A simple and robust Monte Carlo hybrid local search algorithm for the facility location problem

References

• Aikens, Charles H. 1985. “Facility Location Models for Distribution Planning.” European Journal of Operational Research 22 (3): 263–279. doi: 10.1016/0377-2217(85)90246-2
   Web of Science ®Google Scholar
• Al-Sultan, Khaled S., and Mohammad Abdulrahman Al-Fawzan. 1999. “A Tabu Search Approach to the Uncapacitated Facility Location Problem.” Annals of Operations Research 86: 91–103. doi:10.1023/A:1018956213524.
   Web of Science ®Google Scholar
• Arostegui, Marvin A., Sukran N. Kadipasaoglu, and Basheer M. Khumawala. 2006. “An Empirical Comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for Facilities Location Problems.” International Journal of Production Economics 103 (2): 742–754. doi:10.1016/j.ijpe.2005.08.010.
   Web of Science ®Google Scholar
• Arya, Vijay, Naveen Garg, Rohit Khandekar, Adam Meyerson, Kamesh Munagala, and Vinayaka Pandit. 2004. “Local Search Heuristics for k-Median and Facility Location Problems.” SIAM Journal on Computing 33 (3): 544–562. doi:10.1137/S0097539702416402.
   Web of Science ®Google Scholar
• Ayob, M., and G. Kendall. 2003. “A Monte Carlo Hyper-Heuristic to Optimise Component Placement Sequencing for Multi Head Placement Machine.” Proceedings of the international conference on intelligent technologies (InTech 2003), Chiang Mai, Thailand, Vol. 3, 132–141, December 17–19. http://www.cs.nott.ac.uk/pszgxk/papers/intech03mxa.pdf
   Google Scholar
• Bonami, P., L. T. Biegler, A. R. Conn, G. Cornuéjols, I. E. Grossmann, J. Laird, and C. D. Lee, et al. 2008. “An Algorithmic Framework for Convex Mixed Integer Nonlinear Programs.” Discrete Optimization 5 (2): 186–204. doi: 10.1016/j.disopt.2006.10.011
   Web of Science ®Google Scholar
• Canel, Cem, Basheer M. Khumawala, Japhett Law, and Anthony Loh. 2001. “An Algorithm for the Capacitated, Multi-Commodity Multi-Period Facility Location Problem.” Computers & Operations Research 28 (5): 411–427. doi: 10.1016/S0305-0548(99)00126-4
   Web of Science ®Google Scholar
• Chalupa, D., P. Balaghan, K. A. Hawick, and N. A. Gordon. 2017. “Computational Methods for Finding Long Simple Cycles in Complex Networks.” Knowledge-Based Systems 125: 96–107. doi:10.1016/j.knosys.2017.03.022.
   Web of Science ®Google Scholar
• Chalupa, D., and P. Nielsen. 2017. A Large-Scale Customer-Facility Network Model for Customer Service Centre Location Applications. Tech. Rep., Operations Research Group, Aalborg University, Denmark.
   Google Scholar
• Chalupa, D., and P. Nielsen. 2018. “Instance Scale, Numerical Properties and Design of Metaheuristics: A Study for the Facility Location Problem.” ArXiv e-prints https://arxiv.org/pdf/1801.03419
   Google Scholar
• Daskin, Mark S., Lawrence V. Snyder, and Rosemary T. Berger. 2005. “Facility Location in Supply Chain Design.” In Logistics Systems: Design and Optimization, edited by A. Langevin and D. Riopel, 39–65. Boston, MA: Springer. doi:10.1007/0-387-24977-X_2.
   Google Scholar
• Divéki, Gabriella, and Csanád Imreh. 2011. “Online Facility Location with Facility Movements.” Central European Journal of Operations Research 19 (2): 191–200. doi: 10.1007/s10100-010-0153-8
   Web of Science ®Google Scholar
• Do, N. A. D., I. E. Nielsen, G. Chen, and P. Nielsen. 2016. “A Simulation-Based Genetic Algorithm Approach for Reducing Emissions from Import Container Pick-Up Operation at Container Terminal.” Annals of Operations Research 242 (2): 285–301. doi: 10.1007/s10479-014-1636-0
   Web of Science ®Google Scholar
• Farahani, Reza Zanjirani, Maryam Abedian, and Sara Sharahi. 2009. “Dynamic Facility Location Problem.” In Facility Location, 347–372. Heidelberg, Germany: Springer-Verlag. doi:10.1007/978-3-7908-2151-2_15.
