Quality and pricing decisions for substitutable items under imperfect production process over a random planning horizon
Year 2018,
Volume: 47 Issue: 1, 175 - 201, 01.02.2018
Manoranjan De
Barun Das
Manoranjan Maiti
Abstract
The paper determines the optimum qualities and prices of two substitute products for a manufacturer cum retailer in an imperfect production process over a random planning horizon for maximum prot. In this Economic Production Lot-size (EPL) process, items are produced simultaneously, defective production commences during the out-of-control state after the passage of some time from the commencement of production and the defective units are partially reworked. The items are substitutable to each other depending on their prices and qualities jointly or either of these two. Unit production cost depends directly on raw-material, labour and quality improvement costs and inversely on the production rate. A part of it is spent against environment protection. Here learning effect is introduced in the set-up and maintenance costs. For the whole process, the planning horizon is random with normal distribution, which is treated as a chance constraint. The models are formulated as prot maximization problems subject to a chance constraint and solved using Genetic Algorithm with Variable Populations (GAVP). The models are demonstrated numerically and the near-optimum results are presented graphically.
References
- Abdel-Maleka, L. L., & Montanari, R. (2005). An analysis of the multi-product newsboy problem
with a budget constraint. International Journal of Production Economics, 97, 296-307.
- Absi, N., Dauz'ere-P'er'es, S., Kedad-Sidhoum, S., Penz, B., & Rapine, C. (2013). Lot sizing with
carbon emission constraints. European Journal of Operational Research, 227 (1), 55-61.
- Ahiska, S. S., & Kurtul, E. (2014). Modelling and analysis of a product substitution strategy for a
stochastic manufacturing/re-manufacturing system. Computers & Industrial Engineering, 72, 111.
- Bazan, E., Jaber, M.Y. & Zanoni, S. (2015). Supply chain models with greenhouse gases emissions,
energy usage and dierent coordination decisions. Applied Mathematical Modelling, 39, 5131-5151.
- Chand, S. (1989). Lot sizes and set up frequency with learning in set ups and process quality.
European Journal of Operational Research, 42, 190-202.
- Chen, Y. C. (2013). An optimal production and inspection strategy with preventive maintenance
error and rework. Journal of Manufacturing Systems, 32, 99-106.
- Chen, X., Benjaafar, S., & Elomri, A. (2013). The carbon-constrained EOQ. Operations Research
Letters, 41 (2), 172 - 179.
- Cheng, T. C. E., Wu, C. C., & Lee, W. C. (2010). Scheduling problems with deteriorating jobs
and learning eects including proportional set up times. Computers & Industrial Engineering, 58,
326-331.
- Chung, K. H., & Kim, Y. H. (1989). Economic Analysis of Inventory Systems: A rejoinder, Engineering
Economics, 35, 75-80.
- Das, B., & Maiti, M. (2007). An application of bi level newsboy problem in two substitutable
items under capital cost. Applied Mathematics and Computation, 190, 410-422.
- Ghosh, D., & Shah, J. (2015). Supply chain analysis under green sensitive consumer demand and
cost sharing contract. International Journal of Production Economics, 164, 319-329.
- Guria, A., Das, B., mandal, S., & Maiti, M. (2013). Inventory policy for an item with ination
induced purchasing price, selling price and demand with immediate part payment. Applied Mathematical
Modelling, 37, 240-257.
- Gurler, U., & Yilmaz, A.(2010). Inventory and coordination issues with two substitutable products.
Applied Mathematical Modelling, 34, 539-551.
- Hu, J. S., Zheng, H., Guo, C. Y., & Ji, Y. P. (2010). Optimal production run length with imperfect
production processes and backorder in fuzzy random environment. Computers & Industrial
Engineering, 59(1), 915.
- Jin, M., Granda-Marulanda, N.A., & Down, I. (2014). The impact of carbon policies on supply
chain design and logistics of a major retailer. Journal of Cleaner Production, 85, 453-461.
- Khouja, M., & Mehrez, A. (1994). An economic production lot size model with imperfect quality
and variable production rate. Journal of the Operational Research Society, 45, 1405-1417.
- Khouja, M., & Mehrez, A. (1998). A note on the eect of inventory costs on product quality levels.
Production planning & Control, 9(7), 723-726.
- Kim, S.W., Bell, & P.C., 2011. Optimal Pricing and Production Decisions in the Presence of
Symmetrical and Asymmetrical Substitution. Omega-International Journal of Management Science,
39(5), 528-538.
