Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain

DOI: 10.4236/iim.2015.76025   PDF   HTML   XML   5,071 Downloads   6,050 Views   Citations


This paper presents four different hybrid genetic algorithms for network design problem in closed loop supply chain. They are compared using a complete factorial experiment with two factors, viz. problem size and algorithm. Based on the significance of the factor “algorithm”, the best algorithm is identified using Duncan’s multiple range test. Then it is compared with a mathematical model in terms of total cost. It is found that the best hybrid genetic algorithm identified gives results on par with the mathematical model in statistical terms. So, the best algorithm out of four algorithm proposed in this paper is proved to be superior to all other algorithms for all sizes of problems and its performance is equal to that of the mathematical model for small size and medium size problems.

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Aravendan, M. and Panneerselvam, R. (2015) Development and Comparison of Hybrid Genetic Algorithms for Network Design Problem in Closed Loop Supply Chain. Intelligent Information Management, 7, 313-338. doi: 10.4236/iim.2015.76025.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Goldberg, D.E. and Deb, K. (1991) A Comparative Analysis of Selection Schemes Used in Genetic Algorithms. In: Rawlins, G., Ed., Foundations of Genetic Algorithms, Morgan Kaufmann Publishers, San Francisco, 69-93.
[2] Srinivas, N. and Deb, K. (1994) Multi-Objective Optimization Using Non-Dominated Sorting in Genetic Algorithms. Journal of Evolutionary Computation, 2, 221-248.
[3] Golub, M. (1996) An Implementation of Binary and Floating Point Chromosome Representation in Genetic Algorithm. Proceedings of the 18th International Conference ITI, Pula, 18-21 June 1996, 417-422.
[4] Deb, K. (1999) An Introduction to Genetic Algorithm. Sadhana, 24, 293-315.
[5] Lin, W.-Y., Lee, W.-Y. and Hong, T.-P. (2003) Adapting Crossover and Mutation Rates in Genetic Algorithms. Journal of Information Science and Engineering, 19, 889-903.
[6] Sim, E., Jung, S., Kim, H. and Park, J. (2004) A Generic Network Design for a Closed-Loop Supply Chain Using Genetic Algorithm. Lecture Notes in Computer Science, 3103, 1214-1225.
[7] Yeh, W.-C. (2005) A Hybrid Heuristic Algorithm for the Multistage Supply Chain Network Problem. International Journal of Advanced Manufacturing Technology, 26, 675-685.
[8] Altiparmak, F., Gen, M., Lin, L. and Paksoy, T. (2006) A Genetic Algorithm Approach for Multi-Objective Optimization of Supply Chain Networks. Computers & Industrial Engineering, 51, 196-215.
[9] Min, H., Ko, C.S. and Ko, H.J. (2006) The Spatial and Temporal Consolidation of Returned Products in a Closed-Loop Supply Chain Network. Computers & Industrial Engineering, 51, 309-320.
[10] El-Mihoub, T.A., Hopgood, A.A., Nolle, L. and Battersby, A. (2006) Hybrid Genetic Algorithms: A Review. Engineering Letters, 13, 124-137.
[11] Zhou, G., Cao, Z., Qi, F. and Cao, J. (2006) A Genetic Algorithm Approach on a Logistics Distribution System with Uncertain Demand and Product Return. World Journal of Modelling and Simulation, 2, 99-108.
[12] Schultmann, F., Zumkeller, M. and Rentz, O. (2006) Modeling Reverse Logistic Tasks within Closed-Loop Supply Chains: An Example from the Automotive Industry. European Journal of Operational Research, 171, 1033-1050.
[13] Altiparmak, F., Gen, M., Lin, L. and Karaoglan, I. (2007) A Steady-State Genetic Algorithm for Multi-Product Supply Chain Network Design. Computers & Industrial Engineering, 56, 521-537.
[14] Lin, L., Gen, M. and Wang, X. (2007) A Hybrid Genetic Algorithm for Logistics Network Design with Flexible Multistage Model. International Journal of Information Systems for Logistics and Management, 3, 1-12.
[15] Staikos, T. and Rahimifard, S. (2007) A Decision-Making Model for Waste Management in the Footwear Industry. Journal of Production Research, 45, 4403-4422.
[16] Ko, H.J. and Evans, G.W. (2007) A Genetic Algorithm-Based Heuristic for the Dynamic Integrated Forward/Reverse Logistics Network for 3PLs. Computers & Operations Research, 34, 346-366.
[17] Min, H. and Ko, H.-J. (2008) The Dynamic Design of a Reverse Logistics Network from the Perspective of Third-Party Logistics Service Providers. International Journal of Production Economics, 113, 176-192.
[18] Belgasmi, N., Said, L.B. and Ghedira, K. (2008) Genetic Optimization of the Multi-Location Transshipment Problem with Limited Storage Capacity. Proceedings of the 18th European Conference on Artificial Intelligence, Patras, 21-25 July 2008, 563-567.
