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Theory of constraints driven approach to tackle product mix problem with joint material | ||
Computational Sciences and Engineering | ||
مقاله 5، دوره 3، شماره 1، تیر 2023، صفحه 77-89 اصل مقاله (368.34 K) | ||
نوع مقاله: Original Article | ||
شناسه دیجیتال (DOI): 10.22124/cse.2024.27396.1076 | ||
نویسنده | ||
Seyed Amin Badri* | ||
University of Guilan | ||
چکیده | ||
Determining the type and quantity of products to produce holds critical significance in multi-product manufacturing systems. This problem has been named the product mix problem. Several heuristics have been frequently applied to solve the product mix problems. The previous heuristics lead to ineffective decisions when joint material costs are allocated to single products. This paper seeks to establish a new constructive heuristic derived from the theory of constraints (TOC) to tackle problem of product mix with joint material. A comparison is done between the traditional TOC-based approach, modified TOC-based approach, integer linear programming, and proposed constructive heuristic. The provided numerical example illustrates the reasonableness and applicability of the proposed method. | ||
کلیدواژهها | ||
Product mix decision؛ TOC methodology؛ Optimization؛ Mathematical modeling؛ Multi-product manufacturing systems | ||
مراجع | ||
[1] Karakas, E., Koyuncu, M., Erol, R., & Kokangul, A. (2010). Fuzzy programming for optimal product mix decisions based on expanded ABC approach. International Journal of Production Research, 48(3), 729-744. [2] Chaharsooghi, S. K., & Jafari, N. (2007). A simulated annealing approach for product mix decisions. Scientia Iranica, 14(3), 230-235. [3] De Souza, F. B., Sobreiro, V. A., Nagano, M. S., & de Souza Manfrinato, J. W. (2013). When less is better: Insights from the product mix dilemma from the Theory of Constraints perspective. International Journal of Production Research, 51(19), 5839-5852. [4] Ray, A., Sarkar, B., & Sanyal, S. (2010). The TOC-based algorithm for solving multiple constraint resources. Engineering Management, IEEE Transactions on, 57(2), 301-309. [5] Linhares, A. (2009). Theory of constraints and the combinatorial complexity of the product-mix decision. International Journal of Production Economics, 121(1), 121-129. [6] Sobreiro, V. A., & Nagano, M. S. (2012). A review and evaluation on constructive heuristics to optimise product mix based on the Theory of Constraints. International Journal of Production Research, 50(20), 5936-5948. [7] Sobreiro, V. A., Mariano, E. B., & Nagano, M. S. (2014). Product mix: the approach of throughput per day. Production Planning & Control, 25(12), 1015-1027. [8] Goldratt, E. M. (1990). The haystack syndrome: Sifting information from the data ocean. New York, North River. [9] Souren, R., Ahn, H., & Schmitz, C. (2005). Optimal product mix decisions based on the theory of constraints? Exposing rarely emphasized premises of throughput accounting. International Journal of Production Research, 43(2), 361-374. [10] Goldratt, E. M. (1990b). Theory of Constraints: What is this thing called the Theory of Constraints and how should it be implemented. Croton-on-Hudson, North River, New York. [11] Aryanezhad, M. B., Badri, S. A., & Rashidi Komijan, A. (2010). Threshold-based method for elevating the system's constraint under theory of constraints. International Journal of Production Research, 48(17), 5075-5087. [12] Badri, S. A., & Aryanezhad, M. B. (2011). A mathematical method for managing the system constraint. International Journal of Engineering-Transactions A: Basics, 24(1), 37-47. [13] Hsu, T. C., & Chung, S. H. (1998). The TOC-based algorithm for solving product mix problems. Production planning & control, 9(1), 36-46. [14] Luebbe, R., & Finch, B. (1992). Theory of constraints and linear programming: a comparison. THE International Journal of Production Research, 30(6), 1471-1478. [15] Patterson, M. C. (1992). The product-mix decision: a comparison of theory of constraints and labor-based management accounting. Production and