- Last, M., & Eyal, S. (2005). A fuzzy-based lifetime extension of genetic algorithms. Fuzzy Sets
and Systems, 149, 131 - 147.
- Liang, Y., & Zhou, F. (2011). A two-warehouse inventory model for deteriorating items under
conditionally permissible delay in payment, Applied Mathematical Modelling, 35, 2221-2231.
- Liu, B., & Iwamura, K. (1998). Chance constraint programming with fuzzy parameters. Fuzzy
Sets and Systems, 94, 227-237.
- Maiti A. K., Maiti M. K., & Maiti, M. (2009). Inventory model with stochastic lead-time and price
dependent demand incorporating advance payment. Applied Mathematical Modelling, 33, 2433-2443.
- Maiti, M. K. (2011). A fuzzy Genetic Algorithm with varying population size to solve an inventory
model with credit-linked promotional demand in an imprecise planning horizon. European Journal of
Operational Research, 213, 96-106.
- Maity, K., & Maiti M. (2009). Optimal inventory policies for deteriorating complementary and
substitute items. International Journal of Systems Science, 40(3), 267-276.
- Mandal, S., Maity, K., Mondal, S., & Maiti, M. (2010). Optimal production inventory policy for
defective items with fuzzy time period. Applied Mathematical Modelling, 34, 810-822.
- Michalewicz, Z. (1996). Genetic Algorithm + Data Structure = Evolution Programs, 3rd Edition.
New York, Springer-Verlag.
- Mondal,B., Bhunia, A. K., & Maiti, M. (2003). An inventory system of ameliorating items for
price dependent demand rate. Computers & Industrial Engineering, 45(3), 443-456.
- Mondal, S & Maiti, M. (2002). Multi-item Fuzzy EOQ Models using Genetic Algorithm. Computers
& Industrial Engineering, 44, 105-117.
- Moon,J. & Yun, W. (1993). An economic order quantity model with a random planning horizon.
Engineering Economics, 39, 77-86.
- Pal, B., Sana, S. S., & Chaudhuri, K. S. (2013). A mathematical model on EPQ for stochastic
demand in an imperfect production system. Journal of Manufacturing Systems, 32, 260-270.
- Pal, S, Maiti, M.K. & Maiti, M. (2009). An EPQ model with price discounted promotional demand
in an imprecise planning horizon via Genetic Algorithm. Computers & Industrial Engineering, 57,
181-187.
- Paul, S., Wahab, M. I. M., & Ongkunaruk, P. (2014). Joint replenishment with imperfect items
and price discount. Computers & Industrial Engineering, 74, 179-185.
- Rad, M. A., Khoshalhan, F., & Glock, C. H. (2014). Optimizing inventory and sales decisions in
a two-stage supply chain with imperfect production and backorders. Computers & Industrial Engineering,
74, 219-227.
- Rao, S. S. (2009). Engineering Optimization: Theory and Practice, 4th Edition. John Wiley &
Sons, Inc., Hoboken, New Jersey.
- Rosenblatt, M. J., & Lee, H. L. (1986). Economic production cycle with imperfect production
processes. IIE Transactions, 18, 48-55.
- Roy, A., Pal, S., & Maiti, M. K. (2009). A production inventory model with stock dependent
demand incorporating learning and inationary eect in a random planning horizon: A fuzzy genetic
algorithm with varying population size approach. Computers & Industrial Engineering, 57(4), 1324-
1335.
- Sana, S. S., (2010). An economic production lot size model in an imperfect production system.
European Journal of Operational Research, 201, 158 - 170.
- Sarkar, B., Sana, S., & Chaudhuri, K. S. (2010). Optimal reliability, production lot size and
safety stock in an imperfect production system. International Journal of Mathematics in Operational
Research, 2(4), 467-490.
- Stavrulaki. E. (2011). Inventory decisions for substitutable products with stock-dependent demand.
International Journal of Production Economics, 129, 65-78.
- Swami, S., & Shah, J. (2013). Channel coordination in green supply chain management. Journal
of the Operational Research Society, 64, 336 - 351.
- Tarakci, H., Tang, K., & Teyarachakul, S. (2009). Learning eects on maintenance outsourcing.
European Journal of Operational Research, 192, 138-150.
- Yao, J. S., & Wu, K. (2000). The best prices of two mutually complements in fuzzy sense. Fuzzy
Sets and Systems, 111, 433454.
- Zakeri, A., Dehghanian, F., Fahimnia, B., & Sarkis, J. (2015). Carbon pricing versus emissions
trading: A supply chain planning perspective. International Journal of Production Economics, 164,
197-205.
