Skip to main content
Log in

Retailer’s optimal replenishment policy in a two-echelon supply chain under two-part delay in payments and disruption in delivery

  • Original Article
  • Published:
International Journal of System Assurance Engineering and Management Aims and scope Submit manuscript

Abstract

Now-a-days, the risks associated with transportation have received special attention among the global traders due to the unusual circumstances such as terrorist attack, earth quake, mishandling in transport, shipping damage, misplacing products etc. A mathematical model for an inventory system under such transport risk conditions is highly useful to run the supply chain (SC) smoothly and it paves the way to minimize the total cost incurred. In business, many suppliers offer two-part delay in payments, say \( (\alpha /M_{1} ,{\text{ net }}M_{2} ) \), in order to attract their retailers. This paper investigates retailer’s inventory system in a SC under the random effect of risk in delivery from a supplier to the retailer. Here, the supplier offers two-part trade credit to his retailer and the retailer in turn offers a full credit period to the customers. The total cost incurred at the retailer’s inventory system is minimized and the optimal replenishment policies are determined. Mathematical theorems are developed and numerical examples are presented to illustrate the sensitivity analysis of inventory key parameters.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14

Similar content being viewed by others

References

  • Aggarwal SP, Jaggi CK (1995) Ordering policies of deteriorating items under permissible delay in payment. J Oper Res Soc 46:658–662

    Article  MATH  Google Scholar 

  • Atasoy B, Güllü R, Tan T (2012) Optimal inventory policies with non-stationary supply disruptions and advance supply information. Decis Support Syst 53:269–281

    Article  Google Scholar 

  • Pal B, Sana SS, Chaudhuri K (2012) A multi-echelon supply chain model for reworkable items in multiple-markets with supply disruption. Econ Model 29:1891–1898

    Article  Google Scholar 

  • Pal B, Sana SS, Chaudhuri K (2014) A multi-echelon production–inventory system with supply disruption. J Manuf Syst 33:262–276

    Article  Google Scholar 

  • Chang CT, Teng JT, Goyal SK (2008) Inventory lot-size models under trade credits: a review. Asia Pac J Oper Res 25:89–112

    Article  MathSciNet  MATH  Google Scholar 

  • Chang CT, Teng JT, Chern MS (2010) Optimal manufacturer’s optimal policies for deteriorating items in a supply chain with upstream and down stream trade credits. Int J Prod Econ 127:197–202

    Article  Google Scholar 

  • Chen LH, Kang FS (2010) Coordination between vendor and buyer considering trade credit and items of imperfect quality. Int J Prod Econ 123:52–61

    Article  Google Scholar 

  • Chen S-H, Cárdenas-Barrón LE, Teng JT (2013a) Retailer’s economic order quantity when the supplier offers conditionally permissible delay in payments link to order quantity. Int J Prod Econ. doi:10.1016/j.ijpe.2013.05.032 (in press)

  • Chen S-C, Chang C-T, Teng J-T (2013b) A comprehensive note on “Lot-sizing decisions for deteriorating items with two warehouses under an order-size-dependent trade credit”. Int Trans Oper Res (in press)

  • Chern M-S, Pan Q, Teng J-T, Chan Y-L, Chen S-C (2013) Stackelberg solution in a vendor–buyer supply chain model with permissible delay in payments. Int J Prod Econ 144(1):397–404

    Article  Google Scholar 

  • Chopra S, Reinhardt G, Mohan U (2007) The importance of decoupling recurrent and disruption risks in a supply chain. Naval Res Logist 54(5):544–555

    Article  MathSciNet  MATH  Google Scholar 

  • Chung KJ, Cárdenas-Barrón LE (2013) The simplified solution procedure for deteriorating items under stock-dependent demand and two-level trade credit in the supply chain management. Appl Math Model 37(7):4653–4660

    Article  MathSciNet  Google Scholar 

  • Chung KJ, Liao JJ (2011) The simplified solution algorithm for an integrated supplier–buyer inventory model with two-part trade credit in a supply chain system. Eur J Oper Res 213:156–165

    Article  MathSciNet  MATH  Google Scholar 

  • Eisenstein DD (2005) Recovering cyclic schedules using dynamic produce-up-to policies. Oper Res 53:675–688

