How to cite this paper
Sarwar, F., Ahmed, M & Rahman, M. (2021). Application of nature inspired algorithms for multi-objective inventory control scenarios.International Journal of Industrial Engineering Computations , 12(1), 91-114.
Refrences
Arrow, K. J., Harris, T., & Marschak, J. (1951). Optimal inventory policy. Econometrica: Journal of the Econometric Society,19(3), 250–272.
As’Ad, R., & Demirli, K. (2011). A bilinear programming model and a modified branch-and-bound algorithm for production planning in steel rolling mills with substitutable demand. International Journal of Production Research, 49(12), 3731–3749. https://doi.org/10.1080/00207541003690116
Blinder, A. S., & Maccini, L. J. (1991). Taking stock: a critical assessment of recent research on inventories. The Journal of Economic Perspectives, 5(1), 73–96. https://doi.org/10.1016/j.jmoneco.2004.08.005
Bonney, M., & Jaber, M. Y. (2011). Environmentally responsible inventory models: Non-classical models for a non-classical era. International Journal of Production Economics, 133(1), 43–53.
Branke, J., & Mostaghim, S. (2016). Comprehensive Comparision of MOPSO methods: Study of Convergence and Diversity-Survey of State of The Art.
Chiu, S. W., & Chiu, Y. S. P. (2006). Mathematical modeling for production system with backlogging and failure in repair. Journal of Scientific & Industrial Research, 65, 499-506.
Chiu, Y. S. P., Wu, M. F., Chiu, S. W., & Chang, H. H. (2015). A simplified approach to the multi-item economic production quantity model with scrap, rework, and multi-delivery. Journal of Applied Research and Technology, 13(4), 472–476. https://doi.org/10.1016/j.jart.2015.09.004
Chopra, S., & Meindl, P. (2001). Strategy, Planning, and Operation. Supply Chain Management.
Coello Coello, C. A., & Lechuga, M. S. (2002). MOPSO: A proposal for multiple objective particle swarm optimization. Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, 2, 1051–1056. https://doi.org/10.1109/CEC.2002.1004388
Conway, R., Maxwell, W., McClain, J. O., & Thomas, L. J. (1988). The Role of Work-in-Process Inventory in Serial Production Lines. Operations Research, 36(2), 229–241. https://doi.org/10.1287/opre.36.2.229
Darwish, M. A. (2008). EPQ models with varying setup cost. International Journal of Production Economics, 113(1), 297–306. https://doi.org/10.1016/j.ijpe.2007.07.010
Diabat, A. (2014). Hybrid algorithm for a vendor managed inventory system in a two-echelon supply chain. European Journal of Operational Research, 238(1), 114–121. https://doi.org/10.1016/j.ejor.2014.02.061
Fattahi, P., Hajipour, V., & Nobari, A. (2015). A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms. Applied Soft Computing Journal, 32, 211–223. https://doi.org/10.1016/j.asoc.2015.02.044
Goyal, S. K. (1976). An integrated inventory model for a single supplier- single customer problem. International Journal of Production Research, 15(1), 107–111. https://doi.org/http://dx.doi.org/10.1080/00207547708943107
Grubbström, R. W., & Erdem, A. (1999). EOQ with backlogging derived without derivatives. International Journal of Production Economics, 59(1), 529–530. https://doi.org/10.1016/S0925-5273(98)00015-2
Guo, X., Liu, C., Xu, W., Yuan, H., & Wang, M. (2014). A prediction-based inventory optimization using data mining models. Proceedings - 2014 7th International Joint Conference on Computational Sciences and Optimization, CSO 2014, 611–615. https://doi.org/10.1109/CSO.2014.118
Hayek, P. A., & Salameh, M. K. (2001). Production lot sizing with the reworking of imperfect quality items produced. Production Planning & Control, 12(6), 584–590.
Huang, B., & Wu, A. (2016). EOQ model with batch demand and planned backorders. Applied Mathematical Modelling (Vol. 40). Elsevier Inc. https://doi.org/10.1016/j.apm.2016.01.004
Huseyinov, I., & Bayrakdar, A. (2019). Performance Evaluation of NSGA-III and SPEA2 in Solving a Multi-Objective Single-Period Multi-Item Inventory Problem. UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering, (4), 531–535. https://doi.org/10.1109/UBMK.2019.8907139
Jones, D. F., Mirrazavi, S. K., & Tamiz, M. (2002). Multi-objective meta-heuristics: An overview of the current state-of-the-art. European Journal of Operational Research, 137(1), 1–9.