- Zhang, B., & Xu, L.(2013). Multi-item production planning with carbon cap and trade mechanism.
International Journal of Production Economics, 144, 1, 118-127.
- Zhao, J., Tang, W., Zhao, R., & Wei, J. (2012). Pricing decisions for substitutable products with
a common retailer in fuzzy environments. European Journal of Operational Research, 216, 409419.
Year 2018,
Volume: 47 Issue: 1, 175 - 201, 01.02.2018
Manoranjan De
Barun Das
Manoranjan Maiti
References
- Abdel-Maleka, L. L., & Montanari, R. (2005). An analysis of the multi-product newsboy problem
with a budget constraint. International Journal of Production Economics, 97, 296-307.
- Absi, N., Dauz'ere-P'er'es, S., Kedad-Sidhoum, S., Penz, B., & Rapine, C. (2013). Lot sizing with
carbon emission constraints. European Journal of Operational Research, 227 (1), 55-61.
- Ahiska, S. S., & Kurtul, E. (2014). Modelling and analysis of a product substitution strategy for a
stochastic manufacturing/re-manufacturing system. Computers & Industrial Engineering, 72, 111.
- Bazan, E., Jaber, M.Y. & Zanoni, S. (2015). Supply chain models with greenhouse gases emissions,
energy usage and dierent coordination decisions. Applied Mathematical Modelling, 39, 5131-5151.
- Chand, S. (1989). Lot sizes and set up frequency with learning in set ups and process quality.
European Journal of Operational Research, 42, 190-202.
- Chen, Y. C. (2013). An optimal production and inspection strategy with preventive maintenance
error and rework. Journal of Manufacturing Systems, 32, 99-106.
- Chen, X., Benjaafar, S., & Elomri, A. (2013). The carbon-constrained EOQ. Operations Research
Letters, 41 (2), 172 - 179.
- Cheng, T. C. E., Wu, C. C., & Lee, W. C. (2010). Scheduling problems with deteriorating jobs
and learning eects including proportional set up times. Computers & Industrial Engineering, 58,
326-331.
- Chung, K. H., & Kim, Y. H. (1989). Economic Analysis of Inventory Systems: A rejoinder, Engineering
Economics, 35, 75-80.
- Das, B., & Maiti, M. (2007). An application of bi level newsboy problem in two substitutable
items under capital cost. Applied Mathematics and Computation, 190, 410-422.
- Ghosh, D., & Shah, J. (2015). Supply chain analysis under green sensitive consumer demand and
cost sharing contract. International Journal of Production Economics, 164, 319-329.
- Guria, A., Das, B., mandal, S., & Maiti, M. (2013). Inventory policy for an item with ination
induced purchasing price, selling price and demand with immediate part payment. Applied Mathematical
Modelling, 37, 240-257.
- Gurler, U., & Yilmaz, A.(2010). Inventory and coordination issues with two substitutable products.
Applied Mathematical Modelling, 34, 539-551.
- Hu, J. S., Zheng, H., Guo, C. Y., & Ji, Y. P. (2010). Optimal production run length with imperfect
production processes and backorder in fuzzy random environment. Computers & Industrial
Engineering, 59(1), 915.
- Jin, M., Granda-Marulanda, N.A., & Down, I. (2014). The impact of carbon policies on supply
chain design and logistics of a major retailer. Journal of Cleaner Production, 85, 453-461.
- Khouja, M., & Mehrez, A. (1994). An economic production lot size model with imperfect quality
and variable production rate. Journal of the Operational Research Society, 45, 1405-1417.
- Khouja, M., & Mehrez, A. (1998). A note on the eect of inventory costs on product quality levels.
Production planning & Control, 9(7), 723-726.
- Kim, S.W., Bell, & P.C., 2011. Optimal Pricing and Production Decisions in the Presence of
Symmetrical and Asymmetrical Substitution. Omega-International Journal of Management Science,
39(5), 528-538.
- Last, M., & Eyal, S. (2005). A fuzzy-based lifetime extension of genetic algorithms. Fuzzy Sets
and Systems, 149, 131 - 147.
- Liang, Y., & Zhou, F. (2011). A two-warehouse inventory model for deteriorating items under
conditionally permissible delay in payment, Applied Mathematical Modelling, 35, 2221-2231.
- Liu, B., & Iwamura, K. (1998). Chance constraint programming with fuzzy parameters. Fuzzy
Sets and Systems, 94, 227-237.
