Open Access
Issue
RAIRO-Oper. Res.
Volume 59, Number 5, September-October 2025
Page(s) 2517 - 2543
DOI https://doi.org/10.1051/ro/2025101
Published online 05 September 2025
  • M. Akhtar, A.K. Manna and A.K. Bhunia, Optimization of a non-instantaneous deteriorating inventory problem with time and price dependent demand over finite time horizon via hybrid DESGO algorithm. Exp. Syst. Appl. 211 (2023) 118676. [Google Scholar]
  • M. Al-Amin Khan, A.A. Shaikh, I. Konstantaras, A.K. Bhunia and L.E. Cárdenas-Barrón, Inventory models for perishable items with advanced payment, linearly time-dependent holding cost and demand dependent on advertisement and selling price. Int. J. Prod. Econ. 230 (2020) 107804. [CrossRef] [Google Scholar]
  • B.L. Bayus, Are product life cycles really getting shorter? J. Prod. Innov. Manag. 11 (1994) 300–308. [Google Scholar]
  • S. Benjaafar, Y. Li and M. Daskin, Carbon footprint and the management of supply chains: insights from simple models. IEEE Trans. Autom. Sci. Eng. 10 (2013) 99–116. [Google Scholar]
  • A.K. Bhunia and A.A. Shaikh, An application of PSO in a two-warehouse inventory model for deteriorating item under permissible delay in payment with different inventory policies. Appl. Math. Comput. 256 (2015) 831–850. [Google Scholar]
  • A.K. Bhunia, A.A. Shaikh, V. Dhaka, S. Pareek and L.E. Cárdenas-Barrón, An application of genetic algorithm and PSO in an inventory model for single deteriorating item with variable demand dependent on marketing strategy and displayed stock level. Sci. Iran. 25 (2018) 1641–1655. [Google Scholar]
  • J.M. Chen and L.T. Chen, Pricing and lot-sizing for a deteriorating item in a periodic review inventory system with shortages. J. Oper. Res. Soc. 55 (2004) 892–901. [Google Scholar]
  • C.K. Chen, C. Liao and T.C. Weng, Optimal replenishment policies for the case of a demand function with product-life-cycle shape in a finite planning horizon. Exp. Syst. Appl. 32 (2007) 65–76. [Google Scholar]
  • X. Chen, S. Benjaafar and A. Elomri, The carbon-constrained EOQ. Oper. Res. Lett. 41 (2013) 172–179. [CrossRef] [MathSciNet] [Google Scholar]
  • L. Chen, X. Chen, M.F. Keblis and G. Li, Optimal pricing and replenishment policy for deteriorating inventory under stock-level-dependent, time-varying and price-dependent demand. Comput. Ind. Eng. 135 (2019) 1294–1299. [CrossRef] [Google Scholar]
  • R.Y. Chenavaz and A. Eynan, Advertising, goodwill, and the Veblen effect. Eur. J. Oper. Res. 289 (2021) 676–682. [Google Scholar]
  • M. Choudhury, S. Das, G.W. Weber and G.C. Mahata, Carbon-regulated inventory pricing and ordering policies with marketing initiatives under order volume discounting scheme. Ann. Oper. Res. (2025) [Google Scholar]
  • M. Clerc and J. Kennedy, The particle swarm–explosion, stability, and convergence in a multidimensional complex space. IEEE Trans. Evol. Comput. 6 (2002) 58–73. [Google Scholar]
  • R. Crawford, Life Cycle Assessment in the Built Environment. Routledge, London (2011). [Google Scholar]
  • B. Crettez, N. Hayek and G. Zaccour, Existence and uniqueness of optimal dynamic pricing and advertising controls without concavity. Oper. Res. Lett. 46 (2018) 199–204. [Google Scholar]
  • T. Doganoglu and D. Klapper, Goodwill and dynamic advertising strategies. Quant. Mark. Econ. 4 (2006) 5–29. [Google Scholar]
  • W.A. Donaldson, Inventory replenishment policy for a linear trend in demand-an analytical solution. Oper. Res. Q. 28 (1977) 663–670. [Google Scholar]
  • C.Y. Dye, A finite horizon deteriorating inventory model with two-phase pricing and time-varying demand and cost under trade credit financing using particle swarm optimization. Swarm Evol. Comput. 5 (2012) 37–53. [Google Scholar]