    Article  MathSciNet  MATH  Google Scholar 

  • Feng H, Li J, Zhao D (2013) Retailer’s optimal replenishment and payment policies in the EPQ model under cash discount and two-level trade credit policy. Appl Math Model 37(5): 3322–3339

  • Fernquest J (2011) Floods hit auto and electronics exports. Bangkok Post, Bangkok

    Google Scholar 

  • Gallego G (1994) When is a base stock policy optimal in recovering disrupted cyclic schedules? Naval Res Logist 41:317–333

    Article  MATH  Google Scholar 

  • Giunipero LC, Eltantawy RA (2004) Securing the upstream supply chain: a risk management approach. Int J Phys Distrib Logist Manage 34:698–713

    Article  Google Scholar 

  • Goyal SK (1985) Economic order quantity under conditions of permissible delay in payments. J Oper Res Soc 36:335–338

    Article  MATH  Google Scholar 

  • Hishamuddin H, Sarker RA, Essam D (2012) A disruption recovery model for a single stage production–inventory system. Eur J Oper Res 222(3):464–473

    Article  MathSciNet  MATH  Google Scholar 

  • Hishamuddin H, Sarker RA, Essam D (2013) A recovery model for a two-echelon serial supply chain with consideration of transportation disruption. Comput Ind Eng 64(2):552–561

    Article  Google Scholar 

  • Ho CH, Ouyang LY, Su CH (2008) Optimal pricing, shipment and payment policy for an integrated supplier–buyer inventory model with two-part trade credit. Eur J Oper Res 187:496–510

    Article  MathSciNet  MATH  Google Scholar 

  • Huang YF (2003) Optimal retailer’s ordering policies in the EOQ model under trade credit financing. J Oper Res Soc 54:1011–1015

    Article  MATH  Google Scholar 

  • Huang YF (2007) Economic order quantity under conditionally permissible delay in payments. Eur J Oper Res 176:911–924

    Article  MATH  Google Scholar 

  • Huang YF, Chung KJ (2003) Optimal replenishment and payment policies in the EOQ model under cash discount and trade credit. Asia-Pac J Oper Res 20:90–177

    MathSciNet  MATH  Google Scholar 

  • Huang YF, Hsu KH (2008) An EOQ model under retailer partial trade credit policy in supply chain. Int J Prod Econ 112:655–664

    Article  Google Scholar 

  • Hwang H, Shinn SW (1997) Retailer’s pricing and lot sizing policy for exponentially deteriorating products under the condition of permissible delay in payments. Comput Oper Res 24:539–547

    Article  MATH  Google Scholar 

  • Jaggi CK, Goyal SK, Goel SK (2008) Retailer’s optimal replenishment decisions with credit-linked demand under permissible delay in payments. Eur J Oper Res 190:130–135

    Article  MATH  Google Scholar 

  • Jaggi CK, Kapur PK, Goyal SK, Goel SK (2012) Optimal replenishment and credit policy in EOQ model under two-levels of trade credit policy when demand is influenced by credit period. Int J Syst Assur Eng Manag 3(4):352–359. doi:10.1007/s13198-012-0106-9

    Article  Google Scholar 

  • Jaggi CK, Goel SK, Mittal M (2013) Credit financing in economic ordering policies for defective items with allowable shortages. Appl Math Comput 219:5268–5282

    MathSciNet  MATH  Google Scholar 

  • Jamal AMM, Sarker BR, Wang S (1997) An ordering policy for deteriorating items with allowable shortage and permissible delay in payment. J Oper Res Soc 48:826–833

    Article  MATH  Google Scholar 

  • Li Z, Xu SH, Hayya J (2004) A periodic-review inventory system with supply interruptions. Probab Eng Inf Sci 18(1):33–53

    Article  MathSciNet  MATH  Google Scholar 

  • Liao JJ (2008) An EOQ model with non-instantaneous receipt and exponentially deteriorating items under two-level trade credit. Int J Prod Econ 113:852–861

    Article  Google Scholar 

  • Liao JJ, Huang KN, Chung KJ (2012) Lot-sizing decisions for deteriorating items with two warehouses under an order-size-dependent trade credit. Int J Prod Econ 137:102–115

