Integrated low-carbon distribution system for the demand side of a product distribution supply chain: a DoE-guided MOPSO optimiser-based solution approach

References

• Abdelmaguid, T. F., and M. M. Dessouky. 2006. “A Genetic Algorithm Approach to the Integrated Inventory-distribution Problem.” International Journal of Production Research 44 (21): 4445–4464.
   Web of Science ®Google Scholar
• Adner, R., and D. Snow. 2010. “Old Technology Responses to New Technology Threats: Demand Heterogeneity and Technology Retreats.” Industrial and Corporate Change 19 (5): 1655–1675.
   Web of Science ®Google Scholar
• Aksen, D., and K. Altinkemer. 2008. “A Location-routing Problem for the Conversion to the “click-and-mortar” Retailing: The Static Case.” European Journal of Operational Research 186 (2): 554–575.
   Web of Science ®Google Scholar
• Alumur, S., and B. Y. Kara. 2007. “A New Model for the Hazardous Waste Location-routing Problem.” Computers & Operations Research 34 (5): 1406–1423.
   Web of Science ®Google Scholar
• Ambrosino, D., and M. G. Scutellà. 2005. “Distribution Network Design: New Problems and Related Models.” European Journal of Operational Research 165 (3): 610–624.
   Web of Science ®Google Scholar
• Aronsson, H., and M. H. Brodin. 2006. “The Environmental Impact of Changing Logistics Structures.” The International Journal of Logistics Management 17 (3): 394–415.
   Google Scholar
• Balakrishnan, A., J. E. Ward, and R. T. Wong. 1987. “Integrated Facility Location and Vehicle Routing Models: Recent Work and Future Prospects.” American Journal of Mathematical and Management Sciences 7 (1–2): 35–61.
   Google Scholar
• Benjaafar, S., Y. Li, and M. Daskin. 2013. “Carbon Footprint and the Management of Supply Chains: Insights from Simple Models.” IEEE Transactions on Automation Science and Engineering 10 (1): 99–116.
   Web of Science ®Google Scholar
• Berger, R. 1997. “Location-routing Models for Distribution System Design.” Ph.D diss., Department of Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA.
   Google Scholar
• Berger, R. T., C. R. Coullard, and M. S. Daskin. 2007. “Location-routing Problems with Distance Constraints.” Transportation Science 41 (1): 29–43.
   Web of Science ®Google Scholar
• Bräysy, O., P. P. Porkka, W. Dullaert, P. P. Repoussis, and C. D. Tarantilis. 2009. “A Well-scalable Metaheuristic for the fleet Size and Mix Vehicle Routing Problem with Time Windows.” Expert Systems with Applications 36 (4): 8460–8475.
   Web of Science ®Google Scholar
• Breedam, A. V. 2001. “Comparing Descent Heuristics and Metaheuristics for the Vehicle Routing Problem.” Computers & Operations Research 28 (4): 289–315.
   Web of Science ®Google Scholar
• Brimer, R. C. 1995. “Logistics Networking.” Logistics Information Management 8 (4): 8–11.
   Google Scholar
• Caballero, R., M. González, F. M. Guerrero, J. Molina, and C. Paralera. 2007. “Solving a Multiobjective Location Routing Problem with a Metaheuristic Based on Tabu Search: Application to a Real Case in Andalusia.” European Journal of Operational Research 177 (3): 1751–1763.
   Web of Science ®Google Scholar
• Cappanera, P., G. Gallo, and F. Maffioli. 2004. “Discrete Facility Location and Routing of Obnoxious Activities.” Discrete Applied Mathematics 133 (1–3): 3–28.
   Web of Science ®Google Scholar
• Chan, Y., W. B. Carter, and M. D. Burnes. 2001. “A Multiple-depot, Multiple-vehicle, Location-routing Problem with Stochastically Processed Demands.” Computers and Operations Research 28 (8): 803–826.
   Web of Science ®Google Scholar
• Coello Coello, C. A., and M. S. Lechuga. 2002. “MOPSO: A Proposal for Multiple Objective Particle Swarm Optimization.” Proceedings of the 2002 Congress on Evolutionary Computation, 12–17 May, Honolulu: HI 2: 1051–1056.
   Google Scholar
• Coello Coello, C. A., G. T. Pulido, and M. S. Lechuga. 2004. “Handling Multiple Objectives with Particle Swarm Optimization.” IEEE Transactions on Evolutionary Computation 8 (3): 256–279.
   Web of Science ®Google Scholar
• Daskin, M. S., L. V. Snyder, and R. T. Berger. 2005. “Facility Location in Supply Chain Design.” In Logistics Systems: Design and Optimization, edited by A. Langevin and D. Riopel, 39–65. New York: Springer.