Kanyalkar, A. P., & Adil, G. K. (2005). An integrated aggregate and detailed planning in a multi-site production environment using linear programming. International Journal of Production Research, 43(20), 4431–4454. https://doi.org/10.1080/00207540500142332
Kennedy, J., & Eberhart, R. (1995). Particle Swarm Optimization Proceedings., IEEE International Conference. Proceedings of ICNN’95 - International Conference on Neural Networks, 11(1), 111–117.
Kim, E., & Park, T. (2016). Admission and inventory control of a single-component make-to-order production system with replenishment setup cost and lead time. European Journal of Operational Research, 255(1), 91–102. https://doi.org/10.1016/j.ejor.2016.04.021
Kodama, M. (1995). Some Probabilistic Multiperiod Inventory Problems. IFAC Proceedings Volumes, 28(7), 217–222. https://doi.org/10.1016/S1474-6670(17)47112-6
Lenard, J. D., & Roy, B. (1995). Multi-item inventory control: A multicriteria view. European Journal of Operational Research, 87(3), 685–692. https://doi.org/10.1016/0377-2217(95)00239-1
Gen, M. and Cheng, R. (1997) Genetic Algorithms & Engineering Design. John Wiley & Sons, Inc., Hoboken.
Mandal, N. K., Roy, T. K., & Maiti, M. (2006). Inventory model of deteriorated items with a constraint: A geometric programming approach. European Journal of Operational Research, 173(1), 199–210.
Mirzapour Al-e-Hashem, S. M. J., & Rekik, Y. (2014). Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach. International Journal of Production Economics, 157(1), 80–88. https://doi.org/10.1016/j.ijpe.2013.09.005
Mirzazadeh, A., Fatemi Ghomi, S. M. T., & Seyed Esfahani, M. M. (2011). A multiple items inventory model under uncertain external inflationary conditions. Trends in Applied Sciences Research, 6(5), 472–480.
Moosavi, V., Talebi, A., & Shirmohammadi, B. (2014). Producing a landslide inventory map using pixel-based and object-oriented approaches optimized by Taguchi method. Geomorphology, 204, 646–656. https://doi.org/10.1016/j.geomorph.2013.09.012
Mousavi, S. M., Niaki, S. T. A., Bahreininejad, A., & Musa, S. N. (2014). Multi-item multiperiodic inventory control problem with variable demand and discounts: A particle swarm optimization algorithm. Scientific World Journal, 2014. https://doi.org/10.1155/2014/136047
Niu, B., Tan, L., Liu, J., Liu, J., Yi, W., & Wang, H. (2019). Cooperative bacterial foraging optimization method for multi-objective multi-echelon supply chain optimization problem. Swarm and Evolutionary Computation, 49(May 2018), 87–101. https://doi.org/10.1016/j.swevo.2019.05.003
Park, K., & Kyung, G. (2014). Optimization of total inventory cost and order fill rate in a supply chain using PSO. International Journal of Advanced Manufacturing Technology, 70(9–12), 1533–1541. https://doi.org/10.1007/s00170-013-5399-6
Pasandideh, S. H. R., Niaki, S. T. A., & Sharafzadeh, S. (2013). Optimizing a bi-objective multi-product EPQ model with defective items, rework and limited orders: NSGA-II and MOPSO algorithms. Journal of Manufacturing Systems, 32(4), 764–770. https://doi.org/10.1016/j.jmsy.2013.08.001
Rau, H., Daniel, S., & Agus, G. (2018). Optimization of the multi-objective green cyclical inventory routing problem using discrete multi-swarm PSO method. Transportation Research Part E, 120(September), 51–75. https://doi.org/10.1016/j.tre.2018.10.006
Roozbeh Nia, A., Hemmati Far, M., & Niaki, S. T. A. (2015). A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage. Applied Soft Computing Journal, 30, 353–364. https://doi.org/10.1016/j.asoc.2015.02.004
Rossi, T., Pozzi, R., & Testa, M. (2017). EOQ-based inventory management in single-machine multi-item systems. Omega (United Kingdom), 71, 106–113. https://doi.org/10.1016/j.omega.2016.10.002
Roy, T. K., & Maiti, M. (1998). Multi-objective inventory models of deteriorating items with some constraints in a fuzzy environment. Computers & Operations Research, 25(12), 1085–1095.