    Article  Google Scholar 

  • Mach Traci L, Wolken JD (2006) Financial services used by small businesses: evidence from the 2003 survey of small business finances. Fed Reserve Bull 167–195

  • Min J, Zhou YW, Zhao J (2010) An inventory model for deteriorating items under stock-dependent demand and two-level trade credit. Appl Math Model 34:3273–3285

    Article  MathSciNet  MATH  Google Scholar 

  • Mohebbi E (2003) Supply interruptions in a lost-sales inventory system with random lead time. Comput Oper Res 30(3):411–426

    Article  MATH  Google Scholar 

  • Mohebbi E (2004) A replenishment model for the supply-uncertainty problem. Int J Prod Econ 87(1):25–37

    Article  Google Scholar 

  • Mohebbi E, Hao D (2006) When supplier’s availability affects the replenishment lead time—an extension of the supply-interruption problem. Eur J Oper Res 175(2):992–1008

    Article  MATH  Google Scholar 

  • Ouyang L-Y, Chang C-T (2013) Optimal production lot with imperfect production process under permissible delay in payments and complete backlogging. Int J Prod Econ 144(2):610–617

    Article  Google Scholar 

  • Ouyang LY, Teng JT, Chuang KW, Chuang BR (2005) Optimal inventory policy with noninstantaneous receipt under trade credit. Int J Prod Econ 98:290–300

    Article  Google Scholar 

  • Ouyang L-Y, Yang C-T, Chan YL, Cárdenas-Barrón LE (2013) A comprehensive extension of the optimal replenishment decisions under two levels of trade credit policy depending on the order quantity. Appl Math Comput 224(1):268–277

    MathSciNet  MATH  Google Scholar 

  • Özekici S, Parlar M (1999) Inventory models with unreliable suppliers in a random environment. Ann Oper Res 91:123–136

    Article  MathSciNet  MATH  Google Scholar 

  • Parlar M, Berkin D (1991) Future supply uncertainty in EOQ models. Naval Res Logist 38:107–121

    Article  MathSciNet  MATH  Google Scholar 

  • Parlar M, Perry D (1996) Inventory models of future supply uncertainty with single and multiple suppliers. Naval Res Logist 43:191–210

    Article  MATH  Google Scholar 

  • Paul S, Sarker R, Essam D (2014) Real time disruption management for a two-stage batch production–inventory system with reliability considerations. Eur J Oper Res 237:113–128

    Article  MathSciNet  MATH  Google Scholar 

  • Qi X, Bard JF, Yu G (2004) Supply chain coordination with demand disruptions. Omega 32:301–312. doi:10.1016/j.omega.2003.12.002

    Article  Google Scholar 

  • Qi L, Shen ZJM, Snyder LV (2009) A continuous-review inventory model with disruptions at both supplier and retailer. Prod Oper Manag 18(5):516–532

    Article  Google Scholar 

  • Schmitt AJ, Snyder LV (2012) Infinite-horizon models for inventory control under yield uncertainty and disruptions. Comput Oper Res 39:850–862

    Article  MathSciNet  MATH  Google Scholar 

  • Schmitt AJ, Snyder LV, Shen ZJM (2010) Inventory systems with stochastic demand and supply: properties and approximations. Eur J Oper Res 206(2):313–328

    Article  MathSciNet  MATH  Google Scholar 

  • Shah NH (1993) Probabilistic time-scheduling model for an exponentially decaying inventory when delay in payment is permissible. Int J Prod Econ 32:77–82

    Article  Google Scholar 

  • Taleizadeh AA, Mohammadi B, Cárdenas-Barrón LE, Samimi H (2013) An EOQ model for perishable product with special sale and shortage. Int J Prod Econ 145(1):318–338

    Article  Google Scholar 

  • Teng JT (2002) On the economic order quantity under conditions of permissible delay in payments. J Oper Res Soc 53:915–918

    Article  MATH  Google Scholar 

  • Teng JT (2006) Discount cash-flow analysis on inventory control under various supplier’s trade credits. Int J Oper Res 3:23–29

    MATH  Google Scholar 

  • Teng JT (2009) Optimal ordering policies for a retailer who offers distinct trade credits to its good and bad credit customers. Int J Prod Econ 119:415–423