  • C.Y. Dye and C.T. Yang, Sustainable trade credit and replenishment decisions with credit-linked demand under carbon emission constraints. Eur. J. Oper. Res. 244 (2015) 187–200. [CrossRef] [Google Scholar]
  • R.C. Eberhart and J. Kennedy, A new optimizer using particle swarm theory, in Proceedings of the Sixth International Symposium on Micromachine and Human Science, Nagoya, Japan (1995) 39–43. [Google Scholar]
  • R.C. Eberhart and Y. Shi, Comparing inertia weights and constriction factors in particle swarm optimization, in Proceedings of the 2000 Congress on Evolutionary Computation, CEC00 (Cat. No. 00TH8512). Vol. of 1. IEEE (2000) 84–88. [Google Scholar]
  • S.K. Goyal, D. Morrin and F. Nebebe, The finite horizon trended inventory replenishment problem with shortages. J. Oper. Res. Soc. 43 (1992) 1173–1178. [Google Scholar]
  • M. Honarvar, M. Alimohammadi Ardakani and M. Modarres, A particle swarm optimization algorithm for solving pricing and lead time quotation in a dual-channel supply chain with multiple customer classes. Adv. Oper. Res. 2020 (2020) 5917126. [Google Scholar]
  • D. Horsky, An empirical analysis of the optimal advertising policy. Manag. Sci. 23 (1977) 1037–1049. [Google Scholar]
  • J. Huang, M. Leng and L. Liang, Recent developments in dynamic advertising research. Eur. J. Oper. Res. 220 (2012) 591–609. [CrossRef] [Google Scholar]
  • M. Jain and P. Singh, Optimal inspection and advance payment policy for deteriorating items using differential evolution metaheuristic. Appl. Soft Comput. 128 (2022) 109475. [Google Scholar]
  • S. Jørgensen and G. Zaccour, Equilibrium pricing and advertising strategies in a marketing channel. J. Optim. Theor. Appl. 102 (1999) 111–125. [Google Scholar]
  • S. Jørgensen and G. Zaccour, A survey of game-theoretic models of cooperative advertising. Eur. J. Oper. Res. 237 (2014) 1–14. [Google Scholar]
  • J. Kennedy and R.C. Eberhart, Particle swarm optimization, in Proceedings of IEEE International Conference on Neural Networks. Vol. 4. Piscataway, NJ (1995) 1942–1948. [Google Scholar]
  • J.Y. Lee, Investing in carbon emissions reduction in the EOQ model. J. Oper. Res. Soc. 71 (2020) 1289–1300. [CrossRef] [Google Scholar]
  • L.M. Lodish, M. Abraham, S. Kalmenson, J. Livelsberger, B. Lubetkin, B. Richardson and M.E. Stevens, How TV advertising works: a meta-analysis of 389 real world split cable TV advertising experiments. J. Mark. Res. 32 (1995) 125–139. [Google Scholar]
  • P. Mahata, G.C. Mahata and S. Kumar De, Optimal replenishment and credit policy in supply chain inventory model under two levels of trade credit with time- and credit-sensitive demand involving default risk. J. Ind. Eng. Int. 14 (2018) 31–42. [CrossRef] [Google Scholar]
  • P. Mahata, G.C. Mahata and A. Mukherjee, An ordering policy for deteriorating items with price-dependent iso-elastic demand under permissible delay in payments and price inflation. Math. Comput. Model. Dyn. Syst. 25 (2019) 575–601. [CrossRef] [MathSciNet] [Google Scholar]
  • R. Mardyana, and G.C. Mahata, Impacts of dual carbon emission reduction technology and technology spillovers of deterioration reduction on supply chain system’s performances considering government incentives and contract design. J. Clean. Prod. 468 (2024) 142977. [Google Scholar]
  • R. Mardyana, S.K. De and G.C.M., Investigation of an imperfect production system with controllable deterioration under emission and service constraint via optimal control theory. Int. J. Manag. Sci. Eng. Manag. 20 (2025) 1–23. [Google Scholar]
  • G. Massonnet, J.P. Gayon and C. Rapine, Approximation algorithms for deterministic continuous-review inventory lot-sizing problems with time-varying demand. Eur. J. Oper. Res. 234 (2014) 641–649. [Google Scholar]