S Akindipe, O. (2014). The Role of Raw Material Management in Production Operations. International Journal of Managing Value and Supply Chains, 5(3), 37–44. https://doi.org/10.5121/ijmvsc.2014.5303
Sadeghi, J., Mousavi, S. M., Niaki, S. T. A., & Sadeghi, S. (2014). Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm. Transportation Research Part E: Logistics and Transportation Review, 70(1), 274–292. https://doi.org/10.1016/j.tre.2014.07.007
Sarwar, F., Rahman, M., & Ahmed, M. (2019). A Multi-Item Inventory Control Model using Multi Objective Particle Swarm Optimization ( MOPSO ), 1311–1321.
Scholkopf, B., Sung, K.-K., Burges, C. J. C., Girosi, F., Niyogi, P., Poggio, T., & Vapnik, V. (1997). Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Transactions on Signal Processing, 45(11), 2758–2765.
Schott, J. (1995). Fault Tolerant Design Using Single and Multi-Criteria Genetic Algorithms. Master's Thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology.
Sutrisno, & Wicaksono, P. A. (2015). Optimal Strategy for Multi-product Inventory System with Supplier Selection by Using Model Predictive Control. Procedia Manufacturing, 4(Iess), 208–215. https://doi.org/10.1016/j.promfg.2015.11.033
Taft, E. W. (1918). The most economical production lot. Iron Age, 101(18), 1410–1412.
Taguchi, G. (1990). Introduction to quality engineering, Tokyo. Asian Productivity Organization.
Taleizadeh, A A, Moghadasi, H., Niaki, S. T. A., & Eftekhari, A. (2008). An economic order quantity under joint replenishment policy to supply expensive imported raw materials with payment in advance. Journal of Applied Sciences. https://doi.org/10.3923/jas.2008.4263.4273
Taleizadeh, Ata Allah, Niaki, S. T. A., & Aryanezhad, M. B. (2009). A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments. Mathematical and Computer Modelling, 49(5–6), 1044–1057. https://doi.org/10.1016/j.mcm.2008.10.013
Taleizadeh, Ata Allah, Niaki, S. T. A., Aryanezhad, M. B., & Shafii, N. (2013). A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand. Information Sciences, 220, 425–441. https://doi.org/10.1016/j.ins.2012.07.027
Taleizadeh, Ata Allah, Niaki, S. T. A., Shafii, N., Meibodi, R. G., & Jabbarzadeh, A. (2010). A particle swarm optimization approach for constraint joint single buyer-single vendor inventory problem with changeable lead time and (r,Q) policy in supply chain. International Journal of Advanced Manufacturing Technology, 51(9–12), 1209–1223. https://doi.org/10.1007/s00170-010-2689-0
Tavana, M. (2016). A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms : NSGA-II , NRGA , and MOPSO, 43, 57–72.
Tiwari, S., Daryanto, Y., & Wee, H. M. (2018). Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. Journal of Cleaner Production, 192, 281–292. https://doi.org/10.1016/j.jclepro.2018.04.261
Van Veldhuizen, D. A. (1999). Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. Ph. D. thesis, Air Force Institute of Technology Wright-Pattersonafb OH School of Engineering.
Wang, Gaige, Guo, L., Duan, H., Liu, L., & Wang, H. (2012). A bat algorithm with mutation for UCAV path planning. The Scientific World Journal, 2012. https://doi.org/10.1100/2012/418946
Wang, Guanghui. (2012). Demand forecasting of supply chain based on Support Vector Regression method. Procedia Engineering, 29, 280–284. https://doi.org/10.1016/j.proeng.2011.12.707
Wu, Q. (2010). Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system. Journal of Computational and Applied Mathematics, 233(10), 2481–2491. https://doi.org/10.1016/j.cam.2009.10.030
Yang, X. S., (2011), Bat Algorithm for Multiobjective Optimization, International Journal of Bio-Inspired Computation, 3(5), 267-274.