    Article  Google Scholar 

  • Teng JT, Chang CT (2009) Optimal manufacturer’s replenishment policies in the EPQ model under two levels of trade credit policy. Eur J Oper Res 195:358–363

    Article  MathSciNet  MATH  Google Scholar 

  • Teng JT, Goyal SK (2007) Optimal ordering policies for a retailer in a supply chain with up-stream and down-stream trade credits. J Oper Res Soc 58:1252–1255

    Article  Google Scholar 

  • Teng JT, Yang HL, Chern MS (2013) An inventory model for increasing demand under two levels of trade credit linked to order quantity. Appl Math Model 37:7624–7632

    Article  MathSciNet  Google Scholar 

  • Thangam A (2012) Optimal price discounting and lot-sizing policies for perishable items in a supply chain under advance payment scheme and two-echelon trade credits. Int J Prod Econ 139:459–472

    Article  Google Scholar 

  • Thangam A, Uthayakumar R (2009) Two-echelon trade credit financing for perishable items in a supply chain when demand depends on both credit period and selling price. Comput Ind Eng 57:773–786

    Article  Google Scholar 

  • Tomlin B (2006) On the value of mitigation and contingency strategies for managing supply chain disruption risks. Manage Sci 52(5):639–657

    Article  MathSciNet  MATH  Google Scholar 

  • Tsao YC (2009) Retailers optimal ordering and discounting policies advance sales discount and trade credits. Comput Ind Eng 56:208–215

    Article  Google Scholar 

  • Tsao YC (2011) Replenishment policies considering trade credit and logistics risk. Sci Iranica 18:753–758

    Article  Google Scholar 

  • Tsao YC, Sheen GJ (2012) A multi-item supply chain with credit periods and weight freight cost discounts. Int J Prod Econ 135:106–115

    Article  Google Scholar 

  • Wilson MC (2007) The impact of transportation disruptions on supply chain performance. Transp Res E 43:295–320. doi:10.1016/j.tre.2005.09.008

    Article  Google Scholar 

  • Xia Y, Yang M-H, Golany B, Gilbert SM, Yu G (2004) Real-time disruption management in a two-stage production and inventory system. IIE Trans 36:111–125

    Article  Google Scholar 

  • Zeynep Sargut F, Qi L (2012) Analysis of a two-party supply chain with random disruptions. Oper Res Lett 40:114–122

    Article  MathSciNet  MATH  Google Scholar 

  • Zhong YG, Zhou YW (2012) The model and algorithm for determining optimal ordering/trade-credit policy of supply chains. Appl Math Comput 219:3809–3825

    MathSciNet  MATH  Google Scholar 

  • Zhong YG, Zhou YW, Wahab MIM (2013) How to make the replenishment and payment strategy under flexible two-part trade credit. Comput Oper Res 40:1328–1338

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to A. Thangam.

Appendix 1

Appendix 1

1.1 Proof of Theorem 1

Before going to the proof for the statements in Theorem 1, we need the following as a preliminary.

We could observe that \( \frac{{d^{2} TC_{Ai} (T)}}{{dT^{2} }} > 0 \) for i = 1, 2, 3, 4 under various conditions. So,

  1. (i)

    \( \frac{{dTC_{A1} (T)}}{dT} \) is an increasing function on \( [PM_{1} /\lambda ,\infty ) \).

  2. (ii)

    \( \frac{{dTC_{A2} (T)}}{dT} \) is an increasing function on \( \left[ {M_{1} ,\frac{{PM_{1} }}{\lambda }} \right] \).

  3. (iii)

    \( \frac{{dTC_{A3} (T)}}{dT} \) is an increasing function on \( \left[ {M_{1} - N,M_{1} } \right] \).