Inventory Management Journal, 33, 80-80. [16] Balakrishnan, J., & Cheng, C. H. (2000). Discussion: Theory of constraints and linear programming: A re-examination. International Journal of Production Research, 38(6), 1459-1463. [17] Finch, B. J., & Luebbe, R. L. (2000). Response to 'Theory of constraints and linear programming: a re-examination'. International Journal of Production Research, 38(6), 1465-1466. [18] Lee, T. N., & Plenert, G. (1993). Optimizing theory of constraints when new product alternatives exist. Production and Inventory Management Journal, 34, 51-51. [19] Plenert, G. (1993). Optimizing theory of constraints when multiple constrained resources exist. European Journal of Operational Research, 70(1), 126-133. [20] Fredendall, L. D., & Lea, B. R. (1997). Improving the product mix heuristic in the theory of constraints. International Journal of Production Research, 35(6), 1535-1544. [21] Onwubolu, G. C. (2001). Tabu search-based algorithm for the TOC product mix decision. International Journal of Production Research, 39(10), 2065-2076. [22] Onwubolu, G. C., & Mutingi, M. (2001a). Optimizing the multiple constrained resources product mix problem using genetic algorithms. International Journal of Production Research, 39(9), 1897-1910. [23] Onwubolu, G. C., & Mutingi, M. (2001b). A genetic algorithm approach to the theory of constraints product mix problems. Production Planning & Control, 12(1), 21-27. [24] Aryanezhad, M. B., & Komijan, A. R. (2004). An improved algorithm for optimizing product mix under the theory of constraints. International Journal of Production Research, 42(20), 4221-4233. [25] Mishra, N., Tiwari, M. K., Shankar, R., & Chan, F. T. (2005). Hybrid tabu-simulated annealing based approach to solve multi-constraint product mix decision problem. Expert systems with applications, 29(2), 446-454. [26] Tsai, W. H., Lai, C. W., & Chang, J. C. (2007). An algorithm for optimizing joint products decision based on the Theory of Constraints. International journal of production research, 45(15), 3421-3437. [27] Bhattacharya, A., Vasant, P., Sarkar, B., & Mukherjee, S. K. (2008). A fully fuzzified, intelligent theory-of-constraints product-mix decision. International Journal of Production Research, 46(3), 789-815. [28] Wang, J. Q., Sun, S. D., Si, S. B., & Yang, H. A. (2009). Theory of constraints product mix optimisation based on immune algorithm. International Journal of Production Research, 47(16), 4521-4543. [29] Komijan, A. R., Aryanezhad, M. B., & Makui, A. (2009). A new heuristic approach to solve product mix problems in a multi-bottleneck system. Journal of Industrial Engineering International, 5(9), 46-57. [30] Tanhaei, F., & Nahavandi, N. (2013). Algorithm for solving product mix problem in two-constraint resources environment. The International Journal of Advanced Manufacturing Technology, 64(5-8), 1161-1167. [31] Rajesh, M. (2014). A Mixed Integer Linear Goal Programming Model for Optimizing Multiple Constrained Resources Product-Mix Problem Under the Theory of Constraints. IUP Journal of Operations Management, 13(1), 7-19. [32] Badri, S. A., Ghazanfari, M., & Shahanaghi, K. (2014). A multi-criteria decision-making approach to solve the product mix problem with interval parameters based on the theory of constraints. The International Journal of Advanced Manufacturing Technology, 70(5-8), 1073-1080. [33] Golmohammadi, D., & Mansouri, S. A. (2015). Complexity and workload considerations in product mix decisions under the theory of constraints. Naval Research Logistics (NRL), 62(5), 357-369. [34] Hadidi, L. A., & Moawad, O. A. (2017). The product-mix problem for multiple production lines in sequenced stages: a case study in the steel industry. The International Journal of Advanced Manufacturing Technology, 88(5-8), 1495-1504. [35] Mansouri, S. A., Golmohammadi, D., & Miller, J. (2019). The moderating role of master production scheduling method on throughput in job shop systems. International Journal of Production Economics, 216, 67-80. | ||
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