   Google Scholar
• DEFRA (Department for Environment, Food and Rural Affairs). 2008. Guidelines to Defra’s GHG Conversion Factors: Methodology Paper for Transport Emission Factors. London: UK.
   Google Scholar
• Diabat, A., and D. Simchi-Levi. 2009. “A Carbon-capped Supply Chain Network Problem.” Proceedings of the IEEE International Conference on Industrial Engineering and Engineering Management, 8–11 December 2009, Hong Kong, 523–527.
   Google Scholar
• Eiselt, H. A., and G. Laporte. 1989. “Integrated Planning in Distribution Systems.” International Journal of Physical Distribution and Materials Management 19 (4): 14–19.
   Google Scholar
• Esteco. 2012. modeFRONTIER^® 4 User Manual. Accessed October 19. http://www.esteco.com/home/mode_frontier/mode_frontier.html
   Google Scholar
• Fieldsend, J. E., and S. Singh. 2002. “A Multi-objective Algorithm Based Upon Particle Swarm Optimisation, an Efficient Data Structure and Turbulence.” Proceedings of the 2002 U.K. Workshop on Computational Intelligence 6: 37–44, Birmingham, UK.
   Google Scholar
• Golden, B. L., and C. C. Skiscim. 1986. “Using Simulated Annealing to Solve Routing and Location Problems.” Naval Research Logistics Quarterly 33 (2): 261–279.
   Google Scholar
• Gunnarsson, H., M. Rönnqvist, and D. Carlsson. 2006. “A Combined Terminal Location and Ship Routing Problem.” Journal of the Operational Research Society 57 (8): 928–938.
   Web of Science ®Google Scholar
• Hansen, P. H., B. Hegedahl, S. Hjortkjær, and B. Obel. 1994. “A Heuristic Solution to the Warehouse Location-routing Problem.” European Journal of Operational Research 76 (1): 111–127.
   Web of Science ®Google Scholar
• Holmström, J., T. Ala-Risku, J. Auramo, J. Collin, E. Eloranta, and A. Salminen. 2010. “Demand-supply Chain Representation: A Tool for Economic Organizing of Industrial Services.” Journal of Manufacturing Technology Management 21 (3): 376–387.
   Google Scholar
• Hu, X., and R. Eberhart. 2002. “Multiobjective Optimization Using Dynamic Neighborhood Particle Swarm Optimization.” Proceedings of the 2002 Congress on Evolutionary Computation 2: 1677–1681.
   Google Scholar
• Hwang, C. L., and K. Yoon. 1981. Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems, 186. Berlin: Springer-Verlag.
   Google Scholar
• Institute of Grocery Distribution. 2009. UK Food & Grocery Retail Logistics Overview. IGD, Accessed December 13 2012. http://www.igd.com/Retail_Logistics_Overview#1
   Google Scholar
• Jacobsen, S. K., and O. B. G. Madsen. 1980. “A Comparative Study of Heuristics for a Two-level Routing-location Problem.” European Journal of Operational Research 5 (6): 378–387.
   Web of Science ®Google Scholar
• Jha, J. K., and K. Shanker. 2013. “A Coordinated Two-phase Approach for Operational Decisions with Vehicle Routing in a Single-vendor Multi-buyer System.” International Journal of Production Research 51 (5): 1426–1450.
   Web of Science ®Google Scholar
• Kennedy, J., and R. Eberhart. 1995. “Particle Swarm Optimization.” In: Proceedings of 1995 IEEE International Conference on Neural Networks 4: 1942–1948.
   Google Scholar
• Kenyon, A. S., and D. P. Morton. 2001. “A Survey on Stochastic Location and Routing Problems.” Central European Journal of Operations Research 9 (4): 277–328.
   Google Scholar
• Kulcar, T. 1996. “Optimizing Solid Waste Collection in Brussels.” European Journal of Operational Research 90 (1): 71–77.
   Web of Science ®Google Scholar
• Kumar, S., S. Teichman, and T. Timpernagel. 2012. “A Green Supply Chain is a Requirement for Profitability.” International Journal of Production Research 50 (5): 1278–1296.
   Web of Science ®Google Scholar
• Laporte, G. 1988. “Location-routing Problems.” In Vehicle Routing: Methods and Studies, edited by B. L. Golden and A. A. Assad, 163–198. Amsterdam: North-Holland.
   Google Scholar
• Laporte, G., and I. H. Osman. 1995. “Routing Problems: A Bibliography.” Annals of Operations Research 61 (1): 227–262.
   Web of Science ®Google Scholar
• Laporte, G., N. Nobert, and D. Arpin. 1986. “An Exact Algorithm for Solving a Capacitated Location-Routing Problem.” Annals of Operations Research 6 (9): 291–310.