\( 2A \ge \delta_{1} \) is implied from \( T_{A1}^{*} \ge \frac{{PM_{1} }}{\lambda } \). Since \( \frac{{dTC_{A1} (T)}}{dT} \) is an increasing function, we have \( \frac{{dTC_{A1} (T_{A1}^{*} )}}{dT} \ge \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \). This implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \le 0 \). Hence, \( 2A \ge \delta_{1} \) implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \le 0 \) and so \( 2A \le \delta_{1} \) implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \ge 0. \) Similarly, \( 2A \ge \delta_{2} \) implies that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \le 0 \) and so \( 2A \le \delta_{2} \) implies that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \ge 0. \)

\( 2A \le \delta_{1} \) implies that \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) and so \( 2A \ge \delta_{1} \) implies that \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \le 0. \)

\( 2A \le \delta_{2} \) implies that \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \ge 0 \) and so \( 2A \ge \delta_{2} \) implies that \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \le 0. \)

\( 2A \ge \delta_{3} \) implies that \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0 \) and so \( 2A \le \delta_{3} \) implies that \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \ge 0. \)

\( 2A < \delta_{3} \) implies that \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \ge 0 \) and so \( 2A > \delta_{3} \) implies that \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \le 0. \)

  1. (a)

    If \( 2A \ge \delta_{1}, \) then \( TC_{A1} (T) \) is a convex function on \( [PM_{1} /\lambda ,\infty ) \) and \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \le 0; \) This shows that \( TC_{A1} (T) \) is decreasing on \( [PM_{1} /\lambda ,T_{A1}^{*} ] \) and increasing on \( [T_{A1}^{*} ,\infty ). \) Since \( \delta_{1} \ge \delta_{2} \ge \delta_{3} \, , \) we have \( 2A \ge \delta_{2} \) and \( 2A \ge \delta_{3}. \) These imply that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \le 0 \) and \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \le 0, \) \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0 \) and \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \le 0. \) \( 2A \ge \delta_{1} \) implies that \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \le 0. \) Hence, we have (i) \( TC_{A2} (T) \) is a decreasing function on \( \left[ {M_{1} ,\frac{{PM_{1} }}{\lambda }} \right], \) (ii) \( TC_{A3} (T) \) is a decreasing function on \( \left[ {M_{1} - N,M_{1} } \right], \) (iii) \( TC_{A4} (T) \) is a decreasing function on \( \left[ {0,M_{1} - N} \right] \) since \( \mathop { \lim }\limits_{{{\text{T}} \to 0}} TC_{A4}^{\prime } (T) = - \infty. \) Hence, \( TC_{A} (T) \) is decreasing on [0, \( T_{A1}^{*} \)] and increasing on [\( T_{A1}^{*} \),∞). Hence, \( T^{*} = T_{A1}^{*} \) and \( TC_{A}^{*} (T) = TC_{A1}^{*} (T_{A1}^{*} ). \)

  2. (b)

    Let \( \delta_{1} \ge 2A \ge \delta_{2} \). \( \delta_{1} \ge 2A \) implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0. \) \( \delta_{2} \le 2A \) implies that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \le 0 \) and \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \le 0. \) \( \delta_{3} \le \delta_{2} \le 2A \) implies that \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0 \) and \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \le 0. \) Since \( TC_{A1}^{\prime } (T) \) is increasing on \( [PM_{1} /\lambda ,\infty ) \) and \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) implies that \( TC_{A1} (T) \) is increasing on \( [PM_{1} /\lambda ,\infty ). \) Since \( \delta_{1} \ge 2A \ge \delta_{2} \) implies that \( TC_{A2} (T) \)is a convex function on \( [M_{1} ,PM_{1} /\lambda ] \) and \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \le 0. \) Therefore, \( TC_{A2} (T) \) is decreasing on \( [M_{1} ,T_{A2}^{*} ] \) and increasing on \( [T_{A2}^{*} ,PM_{1} /\lambda ]. \) Since \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \le 0 \) and \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0, \) \( TC_{A3} (T) \) is decreasing on \( \left[ {M_{1} - N,M_{1} } \right]. \) Since \( - \infty = \mathop { \lim }\limits_{{{\text{T}} \to 0}} TC_{A4}^{\prime } (T) < TC_{A4}^{\prime } (M_{1} - N) \le 0, \) \( TC_{A4} (T) \) is decreasing on \( \left[ {0,M_{1} - N} \right]. \) Hence, \( TC_{A} (T) \) is decreasing on [0, \( T_{A2}^{*} \)] and increasing on [\( T_{A2}^{*} \), ∞). Hence, \( T^{*} = T_{A2}^{*} \) and \( TC_{A}^{*} (T) = TC_{A2}^{*} (T_{A2}^{*} ). \)