Yang, X. S., & He, X. (2013). Bat algorithm: literature review and applications. International Journal of Bio-Inspired Computation, 5(3), 141. https://doi.org/10.1504/IJBIC.2013.055093
Zitzler, E., & Thiele, L. (1998). Multiobjective optimization using evolutionary algorithms - A comparative case study. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1498 LNCS(September), 292–301. https://doi.org/10.1007/bfb0056872
As’Ad, R., & Demirli, K. (2011). A bilinear programming model and a modified branch-and-bound algorithm for production planning in steel rolling mills with substitutable demand. International Journal of Production Research, 49(12), 3731–3749. https://doi.org/10.1080/00207541003690116
Blinder, A. S., & Maccini, L. J. (1991). Taking stock: a critical assessment of recent research on inventories. The Journal of Economic Perspectives, 5(1), 73–96. https://doi.org/10.1016/j.jmoneco.2004.08.005
Bonney, M., & Jaber, M. Y. (2011). Environmentally responsible inventory models: Non-classical models for a non-classical era. International Journal of Production Economics, 133(1), 43–53.
Branke, J., & Mostaghim, S. (2016). Comprehensive Comparision of MOPSO methods: Study of Convergence and Diversity-Survey of State of The Art.
Chiu, S. W., & Chiu, Y. S. P. (2006). Mathematical modeling for production system with backlogging and failure in repair. Journal of Scientific & Industrial Research, 65, 499-506.
Chiu, Y. S. P., Wu, M. F., Chiu, S. W., & Chang, H. H. (2015). A simplified approach to the multi-item economic production quantity model with scrap, rework, and multi-delivery. Journal of Applied Research and Technology, 13(4), 472–476. https://doi.org/10.1016/j.jart.2015.09.004
Chopra, S., & Meindl, P. (2001). Strategy, Planning, and Operation. Supply Chain Management.
Coello Coello, C. A., & Lechuga, M. S. (2002). MOPSO: A proposal for multiple objective particle swarm optimization. Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002, 2, 1051–1056. https://doi.org/10.1109/CEC.2002.1004388
Conway, R., Maxwell, W., McClain, J. O., & Thomas, L. J. (1988). The Role of Work-in-Process Inventory in Serial Production Lines. Operations Research, 36(2), 229–241. https://doi.org/10.1287/opre.36.2.229
Darwish, M. A. (2008). EPQ models with varying setup cost. International Journal of Production Economics, 113(1), 297–306. https://doi.org/10.1016/j.ijpe.2007.07.010
Diabat, A. (2014). Hybrid algorithm for a vendor managed inventory system in a two-echelon supply chain. European Journal of Operational Research, 238(1), 114–121. https://doi.org/10.1016/j.ejor.2014.02.061
Fattahi, P., Hajipour, V., & Nobari, A. (2015). A bi-objective continuous review inventory control model: Pareto-based meta-heuristic algorithms. Applied Soft Computing Journal, 32, 211–223. https://doi.org/10.1016/j.asoc.2015.02.044
Goyal, S. K. (1976). An integrated inventory model for a single supplier- single customer problem. International Journal of Production Research, 15(1), 107–111. https://doi.org/http://dx.doi.org/10.1080/00207547708943107
Grubbström, R. W., & Erdem, A. (1999). EOQ with backlogging derived without derivatives. International Journal of Production Economics, 59(1), 529–530. https://doi.org/10.1016/S0925-5273(98)00015-2
Guo, X., Liu, C., Xu, W., Yuan, H., & Wang, M. (2014). A prediction-based inventory optimization using data mining models. Proceedings - 2014 7th International Joint Conference on Computational Sciences and Optimization, CSO 2014, 611–615. https://doi.org/10.1109/CSO.2014.118
Hayek, P. A., & Salameh, M. K. (2001). Production lot sizing with the reworking of imperfect quality items produced. Production Planning & Control, 12(6), 584–590.
Huang, B., & Wu, A. (2016). EOQ model with batch demand and planned backorders. Applied Mathematical Modelling (Vol. 40). Elsevier Inc. https://doi.org/10.1016/j.apm.2016.01.004
Huseyinov, I., & Bayrakdar, A. (2019). Performance Evaluation of NSGA-III and SPEA2 in Solving a Multi-Objective Single-Period Multi-Item Inventory Problem. UBMK 2019 - Proceedings, 4th International Conference on Computer Science and Engineering, (4), 531–535. https://doi.org/10.1109/UBMK.2019.8907139
Jones, D. F., Mirrazavi, S. K., & Tamiz, M. (2002). Multi-objective meta-heuristics: An overview of the current state-of-the-art. European Journal of Operational Research, 137(1), 1–9.
Kanyalkar, A. P., & Adil, G. K. (2005). An integrated aggregate and detailed planning in a multi-site production environment using linear programming. International Journal of Production Research, 43(20), 4431–4454. https://doi.org/10.1080/00207540500142332
Kennedy, J., & Eberhart, R. (1995). Particle Swarm Optimization Proceedings., IEEE International Conference. Proceedings of ICNN’95 - International Conference on Neural Networks, 11(1), 111–117.