   Google Scholar
• Laporte, G., Y. Nobert, and S. Taillefer. 1988. “Solving a Family of Multi-Depot Vehicle Routing and Location-Routing Problems.” Transportation Science 22 (3): 161–172.
   Web of Science ®Google Scholar
• Laporte, G., F. V. Louveaux, and H. Mercure. 1989. “Models and Exact Solutions for a Class of Stochastic Location-routing Problems.” European Journal of Operational Research 39 (1): 71–78.
   Web of Science ®Google Scholar
• Lee, J.-H., I.-K. Moon, and J.-H. Park. 2010. “Multi-level Supply Chain Network Design with Routing.” International Journal of Production Research 48 (13): 3957–3976.
   Web of Science ®Google Scholar
• Lewis, M. W. 2009. “On the Use of Guided Design Search for Discovering Significant Decision Variables in The Fixed-charge Capacitated Multicommodity Network Design Problem.” Networks 53 (1): 6–18.
   Web of Science ®Google Scholar
• Lin, C. K. Y., C. K. Chow, and A. Chen. 2002. “A Location-routing-loading Problem for Bill Delivery Services.” Computers & Industrial Engineering 43 (1–2): 5–25.
   Web of Science ®Google Scholar
• Liu, H., W. Wang, and Q. Zhang. 2012. “Multi-objective Location-routing Problem of Reverse Logistics Based on GRA with Entropy Weight.” Grey Systems: Theory and Application 2 (2): 249–258.
   Google Scholar
• Madsen, O. B. G. 1983. “Methods for Solving Combined Two Level Location-routing Problems for Realistic Dimensions.” European Journal of Operational Research 12 (3): 295–301.
   Web of Science ®Google Scholar
• Manzini, R., and E. Gebennini. 2008. “Optimization Models for the Dynamic Facility Location and Allocation Problem.” International Journal of Production Research 46 (8): 2061–2086.
   Web of Science ®Google Scholar
• Marinakis, Y., and M. Marinaki. 2008. “A Particle Swarm Optimization Algorithm with Path Relinking for the Location Routing Problem.” Journal of Mathematical Modelling and Algorithms 7 (1): 59–78.
   Google Scholar
• Min, H., V. Jayaraman, and R. Srivastava. 1998. “Combined Location-routing Problems: A Synthesis and Future Research Directions.” European Journal of Operational Research 108 (1): 1–15.
   Web of Science ®Google Scholar
• Mostaghim, S., and J. Teich. 2003. “Strategies for finding good local guides in multi-objective particle swarm optimization (MOPSO).” Proceedings of the 2003 IEEE Swarm Intelligence Symposium, Indianapolis, Indiana, USA, April 6: 24–26, 26–33.
   Google Scholar
• Nagy, G., and S. Salhi. 2007. “Location-routing: Issues, Models and Methods.” European Journal of Operational Research 177 (2): 649–672.
   Web of Science ®Google Scholar
• Parsopoulos, K. E., and M. N. Vrahatis. 2002. “Particle Swarm Optimization Method in Multiobjective Problems.” Proceedings of the 2002 ACM Symposium on Applied Computing, Madrid: Spain 603–607.
   Google Scholar
• Perl, J., and M. S. Daskin. 1984. “A Unified Warehouse Location-routing Methodology.” Journal of Business Logistics 5 (1): 92–111.
   Google Scholar
• Perl, J., and M. S. Daskin. 1985. “A Warehouse Location-routing Problem.” Transportation Research Part B: Methodological 19 (5): 381–396.
   Web of Science ®Google Scholar
• Priem, R. L., and M. Swink. 2012. “A Demand-side Perspective on Supply Chain Management.” Journal of Supply Chain Management 48 (2): 7–13.
   Web of Science ®Google Scholar
• Prins, C., C. Prodhon, A. Ruiz, P. Soriano, and R. W. Calvo. 2007. “Solving the Capacitated Location-routing Problem by a Cooperative Lagrangean Relaxation-granular Tabu Search Heuristic.” Transportation Science 41 (4): 470–483.
   Web of Science ®Google Scholar
• Prins, C., N. Labadi, and M. Reghioui. 2009. “Tour Splitting Algorithms for Vehicle Routing Problems.” International Journal of Production Research 47 (2): 507–535.
   Web of Science ®Google Scholar
• Raquel, C. R., and P. C. Naval Jr., 2005. “An Effective Use of Crowding Distance in Multiobjective Particle Swarm Optimization.” Proceedings of the 2005 Conference on Genetic and Evolutionary Computation 257–264, ACM, New York, USA.
   Google Scholar
• Reyes-Sierra, M., and C. A. Coello Coello. 2005. Improving PSO-based multi-objective optimization using crowding, mutation and ε-dominance. Lecture Notes in Computer Science. vol. 3410. Berlin Heidelberg: Springer-Verlag, 505–519.
