ارائه مدل انتخاب تأمین کننده و تخصیص سفارش و توسعه الگوریتم سه بعدی فوردیس-وبستر با در نظر گرفتن کمبود (مطالعه موردی: شرکت تولید کننده کلید های برق فشار قوی)

نوع مقاله: مقاله پژوهشی

نویسندگان

1 دانشکده مهندسی صنایع و سیستم ها، دانشگاه تربیت مدرس، تهران، ایران

2 دانشیار مهندسی صنایع، دانشکده مهندسی صنایع و سیستم‌ها، دانشگاه تربیت مدرس، تهران، ایران.

چکیده

هزینه‌های تأمین مواد اولیه بیشتر از 60 درصد قیمت تمام‌شده یک محصول را در یک سازمان تشکیل می‌دهد. به همین جهت نحوه برنامه‌ریزی تأمین مواد اولیه از اهمیت قابل ملاحظه‌ای در کاهش هزینه‌های تمام‌شده، برخوردار است. مدیریت تأمین‌کنندگان یکی از بخش‌های مهم در مدیریت زنجیره تأمین است. بسیاری از شرکت‌ها مقدار قابل توجهی از درآمد خود را صرف خرید از تأمین‌کنندگان می‌کنند. از این رو انتخاب تأمین‌کننده یکی از وظایف مهم در مدیریت خرید است. هدف این تحقیق ارائه یک مدل ریاضی خطی عدد صحیح برای انتخاب تأمین‌کننده و تخصیص سفارش با در نظر گرفتن کمبود و همچنین حل مدل با استفاده از الگوریتم سه بعدی فوردیس- وبستر می‌باشد. در این تحقیق برای اولین بار هزینه کمبود تا حداکثر 1 دوره، به الگوریتم سه بعدی فوردیس- وبستر اضافه شده است. به منظور سنجش کارایی مدل پیشنهادی، داده‌های یک شرکت تولید‌کننده کلید‌های برق فشار قوی و داده‌های دو مثال دیگر بر روی مدل ارائه‌شده اعمال شده و مدل از نظر "تغییر نسبت هزینه نگهداری و هزینه کمبود" و "تعداد تأمین‌کنندگان و تعداد دوره‌ها" مورد بررسی قرار گرفته است. در آخر هم جهت حل مدل، هزینه کمبود تا حداکثر 1 دوره، به الگوریتم سه بعدی فوردیس-وبستر اضافه شده است.

کلیدواژه‌ها


عنوان مقاله [English]

Providing a model for supplier selection and order allocation and developing of Three Dimensional Fordyce-Webster Algorithm with shortage(Case Study: a high-voltage switches company)

نویسندگان [English]

  • Sahar Abuzari 1
  • Nasim Nahavandi 2
1 Faculty of Industrial and Systems Engineering , Tarbiat Modares University, Tehran, Iran.
2 Associate Professor of Industrial Engineering, Faculty of Industrial Engineering and Systems, Tarbiat Modares University, Tehran, Iran.
چکیده [English]

Raw materials supply costs form more than 60 percent of the price of a product in an organization. Therefore, the raw material supply planning has considerable effect in reducing the cost. Supplier management is one of the most important parts in supply chain management. Most of firms have been spending considerable amount of their revenues on purchasing. Hence supplier selection is one of the most important functions of purchasing management. The aim of this research is providing a linear integer mathematical model for supplier selection and order allocation with shortage and solving the model with three dimensional Fordyce–Webster Algorithm. In this research for the first time, maximum once period backorder cost is added to the three dimensional Fordyce–Webster Algorithm. In order to measuring performance of the proposed model, a high-voltage switches company's data and data from two other examples have been applied to the proposed model and the model has been studied in terms of " changing the ratio of holding cost and backorder cost" and " number of suppliers and number of time period". Finally, to solve the model, maximum once period backorder cost is added to the three dimensional Fordyce–Webster Algorithm.

کلیدواژه‌ها [English]

  • Suppler selection
  • Order Allocation
  • Inventory planning
  • three dimensional Fordyce–Webster Algorithm
  • Shortage
[1]      Hadian, Hengameh., Suppliers selection and allocation of orders in discount conditions in a supply chain system using Multiple Attribute Decision Making methods, Master of Science thesis, Sharif University of Technology, 2009 .(In Persian)

[2]      Aissaoui, N., Haouari, M. &  Hassini, E., Supplier selection and order lot sizing modeling: A review, Computers & Operations Research, 34, 2007, 3516-3540.

