Lower and upper bounds for the continuous single facility location problem in the presence of a forbidden region and travel barrier
RAIRO. Operations Research, Tome 55 (2021) no. 1, pp. 141-165

In this paper, we investigate FRB, which is the single facility Euclidean location problem in the presence of a (non-)convex polygonal forbidden region where travel and location are not permitted. We search for a new facility’s location that minimizes the weighted Euclidean distances to existing ones. To overcome the non-convexity and non-differentiability of the problem’s objective function, we propose an equivalent reformulation (RFRB) whose objective is linear. Using RFRB, we limit the search space to regions of a set of non-overlapping candidate domains that may contain the optimum; thus we reduce RFRB to a finite series of tight mixed integer convex programming sub-problems. Each sub-problem has a linear objective function and both linear and quadratic constraints that are defined on a candidate domain. Based on these sub-problems, we propose an efficient bounding-based algorithm (BA) that converges to a (near-)optimum. Within BA, we use two lower and four upper bounds for the solution value of FRB. The two lower and two upper bounds are solution values of relaxations of the restricted problem. The third upper bound is the near-optimum of a nested partitioning heuristic. The fourth upper bound is the outcome of a divide and conquer technique that solves a smooth sub-problem for each sub-region. We reveal via our computational investigation that BA matches an existing upper bound and improves two more.

DOI : 10.1051/ro/2020024
Classification : 90B85, 9008, 90C26
Keywords: Facility location, Euclidean distance, forbidden region, reformulation, divide and conquer, nested partitioning
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Al-Mudahka, Intesar M.; Al-Jeraiwi, Marwa S.; M’Hallah, Rym. Lower and upper bounds for the continuous single facility location problem in the presence of a forbidden region and travel barrier. RAIRO. Operations Research, Tome 55 (2021) no. 1, pp. 141-165. doi: 10.1051/ro/2020024

[1] I. Al-Mudahka, M. Hifi and R. M’Hallah, Packing circles in the smallest circle: an adaptive hybrid algorithm. J. Oper. Res. Soc. 62 (2011) 1917–1930. | DOI

[2] Y. P. Aneja and M. Parlar, Algorithms for Weber facility location in the presence of forbidden regions and/or barriers to travel. Transp. Sci. 28 (1994) 70–76. | Zbl | DOI

[3] M. Bischoff and K. Klamroth, An efficient solution method for Weber problems with barriers based on genetic algorithms. Eur. J. Oper. Res. 177 (2007) 22–41. | MR | Zbl | DOI

[4] R. Bosch and M. Trick, Integer programming, edited by E. K. Burke and G. Kendall. In: Search Methodologies: Introductory Tutorial in Optimization and Decision Support Techniques, Chapter 3. Springer, US (2005) 69–95. | DOI

[5] S. E. Butt, Facility location in the presence of forbidden regions. Ph.D. thesis, Pennsylvania State University, University Park, PA (1994).

[6] S. E. Butt and T. M. Cavalier, An efficient algorithm for facility locations in the presence of forbidden regions. Eur. J. Oper. Res. 90 (1996) 56–70. | Zbl | DOI

[7] S. E. Butt and T. M. Cavalier, Facility location in the presence of congested regions with the rectilinear distance metric. Socio Econ. Plan. Sci. 31 (1997) 103–113. | DOI

[8] E. W. Dijkstra, A note on two problems in connection with graphs. Numer. Math. 1 (1959) 269–271. | MR | Zbl | DOI

[9] Z. Drezner, Sensitivity analysis of the optimal location of a facility. Nav. Res. Log. Q. 32 (1985) 209–224. | MR | Zbl | DOI

[10] R. L. Francis, L. F. Mcginnis and J. A. White, Facility Layout and Location: An Analytical Approach. Prentice Hall, New York (1992).