- Maiti A. K., Maiti M. K., & Maiti, M. (2009). Inventory model with stochastic lead-time and price
dependent demand incorporating advance payment. Applied Mathematical Modelling, 33, 2433-2443.
- Maiti, M. K. (2011). A fuzzy Genetic Algorithm with varying population size to solve an inventory
model with credit-linked promotional demand in an imprecise planning horizon. European Journal of
Operational Research, 213, 96-106.
- Maity, K., & Maiti M. (2009). Optimal inventory policies for deteriorating complementary and
substitute items. International Journal of Systems Science, 40(3), 267-276.
- Mandal, S., Maity, K., Mondal, S., & Maiti, M. (2010). Optimal production inventory policy for
defective items with fuzzy time period. Applied Mathematical Modelling, 34, 810-822.
- Michalewicz, Z. (1996). Genetic Algorithm + Data Structure = Evolution Programs, 3rd Edition.
New York, Springer-Verlag.
- Mondal,B., Bhunia, A. K., & Maiti, M. (2003). An inventory system of ameliorating items for
price dependent demand rate. Computers & Industrial Engineering, 45(3), 443-456.
- Mondal, S & Maiti, M. (2002). Multi-item Fuzzy EOQ Models using Genetic Algorithm. Computers
& Industrial Engineering, 44, 105-117.
- Moon,J. & Yun, W. (1993). An economic order quantity model with a random planning horizon.
Engineering Economics, 39, 77-86.
- Pal, B., Sana, S. S., & Chaudhuri, K. S. (2013). A mathematical model on EPQ for stochastic
demand in an imperfect production system. Journal of Manufacturing Systems, 32, 260-270.
- Pal, S, Maiti, M.K. & Maiti, M. (2009). An EPQ model with price discounted promotional demand
in an imprecise planning horizon via Genetic Algorithm. Computers & Industrial Engineering, 57,
181-187.
- Paul, S., Wahab, M. I. M., & Ongkunaruk, P. (2014). Joint replenishment with imperfect items
and price discount. Computers & Industrial Engineering, 74, 179-185.
- Rad, M. A., Khoshalhan, F., & Glock, C. H. (2014). Optimizing inventory and sales decisions in
a two-stage supply chain with imperfect production and backorders. Computers & Industrial Engineering,
74, 219-227.
- Rao, S. S. (2009). Engineering Optimization: Theory and Practice, 4th Edition. John Wiley &
Sons, Inc., Hoboken, New Jersey.
- Rosenblatt, M. J., & Lee, H. L. (1986). Economic production cycle with imperfect production
processes. IIE Transactions, 18, 48-55.
- Roy, A., Pal, S., & Maiti, M. K. (2009). A production inventory model with stock dependent
demand incorporating learning and inationary eect in a random planning horizon: A fuzzy genetic
algorithm with varying population size approach. Computers & Industrial Engineering, 57(4), 1324-
1335.
- Sana, S. S., (2010). An economic production lot size model in an imperfect production system.
European Journal of Operational Research, 201, 158 - 170.
- Sarkar, B., Sana, S., & Chaudhuri, K. S. (2010). Optimal reliability, production lot size and
safety stock in an imperfect production system. International Journal of Mathematics in Operational
Research, 2(4), 467-490.
- Stavrulaki. E. (2011). Inventory decisions for substitutable products with stock-dependent demand.
International Journal of Production Economics, 129, 65-78.
- Swami, S., & Shah, J. (2013). Channel coordination in green supply chain management. Journal
of the Operational Research Society, 64, 336 - 351.
- Tarakci, H., Tang, K., & Teyarachakul, S. (2009). Learning eects on maintenance outsourcing.
European Journal of Operational Research, 192, 138-150.
- Yao, J. S., & Wu, K. (2000). The best prices of two mutually complements in fuzzy sense. Fuzzy
Sets and Systems, 111, 433454.
- Zakeri, A., Dehghanian, F., Fahimnia, B., & Sarkis, J. (2015). Carbon pricing versus emissions
trading: A supply chain planning perspective. International Journal of Production Economics, 164,
197-205.
- Zhang, B., & Xu, L.(2013). Multi-item production planning with carbon cap and trade mechanism.
International Journal of Production Economics, 144, 1, 118-127.
- Zhao, J., Tang, W., Zhao, R., & Wei, J. (2012). Pricing decisions for substitutable products with
a common retailer in fuzzy environments. European Journal of Operational Research, 216, 409419.