  • U. Mishra, J.Z. Wu and B. Sarkar, Optimum sustainable inventory management with backorder and deterioration under controllable carbon emissions. J. Clean. Prod. 279 (2021) 123699. [CrossRef] [Google Scholar]
  • A. Mukherjee and G.C. Mahata, Optimal replenishment and credit policy in an inventory model for deteriorating items under two-levels of trade credit policy when demand depends on both time and credit period involving default risk. RAIRO-Oper. Res. 52 (2018) 1175–1200. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • A. Nair and R. Narasimhan, Dynamics of competing with quality-and advertising-based goodwill. Eur. J. Oper. Res. 175 (2006) 462–474. [Google Scholar]
  • M. Nerlove and K.J. Arrow, Optimal advertising policy under dynamic conditions. Economica 29 (1962) 129–142. [CrossRef] [Google Scholar]
  • M. Pervin, S.K. Roy, P. Sannyashi and G.W. Weber, Sustainable inventory model with environmental impact for non-instantaneous deteriorating items with composite demand. RAIRO-Oper. Res. 57 (2023) 237–261. [CrossRef] [EDP Sciences] [MathSciNet] [Google Scholar]
  • A. Ranjan and J. Jha, Multi-period dynamic pricing model for deteriorating products in a supply chain with preservation technology investment and carbon emission. Comput. Ind. Eng. 174 (2022) 108817. [CrossRef] [Google Scholar]
  • S. Saha, B. Sarkar and M. Sarkar, Application of improved meta-heuristic algorithms for green preservation technology management to optimize dynamical investments and replenishment strategies. Math. Comput. Simul. 209 (2023) 426–450. [CrossRef] [Google Scholar]
  • L.A. San-José, J. Sicilia and B. Abdul-Jalbar, Optimal policy for an inventory system with demand dependent on price, time and frequency of advertisement. Comput. Oper. Res. 128 (2021) 105169. [CrossRef] [Google Scholar]
  • A. Shamayleh, M. Hariga, R. As’ad and A. Diabat, Economic and environmental models for cold products with time varying demand. J. Clean. Prod. 212 (2019) 847–863. [CrossRef] [Google Scholar]
  • E.S. Subramanyam and S. Kumaraswamy, EOQ Formula under varying marketing policies and conditions. AIIE Trans. 13 (1981) 312–314. [CrossRef] [Google Scholar]
  • A.A. Taleizadeh, L. Aliabadi and P. Thaichon, A sustainable inventory system with price-sensitive demand and carbon emissions under partial trade credit and partial backordering. Oper. Res. 22 (2022) 4471–4516. [Google Scholar]
  • J.T. Teng, M.S. Chern, H.L. Yang and Y.J. Wang, Deterministic lot-size inventory models with shortages and deterioration for fluctuating demand. Oper. Res. Lett. 24 (1999) 65–72. [CrossRef] [MathSciNet] [Google Scholar]
  • S. Tiwari, C.K. Jaggi, A.K. Bhunia, A.A. Shaikh and M. Goh, Two-warehouse inventory model for non-instantaneous deteriorating items with stock-dependent demand and inflation using particle swarm optimization. Ann. Oper. Res. 254 (2017) 401–423. [Google Scholar]
  • Y.C. Tsao, Two-phase pricing and inventory management for deteriorating and fashion goods under trade credit. Math. Methods Oper. Res. 72 (2010) 107–127. [Google Scholar]
  • T.L. Urban, Deterministic inventory models incorporating marketing decisions. Comput. Ind. Eng. 22 (1992) 85–93. [Google Scholar]
  • H.M. Wee, Joint pricing and replenishment policy for deteriorating inventory with declining market. Int. J. Prod. Econ. 40 (1995) 163–171. [Google Scholar]
  • J. Wu, J.T. Teng and K. Skouri, Optimal inventory policies for deteriorating items with trapezoidal-type demand patterns and maximum lifetimes under upstream and downstream trade credits. Ann. Oper. Res. 264 (2018) 459–476. [CrossRef] [MathSciNet] [Google Scholar]
  • H.L. Yang, J.T. Teng and M.S. Chern, A forward recursive algorithm for inventory lot-size models with power-form demand and shortages. Eur. J. Oper. Res. 137 (2002) 394–400. [Google Scholar]

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