   Google Scholar
• Farahani, Reza Zanjirani, Maryam SteadieSeifi, and Nasrin Asgari. 2010. “Multiple Criteria Facility Location Problems: A Survey.” Applied Mathematical Modelling 34 (7): 1689–1709. http://www.sciencedirect.com/science/article/pii/S0307904X09003242 doi: 10.1016/j.apm.2009.10.005
   Web of Science ®Google Scholar
• Gola, Arkadiusz, and Grzegorz Kłosowski. 2018. “Application of Fuzzy Logic and Genetic Algorithms in Automated Works Transport Organization.” In Proceedings of the 14th International Conference on Distributed Computing and Artificial Intelligence (DCAI 2017), edited by S. Omatu, S. Rodríguez, G. Villarrubia, P. Faria, P. Sitek, and J. Prieto, 29–36. Vol. 620 in the series Advances in Intelligent Systems and Computing. Cham, Switzerland: Springer. doi:10.1007/978-3-319-62410-5_4.
   Google Scholar
• Gubbi, J., R. Buyya, S. Marusic, and M. Palaniswami. 2013. “Internet of Things (IoT): A Vision, Architectural Elements, and Future Directions.” Future Generation Computer Systems 29 (7): 1645–1660. doi: 10.1016/j.future.2013.01.010
   Web of Science ®Google Scholar
• Guha, Sudipto, and Samir Khuller. 1999. “Greedy Strikes Back: Improved Facility Location Algorithms.” Journal of Algorithms 31 (1): 228–248. doi: 10.1006/jagm.1998.0993
   Web of Science ®Google Scholar
• Guner, Ali R., and Mehmet Sevkli. 2008. “A Discrete Particle Swarm Optimization Algorithm for Uncapacitated Facility Location Problem.” Journal of Artificial Evolution and Applications. doi:10.1155/2008/861512.
   Google Scholar
• Jaramillo, Jorge H., Joy Bhadury, and Rajan Batta. 2002. “On the Use of Genetic Algorithms to Solve Location Problems.” Computers & Operations Research 29 (6): 761–779. doi: 10.1016/S0305-0548(01)00021-1
   Web of Science ®Google Scholar
• Khosiawan, Y., A. Khalfay, and I. Nielsen. 2018. “Scheduling Unmanned Aerial Vehicle and Automated Guided Vehicle Operations in an Indoor Manufacturing Environment Using Differential Evolution—Fused Particle Swarm Optimization.” International Journal of Advanced Robotic Systems 15 (1). doi:10.1177/1729881417754145.
   Web of Science ®Google Scholar
• Khosiawan, Y., Y. Park, I. Moon, J. M. Nilakantan, and I. Nielsen. 2018. “Task Scheduling System for UAV Operations in Indoor Environment.” Neural Computing and Applications 1–29. doi:10.1007/s00521-018-3373-9.
   Google Scholar
• Klose, Andreas, and Andreas Drexl. 2005. “Facility Location Models for Distribution System Design.” European Journal of Operational Research 162 (1): 4–29. doi: 10.1016/j.ejor.2003.10.031
   Web of Science ®Google Scholar
• Korupolu, Madhukar R., C. Greg Plaxton, and Rajmohan Rajaraman. 2000. “Analysis of a Local Search Heuristic for Facility Location Problems.” Journal of Algorithms 37 (1): 146–188. doi: 10.1006/jagm.2000.1100
   Web of Science ®Google Scholar
• Li, Shi. 2013. “A 1.488 Approximation Algorithm for the Uncapacitated Facility Location Problem.” Information and Computation 222: 45–58. doi:10.1016/j.ic.2012.01.007.
   Web of Science ®Google Scholar
• Li, Zixiang, Mukund Nilakantan Janardhanan, Qiuhua Tang, and Peter Nielsen. 2018. “Mathematical Model and Metaheuristics for Simultaneous Balancing and Sequencing of a Robotic Mixed-Model Assembly Line.” Engineering Optimization 50 (5): 877–893. doi: 10.1080/0305215X.2017.1351963
   Web of Science ®Google Scholar
• Linderoth, J. T., and A. Lodi. 2011. “MILP Software.” In Wiley Encyclopedia of Operations Research and Management Science. Wiley Online Library. doi:10.1002/9780470400531.eorms0524.