[3]      Hou, J. & Su, D., EJB‐MVC oriented supplier selection system for mass customization, Journal of Manufacturing Technology Management, 18, 2007, 54-71.

[4]      You, X.-Y.,  You, J. -X.,  Liu, H.-C. & Zhen, L., Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information, Expert Systems with Applications, 42, 2015, 1906-1916.

[5]      Moghaddam, K. S., Fuzzy multi-objective model for supplier selection and order allocation in reverse logistics systems under supply and demand uncertainty, Expert Systems with Applications, 42, 2015, 6237-6254.

[6]      Beikkhakhian, Y., Javanmardi, M., Karbasian, M. & Khayambashi, B., The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods, Expert Systems with Applications, 42, 2015, 6224-6236.

[7]      Moqri, M. M., Moshref Javadi, M. & Yazdian, S. A., Supplier selection and order lot sizing using dynamic programming, International Journal of Industrial Engineering Computations, 2, 2011, 319-328.

[8]       Kar, A. K., A hybrid group decision support system for supplier selection using analytic hierarchy process, fuzzy set theory and neural network, Journal of Computational Science, 6, 2015,23-33.

[9]       Amorim, p., Curcio, E., Almada-Lobo, B., Barbosa-Póvoa, A. P. F. D. & Grossmann, I. E., Supplier selection in the processed food industry under uncertainty, European Journal of Operational Research, 252, 2016, 801-814.

[10]   Luthra, S., Govindan, K., Kannan, D., Mangla, S. K. & Garg, C. P., An integrated framework for sustainable supplier selection and evaluation in supply chains, Journal of Cleaner Production, 140, 2017, 1686-1698.

[11]  Mirzaee,  H., Naderi, B. & Pasandideh, S.H.R., A preemptive fuzzy goal programming model for generalized supplier selection and order allocation with incremental discount, Computers & Industrial Engineering, 122, 2018, 292-302.

[12]  Govindan, K., Shankar, M. & Kannan, D., Supplier selection based on corporate social responsibility practices, International Journal of Production Economics,  200, 2018, 353-379.

[13]   Mazdeh, M. M., Emadikhiav, M. & Parsa, I., A heuristic to solve the dynamic lot sizing problem with supplier selection and quantity discounts, Computers & Industrial Engineering, 85, 2015, 33-43.

[14]  Babaee, L., Rabieh, M., Nikbakhsh, E. & Esmaeili, M., Multi- objective mathematical model for green supplier selection (case study: supply chain of IRAN KHODRO company), Journal of Modern Research in Decision Making, 2, 2017, 51-83. (In Persian)

[15]  Bagherzadeh Azar, M. & Dori, B., Applying ANP in selecting the best supplier in supply chain, Journal of Management Research in Iran, 14, 2011, 27-47. (In Persian)

[16]  Bottani, E. & Rizzi, A.,  An adapted multi-criteria approach to suppliers and products selection—An application oriented to lead-time reduction,  International Journal of Production Economics, 111, 2008, 763-781.

[17]   Shil, N. C., Customized Supplier Selection Methodology: An Application of Multiple Regression Analysis ,  Supply Chain Forum: an International Journal, 11, 2010, 58-70.

[18]   Sadeghi Moghadam, M. R., Afsar, A. & Sohrabi, B., Inventory lot-sizing with supplier selection using hybrid intelligent algorithm, Applied Soft Computing, 8, 2008, 1523-1529.

[19]   Yang, P. C., Wee, H. M., Pai, S. & Tseng, Y. F., Solving a stochastic demand multi-product supplier selection model with service level and budget constraints using Genetic Algorithm, Expert Systems with Applications, 38, 2011, 14773-14777.

[20]   Chang, B. & Hung, H.-F., A study of using RST to create the supplier selection model and decision-making rules, Expert Systems with Applications, 37, 2010, 8284-8295.

[21]  Taghavifard, S. M. T., Dehghani, M. H. & Aghaei, M., The model for lot sizing problem with supplier selection and solving by NSGA-II (case study: Morvarid Panberiz company), Journal of Management Research in Iran, 19, 2015, 65-89. (In Persian)

[22]   Olfat, L. & Esmaeili, M., Evaluation, selection and performance management of logistics services providers (case study: Sapco), Journal of Modern Research in Decision Making, 4, 2019, 181-203. (In Persian)

[23]  Grewal, Harpreet., Analysis of inventory lot size problem, Master of Science thesis, University of Manitoba, 1999.