as fine aggregate on fresh and hardened characte

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47

Nugraha, I., M. Hisjam, and W. Sutopo. "Aggregate Planning Method as Production Quantity Planning and Control to Minimizing Cost." IOP Conference Series: Materials Science and Engineering 943 (November 3, 2020): 012045. http://dx.doi.org/10.1088/1757-899x/943/1/012045.

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48

Davizón, Yasser, César Martínez-Olvera, Rogelio Soto, Carlos Hinojosa, and Piero Espino-Román. "Optimal Control Approaches to the Aggregate Production Planning Problem." Sustainability 7, no. 12 (2015): 16324–39. http://dx.doi.org/10.3390/su71215819.

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49

Attia, E., A. Megahed, S. Baioumy, A. Elbetar, and P. Duquenne. "AGGREGATE PRODUCTION PLANNING CONSIDERING PERFORMANCE EVOLUTION: A CASE STUDY." International Conference on Applied Mechanics and Mechanical Engineering 17, no. 17 (2016): 1–16. http://dx.doi.org/10.21608/amme.2016.35291.

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50

Chen, Zhixiang, and Bhaba R. Sarker. "Aggregate production planning with learning effect and uncertain demand." Journal of Modelling in Management 10, no. 3 (2015): 296–324. http://dx.doi.org/10.1108/jm2-12-2012-0044.

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