  3. (c)

    Let \( \delta_{2} \ge 2A \ge \delta_{3}. \) \( \delta_{2} \ge 2A \) implies that \( \delta_{1} \ge 2A. \) \( \delta_{1} \ge 2A \) implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0. \) \( \delta_{2} \ge 2A \) implies that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \ge 0. \) \( 2A \ge \delta_{3} \) implies that \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0 \) and \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \le 0. \) From the discussions in (b), \( TC_{A1} (T) \) is increasing on \( [PM_{1} /\lambda ,\infty ). \) Since \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0, \) \( TC_{A2} (T) \)is increasing on \( [M_{1} ,PM_{1} /\lambda ]. \) Since \( \delta_{2} \ge 2A \ge \delta_{3}, \) \( TC_{A3} (T) \) is convex on \( \left[ {M_{1} - N,M_{1} } \right] \) and \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \le 0, \) \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \ge 0, \) \( TC_{A3} (T) \) is decreasing on \( [M_{1} - N,T_{A3}^{*} ] \) and increasing on \( [T_{A3}^{*} ,M_{1} ]. \) Since \( - \infty = \mathop { \lim }\limits_{{{\text{T}} \to 0}} TC_{A4}^{\prime } (T) < TC_{A4}^{\prime } (M_{1} - N) \le 0, \) \( TC_{A4} (T) \) is decreasing on \( \left[ {0,M_{1} - N} \right]. \) Hence, \( TC_{A} (T) \) is decreasing on [0, \( T_{A3}^{*} \)] and increasing on [\( T_{A3}^{*} \), ∞). Hence, \( T^{*} = T_{A3}^{*} \) and \( TC_{A}^{*} (T) = TC_{A3}^{*} (T_{A3}^{*} ) \)

  4. (d)

    Let \( \delta_{3} \ge 2A. \) Since \( \delta_{1} \ge \delta_{2} \ge \delta_{3}, \) we have the following

    (i) \( \delta_{1} \ge 2A \) implies that \( \frac{{dTC_{A1} (PM_{1} /\lambda )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A2} (PM_{1} /\lambda )}}{dT} \, \ge 0. \)

    (ii) \( \delta_{2} \ge 2A \) implies that \( \frac{{dTC_{A2} (M_{1} )}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A3} (M_{1} )}}{dT} \, \ge 0. \)

    (iii) \( \delta_{3} \ge 2A \) implies that \( \frac{{dTC_{A3} (M_{1} - N)}}{dT} \, \ge 0 \) and \( \frac{{dTC_{A4} (M_{1} - N)}}{dT} \, \ge 0. \)

    (iv) \( TC_{A4} (T) \) is a convex function on \( \left[ {0,M_{1} - N} \right]. \)

Therefore,

  1. (i)

    \( TC_{A1} (T) \) is increasing on \( [PM_{1} /\lambda ,\infty ). \)

  2. (ii)

    \( TC_{A2} (T) \) is increasing on \( [M_{1} ,PM_{1} /\lambda ]. \)

  3. (iii)

    \( TC_{A3} (T) \) is increasing on \( [M_{1} - N,M_{1} ]. \)

  4. (iv)

    \( TC_{A4} (T) \) is decreasing on \( [0,T_{A4}^{*} ] \) and decreasing on \( [T_{A4}^{*} ,M_{1} - N]. \)

Hence \( TC_{A} (T) \) is decreasing on [0, \( T_{A4}^{*} \)] and increasing on [\( T_{A4}^{*} \), ∞). Hence, \( T^{*} = T_{A4}^{*} \) and \( TC_{A}^{*} (T) = TC_{A4}^{*} (T_{A4}^{*} ) \).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Thangam, A. Retailer’s optimal replenishment policy in a two-echelon supply chain under two-part delay in payments and disruption in delivery. Int J Syst Assur Eng Manag 8 (Suppl 1), 26–46 (2017). https://doi.org/10.1007/s13198-014-0285-7

Download citation

  • Received:

  • Revised:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s13198-014-0285-7

Keywords

Navigation