Kim, E., & Park, T. (2016). Admission and inventory control of a single-component make-to-order production system with replenishment setup cost and lead time. European Journal of Operational Research, 255(1), 91–102. https://doi.org/10.1016/j.ejor.2016.04.021
Kodama, M. (1995). Some Probabilistic Multiperiod Inventory Problems. IFAC Proceedings Volumes, 28(7), 217–222. https://doi.org/10.1016/S1474-6670(17)47112-6
Lenard, J. D., & Roy, B. (1995). Multi-item inventory control: A multicriteria view. European Journal of Operational Research, 87(3), 685–692. https://doi.org/10.1016/0377-2217(95)00239-1
Gen, M. and Cheng, R. (1997) Genetic Algorithms & Engineering Design. John Wiley & Sons, Inc., Hoboken.
Mandal, N. K., Roy, T. K., & Maiti, M. (2006). Inventory model of deteriorated items with a constraint: A geometric programming approach. European Journal of Operational Research, 173(1), 199–210.
Mirzapour Al-e-Hashem, S. M. J., & Rekik, Y. (2014). Multi-product multi-period Inventory Routing Problem with a transshipment option: A green approach. International Journal of Production Economics, 157(1), 80–88. https://doi.org/10.1016/j.ijpe.2013.09.005
Mirzazadeh, A., Fatemi Ghomi, S. M. T., & Seyed Esfahani, M. M. (2011). A multiple items inventory model under uncertain external inflationary conditions. Trends in Applied Sciences Research, 6(5), 472–480.
Moosavi, V., Talebi, A., & Shirmohammadi, B. (2014). Producing a landslide inventory map using pixel-based and object-oriented approaches optimized by Taguchi method. Geomorphology, 204, 646–656. https://doi.org/10.1016/j.geomorph.2013.09.012
Mousavi, S. M., Niaki, S. T. A., Bahreininejad, A., & Musa, S. N. (2014). Multi-item multiperiodic inventory control problem with variable demand and discounts: A particle swarm optimization algorithm. Scientific World Journal, 2014. https://doi.org/10.1155/2014/136047
Niu, B., Tan, L., Liu, J., Liu, J., Yi, W., & Wang, H. (2019). Cooperative bacterial foraging optimization method for multi-objective multi-echelon supply chain optimization problem. Swarm and Evolutionary Computation, 49(May 2018), 87–101. https://doi.org/10.1016/j.swevo.2019.05.003
Park, K., & Kyung, G. (2014). Optimization of total inventory cost and order fill rate in a supply chain using PSO. International Journal of Advanced Manufacturing Technology, 70(9–12), 1533–1541. https://doi.org/10.1007/s00170-013-5399-6
Pasandideh, S. H. R., Niaki, S. T. A., & Sharafzadeh, S. (2013). Optimizing a bi-objective multi-product EPQ model with defective items, rework and limited orders: NSGA-II and MOPSO algorithms. Journal of Manufacturing Systems, 32(4), 764–770. https://doi.org/10.1016/j.jmsy.2013.08.001
Rau, H., Daniel, S., & Agus, G. (2018). Optimization of the multi-objective green cyclical inventory routing problem using discrete multi-swarm PSO method. Transportation Research Part E, 120(September), 51–75. https://doi.org/10.1016/j.tre.2018.10.006
Roozbeh Nia, A., Hemmati Far, M., & Niaki, S. T. A. (2015). A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage. Applied Soft Computing Journal, 30, 353–364. https://doi.org/10.1016/j.asoc.2015.02.004
Rossi, T., Pozzi, R., & Testa, M. (2017). EOQ-based inventory management in single-machine multi-item systems. Omega (United Kingdom), 71, 106–113. https://doi.org/10.1016/j.omega.2016.10.002
Roy, T. K., & Maiti, M. (1998). Multi-objective inventory models of deteriorating items with some constraints in a fuzzy environment. Computers & Operations Research, 25(12), 1085–1095.
S Akindipe, O. (2014). The Role of Raw Material Management in Production Operations. International Journal of Managing Value and Supply Chains, 5(3), 37–44. https://doi.org/10.5121/ijmvsc.2014.5303
Sadeghi, J., Mousavi, S. M., Niaki, S. T. A., & Sadeghi, S. (2014). Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm. Transportation Research Part E: Logistics and Transportation Review, 70(1), 274–292. https://doi.org/10.1016/j.tre.2014.07.007
Sarwar, F., Rahman, M., & Ahmed, M. (2019). A Multi-Item Inventory Control Model using Multi Objective Particle Swarm Optimization ( MOPSO ), 1311–1321.