[19] Farahania, R.Z. and Elahipanaha, M. (2008) A Genetic Algorithm to Optimize the Total Cost and Service Level for Just-in-Time Distribution in a Supply Chain. International Journal of Production Economics, 111, 229-243.
[20] Lee, D.H. and Dong, M. (2008) A Heuristic Approach to Logistics Network Design for End-of-Lease Computer Products Recovery. Transportation Research Part E, 44, 455-474.
[21] Yun, Y.S., Moon, C. and Kim, D. (2009) Hybrid Genetic Algorithm with Adaptive Local Search Scheme for Solving Multi-Stage Based Supply Chain Problems. Computers & Industrial Engineering, 56, 821-838.
[22] Sourirajan, K., Ozsen, L. and Uzsoy, R. (2009) A Genetic Algorithm for a Single Product Network Design Model with Lead Time and Safety Stock Considerations. European Journal of Operational Research, 197, 599-608.
[23] Lee, J.-E., Gen, M. and Rhee, K.-G. (2009) Network Model and Optimization of Reverse Logistics by Hybrid Genetic Algorithm. Computers & Industrial Engineering, 56, 951-964.
[24] Gen, M., Lin, L. and Jo, J.-B. (2009) Evolutionary Network Design by Multi Objective Hybrid Genetic Algorithm. Intelligent and Evolutionary Systems, SCI 187, 105-121.
[25] Lin, L., Gen, M. and Wang, X. (2009) Integrated Multistage Logistics Network Design by Using Hybrid Evolutionary Algorithm. Computers & Industrial Engineering, 56, 854-873.
[26] Salema, M.I.G., Povoa, A.P.B. and Novais, A.Q. (2009) A Strategic and Tactical Model for Closed-Loop Supply Chains. OR Spectrum, 31, 573-599.
[27] Costa, A., Celano, G., Fichera, S. and Trovato, E. (2010) A New Efficient Encoding/Decoding Procedure for the Design of a Supply Chain Network with Genetic Algorithms. Computers & Industrial Engineering, 59, 986-999.
[28] Pishvaee, M.S., et al. (2010) A Memetic Algorithm for Bi-Objective Integrated Forward/Reverse Logistics Network Design. Computers & Operations Research, 37, 1100-1112.
[29] Zarei, M., Mansour, S., Kashan, A.H. and Karimi, B. (2010) Designing a Reverse Logistics Network for End-of-Life Vehicles Recovery. Mathematical Problems in Engineering, 2010, 1-16.
[30] Kannan, G., Sasikumar, P. and Devika, K. (2010) A Genetic Algorithm Approach for Solving a Closed Loop Supply Chain Model: A Case of Battery Recycling. Applied Mathematical Modeling, 34, 655-670.
[31] El-Sayed, M., Afia, N. and El-Kharbotly, A. (2010) A Stochastic Model for Forward-Reverse Logistics Network Design under Risk. Computers & Industrial Engineering, 58, 423-431.
[32] Kaya, Y., Uyar, M. and Tekdn, R. (2011) A Novel Crossover Operator for Genetic Algorithms: Ring Crossover.
[33] Khajavi, L.T., Seyed-Hosseini, S.M. and Ahmad Makui, A. (2011) An Integrated Forward/Reverse Logistics Network Optimization Model for Multi-Stage Capacitated Supply Chain. iBusiness, 3, 229-235.
[34] Nandita, A. (2011) The Apparel Aftermarket in India—A Case Study Focusing on Reverse Logistics. Journal of Fashion Marketing and Management, 15, 211-227.
[35] Hosseinzadeh, M. and Roghanian, E. (2012) An Optimization Model for Reverse Logistics Network under Stochastic Environment Using Genetic Algorithm. International Journal of Business and Social Science, 3, 249-264.
[36] Kumar, R. and Jyotishree, (2012) Novel Encoding Scheme in Genetic Algorithms for Better Fitness. International Journal of Engineering and Advanced Technology (IJEAT), 1, 214-218.
[37] Bozorgirad, S., Desa, M.I. and Wibowo, A. (2012) Genetic Algorithm Enhancement to Solve Multi Source Multi Product Flexible Multistage Logistics Network. IJCSI International Journal of Computer Science Issues, 9, 157-164.
[38] Mehdizadeha, E. and Afrabandpeia, F. (2012) Design of a Mathematical Model for Logistic Network in a Multi-Stage Multi-Product Supply Chain Network and Developing a Meta Heuristic Algorithm. Journal of Optimization in Industrial Engineering, 10, 35-43.
[39] Iris, C. and Serdarasan, S. (2012) A Review of Genetic Algorithm Applications in Supply Chain Network Design. In: Kahraman, C., Ed., Computational Intelligence Systems in Industrial Engineering, Atlantis Press Book, Paris, 209-236.
[40] Zaki, S.A., Mousa, A.A.A., Geneedi, H.M. and Elmekawy, A.Y. (2012) Efficient Multi-Objective Genetic Algorithm for Solving Transportation, Assignment and Transshipment Problems. Applied Mathematics, 3, 92-99.