   Google Scholar
• Reyes-Sierra, M., and C. A. Coello Coello. 2006. “Multi-objective particle Swarm Optimizers: A Survey of the State-of-the-art.” International Journal of Computational Intelligence Research 2 (3): 287–308.
   Google Scholar
• Saaty, T. L. 1977. “A Scaling Method for Priorities in Hierarchical Structures.” Journal of Mathematical Psychology 15 (3): 234–281.
   Web of Science ®Google Scholar
• Seuring, S., and M. Müller. 2008. “From a Literature Review to a Conceptual Framework for Sustainable Supply Chain Management.” Journal of Cleaner Production 16 (15): 1699–1710.
   Web of Science ®Google Scholar
• Sha, D. Y., and H.-H. Lin. 2010. “A Multi-objective PSO for Job-shop Scheduling Problems.” Expert Systems with Applications 37 (2): 1065–1070.
   Web of Science ®Google Scholar
• Srivastava, R. 1993. “Alternate Solution Procedures for the Location-routing Problem.” Omega 2 (4): 497–506.
   Web of Science ®Google Scholar
• Srivastava, S. K. 2007. “Green Supply Chain Management: A State-of-the-art literature Review.” International Journal of Management Reviews 9 (1): 53–80.
   Web of Science ®Google Scholar
• Srivastava, R., and W. C. Benton. 1990. “The Location-Routing Problem: Considerations in Physical Distribution System Design.” Computers & Operations Research 17 (5): 427–435.
   Web of Science ®Google Scholar
• Stenger, A., M. Schneider, M. Schwind, and D. Vigo. 2012. “Location Routing for Small Package Shippers with Subcontracting Options.” International Journal of Production Economics 140 (2): 702–712.
   Web of Science ®Google Scholar
• Tarantilis, C. D., M. Gendreau, and D. Spinellis. 2005. “The Impact of Metaheuristic Strategies in Transportation and Logistics Applications.” IEEE Intelligent Systems 20 (4): 16–18.
   Web of Science ®Google Scholar
• Taylor, D. H. 2006. “Demand Management in Agri-food Supply Chains: An Analysis of the Characteristics and Problems and a Framework for Improvement.” The International Journal of Logistics Management 17 (2): 163–186.
   Google Scholar
• The Irish Co-operative Organisation Society (ICOS). Accessed December 18 2012. http://www.icos.i.e./supply-chain/dairy-supply-chain-intro/.
   Google Scholar
• Tuzun, D., and L. I. Burke. 1999. “A Two-phase Tabu Search Approach to the Location Routing Problem.” European Journal of Operational Research 116 (1): 87–99.
   Web of Science ®Google Scholar
• Vachon, S. 2007. “Green Supply Chain Practices and the Selection of Environmental Technologies.” International Journal of Production Research 45 (18–19): 4357–4379.
   Web of Science ®Google Scholar
• Validi, S., A. Bhattacharya, and P. J. Byrne. 2012. “Greening the Irish food market supply-chain through minimal carbon emission: an integrated multi-objective location-routing approach.” In: T. Baines, B. Clegg, and D. Harrison (Eds.), Proceedings of the 10th International Conference on Manufacturing Research, Vol. 2, 11-13th September, Birmingham, UK, pp. 805–810.
   Google Scholar
• Walpole, R. E., R. Myers, and S. L. Myers. 2006. Probability & Statistics for Engineers & Scientists. 8th ed. Pearson: Prentice Hall.
   Google Scholar
• Wu, H.-J., and S. C. Dunn. 1995. “Environmentally Responsible Logistics Systems.” International Journal of Physical Distribution & Logistics Management 25 (2): 20–38.
   Google Scholar
• Yang, P., and C. Zi-Xia. 2009. “Two-phase Particle Swarm Optimization for Multi-depot Location-routing Problem.” In: Proceedings of International Conference on New Trends in Information and Service Science. Beijing, 30 June–2 July 240–245.
   Google Scholar
• Ye, G., R. L. Priem, and A. Alshwer. 2012. “Achieving Demand-side Synergy from Strategic Diversification: How Combining Mundane Assets Can Leverage Consumer Utilities.” Organization Science 23: 207–224.
   Web of Science ®Google Scholar
• Zhu, Q., and J. Sarkis. 2007. “The Moderating Effects of Institutional Pressures on Emergent Green Supply Chain Practices and Performance.” International Journal of Production Research 45 (18–19): 4333–4355.
   Web of Science ®Google Scholar
• Zitzler, E., K. Deb, and L. Thiele. 2000. “Comparison of Multiobjective Evolutionary Algorithms: Empirical Results.” Evolutionary Computation 8 (2): 173–195.
   PubMed Web of Science ®Google Scholar