[11] A. Ghaderi, M. S. Jabalameli, F. Barzinpour and R. Rahmaniani, An efficient hybrid particle swarm optimization algorithm for solving the uncapacitated continuous location-allocation problem. Netw. Spat. Econ. 12 (2012) 421–439. | MR | Zbl | DOI

[12] S. K. Ghosh and D. M. Mount, An output-sensitive algorithm for computing visibility graphs. SIAM J. Comput. 20 (1991) 888–910. | MR | Zbl | DOI

[13] H. W. Hamacher and K. Klamroth, Planar Weber location problems with barriers and block norms. Ann. Oper. Res. 96 (2000) 191–208. | MR | Zbl | DOI

[14] I. N. Katz and L. Cooper, Facility location in the presence of forbidden regions, II: Euclidean distance and several forbidden circles. Report OREM 79006, Department of Operations Research and Engineering Management, Southern Methodist University, Dallas, TX (1979).

[15] I. N. Katz and L. Cooper, Facility location in the presence of forbidden regions, III: lp distance and polygonal forbidden regions. Report OREM 79006, Department of Operations Research and Engineering Management, Southern Methodist University, Dallas, TX (1979).

[16] I. N. Katz and L. Cooper, Facility location in the presence of forbidden regions, I: formulation and the case of Euclidean distance with one forbidden circle. Eur. J. Oper. Res. 6 (1981) 166–173. | MR | Zbl | DOI

[17] L. A. Kazakovtsev, Algorithm for constrained Weber problem with feasible region bounded by arcs. Facta Univ. Ser.: Math. Inf. 28 (2013) 271–284. | MR | Zbl

[18] K. Klamroth, Single-Facility Location Problems with Barriers. Springer Series in Operations Research. Springer, Berlin (2002). | MR | Zbl

[19] H. Kuhn, A note on Fermat’s problem. Math. Program. 4 (1973) 98–107. | MR | Zbl | DOI

[20] R. F. Love, J. G. Morris and G. O. Wesolowsky, Facilities Location: Models and Methods. Elsevier, New York (1988). | MR | Zbl

[21] R. G. Mcgarvey and T. M. Cavalier, A global optimal approach to facility location in the presence of forbidden regions. Comput. Ind. Eng. 45 (2003) 1–15. | DOI

[22] M. A. Prakash, K. V. L. Raju and V. R. Raju, Facility location problems in the presence of mixed forbidden regions. Int. J. Appl. Eng. Res. 13 (2018) 91–97.

[23] B. Satyanarayana, K. V. L. Raju and K. V. V. Mohan, Facility location problems in the presence of single convex/non-convex polygonal barrier/forbidden region. Opsearch 41 (2004) 87–105. | MR | Zbl | DOI

[24] R. Sedgewick and J. S. Vitter, Shortest paths in Euclidean graphs. Algorithmica 1 (1986) 31–48. | MR | Zbl | DOI

[25] H. D. Sherali and I. Al-Loughani, Equivalent primal and dual differentiable reformulations of the Euclidean multifacility location problem. IIE Trans. 30 (1998) 1065–1074. | DOI

[26] H. D. Sherali and I. Al-Loughani, Solving Euclidean distance multi-facility location problems using conjugate subgradient and line-search methods. Comput. Optim. App. 14 (1999) 275–291. | MR | Zbl | DOI

[27] L. Shi and C. H. Chen, A new algorithm for stochastic discrete resource allocation optimization. Disc. Event Dyn. Syst. 10 (2000) 271–294. | MR | Zbl | DOI

[28] L. Shi and S. Men, Optimal buffer allocation in production lines. IIE Trans. 35 (2003) 1–10. | DOI

[29] L. Shi and S. Ólafsson, Nested partitions method for global optimization. Oper. Res. 48 (2000) 390–407. | MR | Zbl | DOI

[30] L. Shi, S. Ólafsson and Q. Chen, A new hybrid optimization algorithm. Comput. Ind. Eng. 36 (1999) 409–426. | DOI

[31] L. Shi, S. Olafsson and N. Sun, New parallel randomized algorithms for the traveling salesman problem. Comput. Oper. Res. 26 (1999) 371–394. | MR | Zbl | DOI

[32] G. A. Torres, A Weiszfeld-like algorithm for a weber location problem constrained to a closed and convex set. Preprint arXiv:1204.1087 (2012).

[33] G. Wangdahl, S. Pollock and J. Woodward, Minimum trajectory pipe routing. J. Ship Res. 18 (1974) 46–49. | DOI

[34] E. Weiszfeld, Sur le point par lequel la somme des distances de n points donnés est minimum. Tohoku Math. J. 43 (1937) 355–386. | Zbl

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