[41] Ozkir, V. and Basligil, H. (2012) Modeling Product-Recovery Processes in Closed-Loop Supply-Chain Network Design. International Journal of Production Research, 50, 2218-2233.
[42] Rafsanjani, M.K. and Eskandari, S. (2013) Using Segment Based Genetic Algorithm with Local Search to Find Approximate Solution for Multi-Stage Supply Chain Network Design Problem. Cankaya University Journal of Science and Engineering, 10, 185-201.
[43] Lee, J.-E., Chung, K.-Y., Lee, K.-D. and Gen, M. (2015) A Multi-Objective Hybrid Genetic Algorithm to Minimize the Total Cost and Delivery Tardiness in a Reverse Logistics. Multimedia Tools and Applications, 74, 9067-9085.
[44] Soleimani, H., Esfahani, M.H. and Shirazi, M.A. (2013) Designing and Planning a Multi Period Multi Product Closed-Loop Supply Chain Utilizing Genetic Algorithm. International Journal of Advanced Manufacturing Technology, 68, 917-931.
[45] Lee, J.-E. and Lee, K.-D. (2013) Modeling and Optimization of Closed-Loop Supply Chain Considering Order or Next Arrival of Goods. International Journal of Innovative Computing, Information and Control, 9, 3639-3654.
[46] Teodoro, F.G.S., Lima, C.A.M. and Peres, S.M. (2013) Supply Chain Management and Genetic Algorithm: Introducing a New Hybrid Genetic Crossover Operator.
[47] Ramezani, M., Bashiri, M. and Moghaddam, R.T. (2013) A New Multi-Objective Stochastic Model for a Forward/Reverse Logistic Network Design with Responsiveness and Quality Level. Applied Mathematical Modeling, 37, 328-344.
[48] Rosa, V.D., Gebhard, M., Hartmann, E. and Wollenweber, J. (2013) Robust Sustainable Bi-Directional Logistics Network Design under Uncertainty. International Journal of Production Economics, 145, 184-198.
[49] Mahmoudi, H., Fazlollahtabar, H. and Mahdavi, I. (2013) Mathematical Modeling for Minimizing Costs in a Multilayer Multi-Product Reverse Supply Chain. Industrial Engineering Management, 2, 1-6.
[50] Hafeti, S.M. and Jolai, F. (2013) Robust and Reliable Forward-Reverse Logistics Network Design under Demand Uncertainty and Facility Disruptions. Applied Mathematical Modeling, 38, 2630-2647.
[51] Cardoso, S.R., Paula, F.D.A., Povoa, B. and Relvas, S. (2013) Design and Planning of Supply Chains with Integration of Reverse Logistics Activities under Demand Uncertainty. European Journal of Operational Research, 226, 436-451.
[52] Devika, K., Jafarian, A. and Nourbakhash, V. (2014) Designing a Sustainable Closed-Loop Supply Chain Network Based on Triple Bottom Line Approach: A Comparison of Metaheuristics Hybridization Techniques. European Journal of Operational Research, 235, 594-615.
[53] Asghari, M. and Nezhadali, S. (2014) A Non-Dominated Sorting Genetic Algorithm for Sustainable Reverse Logistics Network Design. Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management, Bali, 7-9 January 2014, 2426-2436.
[54] Aggarwal, S., Garg, R. and Goswami, P. (2014) A Review Paper on Different Encoding Schemes Used in Genetic Algorithms. International Journal of Advanced Research in Computer Science and Engineering, 4, 596-600.
[55] Demirel, N., Ozceylan, E., Paksoy, T. and Gokcen, H. (2014) A Genetic Algorithm Approach for Optimizing a Closed-Loop Supply Chain Network with Crisp and Fuzzy Objectives. International Journal of Production Research, 52, 3637-3664.
[56] Dzupire, N.C. and Gyekye, Y.N. (2014) A Multi-Stage Supply Chain Network Optimization Using Genetic Algorithms. Mathematical Theory and Modeling, 4, 18-28.
[57] Rad, S.Y.B., Desa, M.I. and Azari, S.D. (2014) Model and Solve the Bi-Criteria Multi Source Flexible Multistage Logistics Network. International Journal of Advanced Computer Science and Information Technology (IJACSIT), 3, 50-69.
[58] Aravendan, M. and Panneerselvam, R. (2014) An Integrated Multi-Echelon Model for a Sustainable Closed Loop Supply Chain Network Design. Intelligent Information Management, 6, 257-279.
[59] Sarrafhaa, K., Rahmatia, S.H.A., Niaki, S.T.A. and Talab, A.Z. (2015) A Bi-Objective Integrated Procurement, Production, and Distribution Problem of a Multi-Echelon Supply Chain Network Design: A New Tuned MOEA. Computers & Operations Research, 54, 35-51.
[60] Pasandideh, S.H.R., Niaki, S.T.A. and Kobra, A. (2015) Bi-Objective Optimization of a Multi-Product Multi-Period Three-Echelon Supply Chain Problem under Uncertain Environments: NSGA-II and NRGA. Information Sciences, 292, 57-74.

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