Scholkopf, B., Sung, K.-K., Burges, C. J. C., Girosi, F., Niyogi, P., Poggio, T., & Vapnik, V. (1997). Comparing support vector machines with Gaussian kernels to radial basis function classifiers. IEEE Transactions on Signal Processing, 45(11), 2758–2765.
Schott, J. (1995). Fault Tolerant Design Using Single and Multi-Criteria Genetic Algorithms. Master's Thesis, Department of Aeronautics and Astronautics, Massachusetts Institute of Technology.
Sutrisno, & Wicaksono, P. A. (2015). Optimal Strategy for Multi-product Inventory System with Supplier Selection by Using Model Predictive Control. Procedia Manufacturing, 4(Iess), 208–215. https://doi.org/10.1016/j.promfg.2015.11.033
Taft, E. W. (1918). The most economical production lot. Iron Age, 101(18), 1410–1412.
Taguchi, G. (1990). Introduction to quality engineering, Tokyo. Asian Productivity Organization.
Taleizadeh, A A, Moghadasi, H., Niaki, S. T. A., & Eftekhari, A. (2008). An economic order quantity under joint replenishment policy to supply expensive imported raw materials with payment in advance. Journal of Applied Sciences. https://doi.org/10.3923/jas.2008.4263.4273
Taleizadeh, Ata Allah, Niaki, S. T. A., & Aryanezhad, M. B. (2009). A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments. Mathematical and Computer Modelling, 49(5–6), 1044–1057. https://doi.org/10.1016/j.mcm.2008.10.013
Taleizadeh, Ata Allah, Niaki, S. T. A., Aryanezhad, M. B., & Shafii, N. (2013). A hybrid method of fuzzy simulation and genetic algorithm to optimize constrained inventory control systems with stochastic replenishments and fuzzy demand. Information Sciences, 220, 425–441. https://doi.org/10.1016/j.ins.2012.07.027
Taleizadeh, Ata Allah, Niaki, S. T. A., Shafii, N., Meibodi, R. G., & Jabbarzadeh, A. (2010). A particle swarm optimization approach for constraint joint single buyer-single vendor inventory problem with changeable lead time and (r,Q) policy in supply chain. International Journal of Advanced Manufacturing Technology, 51(9–12), 1209–1223. https://doi.org/10.1007/s00170-010-2689-0
Tavana, M. (2016). A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms : NSGA-II , NRGA , and MOPSO, 43, 57–72.
Tiwari, S., Daryanto, Y., & Wee, H. M. (2018). Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. Journal of Cleaner Production, 192, 281–292. https://doi.org/10.1016/j.jclepro.2018.04.261
Van Veldhuizen, D. A. (1999). Multiobjective Evolutionary Algorithms: Classifications, Analyses, and New Innovations. Ph. D. thesis, Air Force Institute of Technology Wright-Pattersonafb OH School of Engineering.
Wang, Gaige, Guo, L., Duan, H., Liu, L., & Wang, H. (2012). A bat algorithm with mutation for UCAV path planning. The Scientific World Journal, 2012. https://doi.org/10.1100/2012/418946
Wang, Guanghui. (2012). Demand forecasting of supply chain based on Support Vector Regression method. Procedia Engineering, 29, 280–284. https://doi.org/10.1016/j.proeng.2011.12.707
Wu, Q. (2010). Product demand forecasts using wavelet kernel support vector machine and particle swarm optimization in manufacture system. Journal of Computational and Applied Mathematics, 233(10), 2481–2491. https://doi.org/10.1016/j.cam.2009.10.030
Yang, X. S., (2011), Bat Algorithm for Multiobjective Optimization, International Journal of Bio-Inspired Computation, 3(5), 267-274.
Yang, X. S., & He, X. (2013). Bat algorithm: literature review and applications. International Journal of Bio-Inspired Computation, 5(3), 141. https://doi.org/10.1504/IJBIC.2013.055093
Zitzler, E., & Thiele, L. (1998). Multiobjective optimization using evolutionary algorithms - A comparative case study. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1498 LNCS(September), 292–301. https://doi.org/10.1007/bfb0056872