A Supply-Chain Production Inventory Model with Warehouse Facilities Under Fuzzy Environment

In reality, there are different types of supply-chain system for production. One such type may be that a producer purchases raw materials from several vendors and the finished products are sold to a retailer. The retailer may plan to procure in large quantity to avail the price discount, transportation advantage, etc., and adopt for warehouse facilities system-one warehouse at the market place from where sale is conducted and the other (if necessary) at a distance away from the market place from which the units are transported to the market warehouse (MW) continuously to keep MW full. This motivated us to take up the following three supply-chain production inventory models. In the first model, the above mentioned type two warehouse supply chain model (SCM) is considered with imprecise stock dependent demand and in this model the objective goal is assumed to be fuzzy. There are budget and space constraints which are also in fuzzy nature. The fuzziness are defuzzified following possibility, necessity and credibility measures. In the second model (i) nature of collection of raw-material is different; (ii) demand is increasing with time in a decreasing rate, (iii) selling price of the partial backlogging units depends on the waiting time of the customers. The model is formulated with defective production system and learning effect which is fuzzy in nature. Learning effect i.e., experience is introduced in reducing the defective rate in production. In last model, an integrated production-inventory model is presented for a supplier, manufacturer, and retailer supply chain under conditionally permissible delay in payments in uncertain environments. The supplier produces the item at a certain rate, which is a decision variable, and purchases the item to the manufacturer. The manufacturer has also purchased and produced the item in a finite rate. The manufacturer sells the product to the retailer and also gives the delay in payment to the retailer. The retailer purchases the item from the manufacture to sell it to the customers. Ideal costs of supplier, manufacturer, and retailer have been taken into account. The SCMs have been developed and solved analytically fuzzy environments, and finally, corresponding individual profits are calculated numerically and graphically.

[1]  Xiaojun Wang,et al.  A two-stage Fuzzy-AHP model for risk assessment of implementing green initiatives in the fashion supply chain , 2012 .

[2]  Yian-Kui Liu,et al.  Expected value of fuzzy variable and fuzzy expected value models , 2002, IEEE Trans. Fuzzy Syst..

[3]  K. M. Ragsdell,et al.  The Generalized Reduced Gradient Method: A Reliable Tool for Optimal Design , 1977 .

[4]  Manoranjan Maiti,et al.  A two warehouse inventory model for deteriorating items with a linear trend in demand and shortages , 1998, J. Oper. Res. Soc..

[5]  Turan Paksoy,et al.  A fuzzy linear programming model for the optimization of multi-stage supply chain networks with triangular and trapezoidal membership functions , 2012, J. Frankl. Inst..

[6]  Josefa Mula,et al.  Production , Manufacturing and Logistics A fuzzy linear programming based approach for tactical supply chain planning in an uncertainty environment , 2010 .

[7]  Hui-Ming Wee,et al.  Deteriorating item inventory model with shortage due to supplier in an integrated supply chain , 2004, Int. J. Syst. Sci..

[8]  Özgür Kabak,et al.  Possibilistic linear-programming approach for supply chain networking decisions , 2011, Eur. J. Oper. Res..

[9]  Roger Jianxin Jiao,et al.  Production, Manufacturing and Logistics Adaptive Fuzzy Vendor Managed Inventory Control for Mitigating the Bullwhip Effect in Supply Chains , 2022 .

[10]  O. Coskunoglu,et al.  A New Logit Model for Decision Making and its Application , 1985 .

[11]  K. S. Chaudhuri,et al.  An EOQ model for a deteriorating item with time dependent quadratic demand under permissible delay in payment , 2011, Appl. Math. Comput..

[12]  Przemyslaw Grzegorzewski,et al.  Nearest interval approximation of a fuzzy number , 2002, Fuzzy Sets Syst..

[13]  Manoranjan Maiti,et al.  Production , Manufacturing and Logistics Possibility and necessity constraints and their defuzzification — A multi-item production-inventory scenario via optimal control theory , 2006 .

[14]  Shian-Jong Chuu,et al.  Interactive group decision-making using a fuzzy linguistic approach for evaluating the flexibility in a supply chain , 2011, Eur. J. Oper. Res..

[15]  Manoranjan Maiti,et al.  Numerical Approach of Multi-Objective Optimal Control Problem in Imprecise Environment , 2005, Fuzzy Optim. Decis. Mak..

[16]  Manoranjan Maiti,et al.  Fuzzy inventory model with two warehouses under possibility constraints , 2006, Fuzzy Sets Syst..

[17]  S. Viswanathan,et al.  Coordinating supply chain inventories through common replenishment epochs , 2001, Eur. J. Oper. Res..

[18]  Juite Wang,et al.  Fuzzy decision modeling for supply chain management , 2005, Fuzzy Sets Syst..

[19]  K. K. Achary,et al.  A deterministic inventory model for deteriorating items with two warehouses and finite replenishment rate , 1992 .

[20]  K. Maity,et al.  Possibility and necessity representations of fuzzy inequality and its application to two warehouse production-inventory problem , 2011 .

[21]  Nejat Karabakal,et al.  Supply-Chain Analysis at Volkswagen of America , 2000, Interfaces.

[22]  S. Goyal Economic Order Quantity under Conditions of Permissible Delay in Payments , 1985 .

[23]  Paul H. Zipkin,et al.  Competitive and Cooperative Inventory Policies in a Two-Stage Supply Chain , 1999 .

[24]  Barun Das,et al.  A two warehouse supply-chain model under possibility/ necessity/credibility measures , 2007, Math. Comput. Model..

[25]  Isa Nakhai Kamal Abadi,et al.  Joint control of inventory and its pricing for non-instantaneously deteriorating items under permissible delay in payments and partial backlogging , 2012, Math. Comput. Model..

[26]  Cheng-Liang Chen,et al.  MULTI-CRITERIA FUZZY OPTIMIZATION FOR LOCATING WAREHOUSES AND DISTRIBUTION CENTERS IN A SUPPLY CHAIN NETWORK , 2007 .

[27]  Morris A. Cohen,et al.  The Stabilizing Effect of Inventory in Supply Chains , 1998, Oper. Res..

[28]  Baoding Liu,et al.  Chance constrained programming with fuzzy parameters , 1998, Fuzzy Sets Syst..

[29]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[30]  Vipul Agrawal,et al.  Dynamic balancing of inventory in supply chains , 2004, Eur. J. Oper. Res..

[31]  Shanlin Yang,et al.  A new variable production scheduling strategy for deteriorating items with time-varying demand and partial lost sale , 2003, Comput. Oper. Res..

[32]  Didier Dubois,et al.  Ranking fuzzy numbers in the setting of possibility theory , 1983, Inf. Sci..

[33]  Pisal Yenradee,et al.  Inventory/distribution control system in a one-warehouse/multi-retailer supply chain , 2008 .