   Google Scholar
• Mancini, Sara, Francisco Bernal, and Juan A. Acebrón. 2016. “An Efficient Algorithm for Accelerating Monte Carlo Approximations of the Solution to Boundary Value Problems.” Journal of Scientific Computing 66 (2): 577–597. doi: 10.1007/s10915-015-0033-4
   Web of Science ®Google Scholar
• Max-Planck-Institut für Informatik. 2017. “UflLib.” Accessed 21 November 2017. http://resources.mpi-inf.mpg.de/departments/d1/projects/benchmarks/UflLib/packages.html
   Google Scholar
• Melo, M. Teresa, Stefan Nickel, and Francisco Saldanha-Da-Gama. 2009. “Facility Location and Supply Chain Management–A Review.” European Journal of Operational Research 196 (2): 401–412. doi: 10.1016/j.ejor.2008.05.007
   Web of Science ®Google Scholar
• Michel, Laurent, and Pascal Van Hentenryck. 2004. “A Simple Tabu Search for Warehouse Location.” European Journal of Operational Research 157 (3): 576–591. doi: 10.1016/S0377-2217(03)00247-9
   Web of Science ®Google Scholar
• Nanry, W. P., and J. W. Barnes. 2000. “Solving the Pickup and Delivery Problem with Time Windows Using Reactive Tabu Search.” Transportation Research Part B: Methodological 34 (2): 107–121. doi: 10.1016/S0191-2615(99)00016-8
   Web of Science ®Google Scholar
• Nielsen, I., Q.-V. Dang, G. Bocewicz, and Z. Banaszak. 2017. “A Methodology for Implementation of Mobile Robot in Adaptive Manufacturing Environments.” Journal of Intelligent Manufacturing 28 (5): 1171–1188. doi: 10.1007/s10845-015-1072-2
   Web of Science ®Google Scholar
• Nielsen, P., I. Nielsen, and K. Steger-Jensen. 2010. “Analyzing and Evaluating Product Demand Interdependencies.” Computers in Industry 61 (9): 869–876. doi: 10.1016/j.compind.2010.07.012
   Web of Science ®Google Scholar
• Pan, Q.-K., and R. Ruiz. 2012. “Local Search Methods for the Flowshop Scheduling Problem with Flowtime Minimization.” European Journal of Operational Research 222 (1): 31–43. doi: 10.1016/j.ejor.2012.04.034
   Web of Science ®Google Scholar
• Pirkul, Hasan, and Vaidyanathan Jayaraman. 1998. “A Multi-Commodity, Multi-Plant, Capacitated Facility Location Problem: Formulation and Efficient Heuristic Solution.” Computers & Operations Research 25 (10): 869–878. doi: 10.1016/S0305-0548(97)00096-8
   Web of Science ®Google Scholar
• Rei, W., M. Gendreau, and P. Soriano. 2010. “A Hybrid Monte Carlo Local Branching Algorithm for the Single Vehicle Routing Problem with Stochastic Demands.” Transportation Science 44 (1): 136–146. doi: 10.1287/trsc.1090.0295
   Web of Science ®Google Scholar
• Ruiz, R., and T. Stützle. 2007. “A Simple and Effective Iterated Greedy Algorithm for the Permutation Flowshop Scheduling Problem.” European Journal of Operational Research 177 (3): 2033–2049. doi: 10.1016/j.ejor.2005.12.009
   Web of Science ®Google Scholar
• Sitek, P., and J. Wikarek. 2016. “A Hybrid Programming Framework for Modeling and Solving Constraint Satisfaction and Optimization Problems.” Scientific Programming 2016: 5102616. doi: 10.1155/2016/5102616
   Google Scholar
• Sitek, P., and J. Wikarek. 2017. “Capacitated Vehicle Routing Problem with Pick-Up and Alternative Delivery (CVRPPAD): Model and Implementation Using Hybrid Approach.” Annals of Operations Research. doi:10.1007/s10479-017-2722-x.
   Web of Science ®Google Scholar
• Sun, Minghe. 2006. “Solving the Uncapacitated Facility Location Problem Using Tabu Search.” Computers & Operations Research 33 (9): 2563–2589. doi:10.1016/j.cor.2005.07.014.
   Web of Science ®Google Scholar
• Tavakkoli-Moghaddam, Reza, Samira Vazifeh-Noshafagh, Ata Allah Taleizadeh, Vahid Hajipour, and Amin Mahmoudi. 2017. “Pricing and Location Decisions in Multi-Objective Facility Location Problem with M/M/m/k Queuing Systems.” Engineering Optimization 49 (1): 136–160. doi: 10.1080/0305215X.2016.1163630
   Web of Science ®Google Scholar
• Vanderbilt, D., and S. G. Louie. 1984. “A Monte Carlo Simulated Annealing Approach to Optimization over Continuous Variables.” Journal of Computational Physics 56 (2): 259–271. doi: 10.1016/0021-9991(84)90095-0
   Web of Science ®Google Scholar
• Wolpert, David H., and William G. Macready. 1997. “No Free Lunch Theorems for Optimization.” IEEE Transactions on Evolutionary Computation 1 (1): 67–82. doi:10.1109/4235.585893.
   Google Scholar
• Yigit, Vecihi, M. Emin Aydin, and Orhan Turkbey. 2006. “Solving Large-Scale Uncapacitated Facility Location Problems with Evolutionary Simulated Annealing.” International Journal of Production Research 44 (22): 4773–4791. doi: 10.1080/00207540600621003
   Web of Science ®Google Scholar
• Zangeneh, Morteza, Asadolah Akram, Peter Nielsen, and Alireza Keyhani. 2015. “Developing Location Indicators for Agricultural Service Center: A Delphi–TOPSIS–FAHP Approach.” Production & Manufacturing Research 3 (1): 124–148. doi: 10.1080/21693277.2015.1013582
   Web of Science ®Google Scholar